Where to List Your API or MCP Server (2026)

The complete directory and launch strategy for listing your API, MCP server, or AI agent tool across 47 marketplaces, registries, and developer platforms in 2026.

The MCP ecosystem grew from zero to 97 million monthly SDK downloads in 18 months. That is a 970x increase from the handful of servers that existed when Anthropic released the protocol in November 2024 - MCP Manager. The global API market is expected to reach $12.54 billion in 2026, projected to grow to $87.55 billion by 2035 - Nordic APIs. Over 21,000 MCP servers are now indexed across registries - Glama. The OpenAI GPT Store, Hugging Face Spaces, and the Zapier integration directory each serve millions of developers. And yet, most builders ship their API or MCP server and list it in exactly one place.

This is the discovery problem in 2026: building the product is the first 50%. Getting it found is the other 50%. The developer tools market has fragmented into dozens of specialized marketplaces, each with its own audience, listing requirements, and discovery mechanics. An MCP server listed only on npm is invisible to the 85,000 developers browsing the Awesome MCP Servers list on GitHub. An API listed only on RapidAPI is invisible to AI agents discovering tools via the Official MCP Registry. A tool listed only on Product Hunt gets a one-day spike and then disappears.

This guide maps every major marketplace, registry, and developer platform where you should list your API, MCP server, or AI agent tool. We cover 47 platforms across 8 categories, with exact traffic numbers, listing requirements, and a sequenced launch strategy that maximizes discovery across all channels. Whether you are a solo developer shipping your first MCP server or a company launching an enterprise API product, this is the distribution playbook.

Written by Yuma Heymans (@yumahey), founder of O-mega.ai and co-founder of HeroHunt.ai, who has launched developer products across dozens of these platforms. The distribution strategy described here is the same one used to ship Suprsonic's unified agent API to its initial developer audience.

Contents

1. The Master Directory: All 47 Platforms, Ranked by Impact
2. The Discovery Shift: From Humans to Agents
3. MCP Server Registries: The New Category
4. Package Registries: Where Code Lives
5. API Marketplaces: Where Enterprise Buyers Shop
6. AI Tool Directories: Where Volume Traffic Lives
7. Developer Communities: Where Technical Credibility Is Built
8. Agent Framework Integrations: Where Agents Find Tools
9. Standards and Open Directories: The Machine-Readable Layer
10. The Launch Sequence: Week-by-Week Strategy
11. How to Write a Listing That Gets Discovered
12. The Trust Problem and How to Solve It

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1. The Master Directory: All 47 Platforms, Ranked by Impact

How to read this table: Each cell contains a score (0-10) and its justification. The Final Score is: (Reach x 0.30) + (Relevance x 0.30) + (Effort x 0.20) + (Longevity x 0.20). Only the top 10 are shown here. The full 47 platforms are profiled in sections 3-9 below.

Criteria rationale:

• Reach (30%): How many developers/buyers will see your listing? Traffic, audience size, search visibility. Highest weight because discovery is the primary goal.
• Relevance (30%): How targeted is the audience for your specific product type (API, MCP server, agent tool)? A million visitors who are not developers are less valuable than 10,000 who are. Equal weight to reach because targeted visibility beats broad visibility.
• Effort (20%): How much work to create and maintain the listing? 10 = minutes, auto-indexed. 1 = weeks of prep, editorial review, ongoing maintenance.
• Longevity (20%): How long does the visibility last? 10 = permanent, compounds over time. 1 = one-day spike, then gone.

The top 3 (npm/PyPI, GitHub, Official MCP Registry) are infrastructure-level: every developer product should be listed there regardless of category. The next tier (Awesome MCP Servers, PulseMCP, Glama, Smithery) are MCP-specific and essential for MCP server publishers. The remaining platforms are situational based on your product type and audience.

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2. The Discovery Shift: From Humans to Agents

The most important structural change in API distribution in 2026 is that the entity discovering your API is increasingly a machine, not a human. AI agents in Claude, Cursor, Windsurf, and VS Code Copilot discover tools by querying MCP registries programmatically. RAG pipelines ingest your documentation and surface it in response to natural language queries. LLM-powered search engines like Perplexity and Google AI Overviews summarize your product page without the user ever visiting your website.

This changes what "listing" means. In the old model, you wrote a marketing page for a human visitor who would read it, click around, and make a purchase decision. In the new model, you write a machine-readable capability manifest that an AI agent can parse, understand, and decide to use without any human involvement.

The practical implications for every listing you create:

Structure your data for machines, not just humans. Every API listing should include an OpenAPI spec, a JSON Schema for your MCP tool definitions, and structured metadata (categories, capabilities, pricing, latency) that an agent can filter programmatically. As we covered in our guide to LLM tool gateways, the MCP protocol is the standard interface for this machine-to-machine discovery.

Implement llms.txt. The llms.txt standard (proposed by Jeremy Howard of Answer.AI in 2024) places a plain-text Markdown file at your domain root that maps your site's most important resources for LLM consumption. Adoption is at 10.13% across 300,000 surveyed domains and growing - AEO.press. Developer tools like Cursor, Continue, and Aider already read it. Anthropic, Stripe, Zapier, and Cloudflare have adopted it. Implementation takes 30 minutes: create a file at yourdomain.com/llms.txt that describes your API's purpose, capabilities, and links to documentation - Bluehost.

Register in the Official MCP Registry. This is the canonical source that MCP clients query programmatically. When an agent in Claude Desktop, Cursor, or any MCP-compatible client looks for a tool, the Official Registry is the first place it checks. Registration requires namespace authentication via reverse-DNS format (e.g., io.github.username/server), verified through GitHub login or domain ownership - Official Registry, Nordic APIs.

The AWS Agent Registry (Bedrock AgentCore), announced in preview April 2026, takes this further: a private governed catalog for agents, tools, and MCP servers within enterprise environments. Azure API Center now supports registering MCP servers alongside APIs in the Azure portal, with a plugin marketplace discoverable from Claude Code and GitHub Copilot - AWS, Microsoft Learn.

The takeaway: listing your product in human-readable directories (Product Hunt, G2, AI tool aggregators) still matters for brand awareness and initial buzz. But listing in machine-readable registries (Official MCP Registry, npm/PyPI, llms.txt, OpenAPI specs) is what determines whether AI agents discover and use your tool.

This is a fundamental shift in distribution economics. In the human-first model, you invest in marketing to reach humans who then evaluate and adopt your tool. The cost per acquisition is high (hundreds of dollars per enterprise lead), the cycle is slow (weeks to months), and the reach is limited by your marketing budget. In the agent-first model, you invest in machine-readable metadata once, and then every AI agent in the ecosystem can discover your tool at zero marginal cost. The reach is limited only by how many agents query the registries, which is growing at 970x in 18 months.

The practical implication: every hour spent polishing your Official MCP Registry listing, your OpenAPI spec, and your llms.txt file generates more cumulative usage than every hour spent on Product Hunt prep, because the machine-readable discovery channel is always on, always growing, and scales without additional effort. The human-readable channels are still important for brand building and initial traction, but the machine-readable channels are where the compounding returns live.

This does not mean you should ignore human-facing platforms. It means you should invest in them in the right order: machine-readable infrastructure first (weeks -2 to 1), human-facing launch events second (weeks 2-4), long-tail directories third (weeks 6-12). The machine layer provides the foundation that makes every subsequent human-facing listing more credible and more effective. As we analyzed in our 50 best MCP servers guide, the protocol's 110 million monthly SDK downloads mean the machine-discovery channel is already larger than most human-browsed directories.

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3. MCP Server Registries: The New Category

MCP registries are the newest and fastest-growing category of developer marketplaces. Eighteen months ago, none of these existed. Today, they collectively index over 21,000 servers and are the primary discovery mechanism for the 110 million monthly MCP SDK downloads - Effloow.

If you are publishing an MCP server, you should list on ALL of the following. There is no reason not to: they are all free, and each has a different audience.

The Official MCP Registry (registry.modelcontextprotocol.io)

The canonical registry, backed by Anthropic, GitHub, PulseMCP, and Microsoft. Launched September 8, 2025, with an API freeze at v0.1 as of October 2025 - MCP Blog. This is the registry that MCP clients query programmatically, which means being listed here is not about human visitors. It is about being discoverable by every AI agent that uses the protocol.

Registration requires namespace authentication. You claim a namespace in reverse-DNS format (e.g., io.github.yourusername/your-server), verify ownership via GitHub login or domain verification, and submit your server's metadata. The open-source spec allows sub-registries to mirror and extend it, but the official registry is the root of trust - GitHub.

Why it matters: Every major MCP client (Claude Desktop, Cursor, Windsurf, VS Code Copilot, Replit, Zed) can query this registry. If your server is not here, it does not exist for programmatic discovery.

Glama (glama.ai/mcp/servers)

The largest volume directory at 21,845+ servers, updated daily. Glama auto-indexes open-source MCP servers, which means if your server is public on GitHub with the right metadata, it may already be listed without you submitting anything. Glama also provides an MCP Inspector (for testing servers) and a Gateway (for proxying requests) - Glama.

The REST API allows programmatic access to the directory, making Glama useful not just for human browsing but for automated tooling that needs to discover and catalog MCP servers.

PulseMCP (pulsemcp.com)

The quality-filtered directory. PulseMCP has been hand-reviewing every MCP server since launch week in November 2024. The founder personally writes descriptions for each of the 12,970+ servers listed. This editorial curation means that a listing on PulseMCP carries more credibility than auto-indexed directories - PulseMCP.

PulseMCP also contributes data to the Official MCP Registry and runs a newsletter, which provides additional visibility for newly listed servers. Submit your server at the main site and it enters the review queue.

Smithery (smithery.ai)

Smithery combines a registry with hosted remote server infrastructure. The 7,000+ servers can be installed via one CLI command (smithery mcp install), and Smithery can host your server on their infrastructure so users do not need to run it locally - Smithery Docs.

Publish via smithery mcp publish from the CLI. The experience is intentionally npm-like: package, version, publish. For MCP server developers who want the simplest distribution path, Smithery's combination of registry + hosting + CLI is the most streamlined.

Security caveat: A path traversal vulnerability was disclosed in October 2025 that exposed 3,000+ hosted servers and API keys - WorkOS. Verify that the issue has been fully remediated before hosting sensitive servers on Smithery's infrastructure.

mcp.so

The second-largest directory at 20,289+ servers, mcp.so differentiates through usage-based rankings. While most registries rank by listing date or GitHub stars, mcp.so ranks by actual call volume, meaning servers that get used rise to the top regardless of their marketing or star count. This makes it a more honest barometer of what developers actually deploy in production - mcp.so.

The community-submitted model means there is no editorial review. This is both an advantage (immediate listing) and a disadvantage (no quality filter). For well-built servers, the usage-based ranking rewards real utility over hype. For new servers, the chicken-and-egg problem applies: you need usage to rank, but you need ranking to get usage.

MCP Market (mcpmarket.com)

MCP Market serves 10,000+ servers across 23+ categories with a distinctive daily top-100 leaderboard based on GitHub stars. The one-click Cline integration is particularly useful: developers using the Cline IDE can install servers directly from the MCP Market listing without leaving their editor - MCP Market.

The daily leaderboard format creates a gamification dynamic that is absent from other registries. If your server accumulates stars quickly (e.g., from a Product Hunt or Hacker News launch), it will appear on the leaderboard, which drives additional discovery. This creates a positive feedback loop that benefits servers with strong initial launches.

LobeHub MCP Marketplace

LobeHub's marketplace integrates 10,000+ tools and MCP-compatible plugins directly into the LobeHub platform. The one-click install means LobeHub users can add your server without any CLI commands, configuration files, or manual setup. This is the most frictionless installation path for non-technical users who want to extend their AI assistant - LobeHub.

The marketplace is community-driven, meaning anyone can contribute. For server developers targeting the LobeHub ecosystem specifically, this is a direct distribution channel. For others, it is an incremental listing that takes minutes and adds another discovery surface.

Composio MCP Directory (mcp.composio.dev)

Composio manages 500+ MCP servers with 1,000+ toolkits and 20,000+ tools. The key differentiator is managed authentication: Composio handles OAuth flows for you, which means users do not need to configure API keys for services like Slack, GitHub, or Google Workspace - Composio.

Claude Desktop Extensions Directory

The highest-value listing for MCP servers. Accessible directly within Claude Desktop (Settings > Extensions), this directory requires Anthropic editorial review for policy, security, and brand safety. Getting listed here means direct distribution to every Claude Desktop user with zero friction (one-click install) - Anthropic.

The review process is more selective than open registries, but the distribution is unmatched. If your MCP server passes Anthropic's review, it becomes a first-class extension of Claude.

Enterprise MCP Registries

For enterprise customers, four dedicated registries have emerged in 2026, each serving a different enterprise ecosystem.

Kong MCP Registry extends the existing Kong Konnect API management platform with MCP-specific capabilities: RBAC for controlling which teams can access which MCP servers, audit logs for compliance, and versioning for managing server upgrades. Launched as tech preview in February 2026, it is designed for organizations that already manage APIs through Kong and want to extend that governance to their MCP infrastructure - Kong.

MACH Alliance MCP Registry takes a vendor-neutral approach: a central directory that is not restricted to MACH Alliance members. Any organization can register MCP servers, and any MCP client can query it. The MACH Alliance (Microservices, API-first, Cloud-native, Headless) audience is enterprise commerce and content teams, making this particularly relevant for MCP servers that serve e-commerce, CMS, or digital experience use cases - MACH Alliance.

Azure API Center MCP lets organizations register MCP servers alongside their existing APIs in the Azure portal. The standout feature is the plugin marketplace: registered MCP servers become discoverable from Claude Code and GitHub Copilot, meaning enterprise developers using those tools can find and install your server without leaving their IDE. This is a uniquely powerful distribution channel because it meets developers where they already work - Microsoft.

AWS Agent Registry (Bedrock AgentCore) is the newest addition, announced in preview April 2026. It provides a private governed catalog for agents, tools, and MCP servers within an AWS environment. The governance layer includes access controls, usage tracking, and approval workflows for new tools. For enterprise customers running agent workloads on AWS Bedrock, this registry is the sanctioned way to manage which tools their agents can access - AWS.

These enterprise registries are not where you go for broad developer discovery. They are where you go for enterprise procurement. If your MCP server is used by a Fortune 500 company's AI agents, being listed in that company's Kong or Azure API Center registry is what makes the difference between a pilot and a production deployment. The listing is typically handled by the enterprise customer's platform team rather than by you directly, but providing the right metadata (OpenAPI spec, security documentation, SLA commitments) makes their job easier and accelerates adoption.

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4. Package Registries: Where Code Lives

Package registries are the foundation of developer product distribution. They are not "marketplaces" in the traditional sense (no browsing, no reviews, no featured listings), but they are where the actual installation happens. Every MCP server, SDK, and CLI tool needs to be on the right package registry.

npm (npmjs.com)

The world's largest software registry with 3.1+ million packages - npm. For TypeScript/JavaScript MCP servers and SDKs, npm is the canonical distribution channel. The MCP TypeScript SDK is distributed via npm, and every MCP server tutorial starts with npm install.

Publishing is straightforward: npm publish from your project directory. Use a scoped package name (e.g., @yourorg/your-mcp-server) for organizational clarity. Include a README with usage instructions, and ensure your package.json has accurate keywords (mcp, agent, api) for search discoverability.

The npm listing page is often underestimated as a marketing asset. It is where developers land after finding your package through a search, a blog post, or a recommendation. A good npm page has: a one-line description that says what it does (not what it is), a minimal code example that shows the simplest possible usage, a link to full documentation, and badges showing build status, test coverage, and latest version. Most developers decide within 30 seconds of landing on an npm page whether to install.

Weekly download counts are visible on every npm page and serve as social proof. A package with 10,000 weekly downloads is inherently more credible than one with 50. Early downloads from your team, beta testers, and CI pipelines matter because they seed this number before organic discovery kicks in.

PyPI (pypi.org)

Python's package registry with 816,269 packages and 136.7 billion downloads in March 2026 (4.41 billion per day) - PyPI Stats. For Python MCP servers, SDKs, and AI tools, PyPI is essential. The MCP Python SDK and virtually every AI framework (LangChain, LlamaIndex, CrewAI) distribute via PyPI.

Publish via twine upload or the newer flit publish. Include a README.md that renders on the PyPI page, and use classifiers (e.g., Topic :: Scientific/Engineering :: Artificial Intelligence) for categorization. The PyPI page supports Markdown rendering, so your README should be visually clear with code blocks, installation commands, and usage examples.

The Python AI ecosystem is enormous: PyTorch alone had 45 million monthly downloads in early 2026. Being on PyPI means your package appears in pip search results and is installable with the universal pip install yourpackage command that every Python developer knows. For AI agent tools specifically, the Python ecosystem is the primary language: LangChain, LlamaIndex, CrewAI, Instructor, and the Anthropic/OpenAI SDKs are all Python-first.

GitHub (github.com)

GitHub is simultaneously the source code host, the release distribution channel, and the primary trust signal for developer tools. With 630+ million repositories and 150+ million developers, it is the largest developer platform - Kinsta. GitHub Copilot, used by 20 million developers, reads your repository's code and documentation, making your GitHub presence a factor in AI-assisted coding recommendations.

For MCP servers specifically, GitHub stars are the primary ranking signal used by MCP Market, mcpfind.org, and other directories. The Awesome MCP Servers list (85.2K stars) is the second-most-starred MCP resource after the official reference repository (84.2K stars). Your GitHub repository's README is often the first page a developer sees, making it your most important marketing asset.

The README structure that converts: start with a one-line description, then a "Quick Start" section with installation + minimal usage in under 30 seconds, then a features list, then detailed documentation. Do NOT start with a contributor guide, badges wall, or project governance. Those belong at the bottom. The first thing a developer sees should answer "what does this do and how do I use it."

GitHub Actions (CI/CD) are also a distribution mechanism: if your MCP server passes automated tests on every commit, the green checkmark on your repo signals reliability. Publishing releases via GitHub Releases with a changelog makes version management transparent and gives you a URL to link from other listings.

Docker Hub (hub.docker.com)

Essential for distributing containerized MCP servers that run remotely. As MCP shifts from local stdio transport to remote Streamable HTTP, Docker images become the standard packaging format for servers that run on cloud infrastructure. The Docker Verified Publisher program adds a trust badge that signals enterprise-grade quality.

The containerization trend in MCP is accelerating. Local stdio servers (running as subprocesses on the developer's machine) are convenient for development but impractical for team deployments. Remote servers (running in Docker containers on cloud infrastructure) serve multiple users, handle authentication centrally, and scale independently. If you are building an MCP server intended for production use, publishing a Docker image is no longer optional.

Include a docker-compose.yml example that shows the simplest possible deployment. Tag your images with semantic versions (v1.2.3) and a rolling latest tag. Use multi-stage builds to minimize image size (MCP servers rarely need a full OS; Alpine-based images work for most cases).

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5. API Marketplaces: Where Enterprise Buyers Shop

If your product is an API (with or without an MCP server), these marketplaces connect you with developers and enterprise buyers who are actively looking for APIs to integrate.

RapidAPI (rapidapi.com)

The largest API marketplace with 80,000-98,000+ APIs and 5-8 million registered developers. RapidAPI raised $150M at a $1B valuation in 2022 - TechCrunch.

Listing is free. You set your pricing model (freemium, pay-per-call, or subscription), and RapidAPI handles billing, API key management, and analytics. Consumers get a unified API key for all RapidAPI-listed services, reducing integration friction. The built-in testing interface means developers can try your API without writing code.

For AI agent-focused APIs, RapidAPI's "AI" category has grown significantly. The platform's massive developer base means even a niche API gets meaningful discovery if the listing is well-optimized with keywords and clear descriptions.

Postman API Network (postman.com/explore)

The world's largest public API network with 100,000+ public APIs and 40+ million users ($5.6B valuation) - Postman. Postman rebuilt as an "AI-native" platform in March 2026, adding an API Catalog management plane.

Create a public Postman workspace, add your API as a collection with examples and documentation, and publish to the network. Collections are immediately testable by any of Postman's 40M users, which dramatically lowers the barrier to evaluation. The new API Catalog features governance and lifecycle management for teams managing multiple APIs.

Cloud Marketplaces (AWS, Azure, Google Cloud)

For enterprise API products, cloud marketplaces are the procurement channel. Buyers use existing cloud credits and billing relationships, which removes the procurement friction that kills deals.

AWS Marketplace launched a Discovery API in April 2026 for programmatic catalog access. Starting June 2026, new SaaS listings require Concurrent Agreements. ISV Success incentive program provides go-to-market support - AWS, Clazar.

Azure Marketplace has 41,000+ products (doubled from 15,700 in 2021), adding 130+ new offers per week. The new unified "Microsoft Marketplace" combines Azure Marketplace and AppSource. The MCP plugin marketplace integration means your MCP server can be discoverable from Claude Code and GitHub Copilot - Microsoft, The New Stack.

Google Cloud Marketplace uses a three-tier partner system (Select, Premier, Diamond) introduced in Q1 2026, with up to 24 pricing plans per product - Clazar.

The cloud marketplace strategy requires a different mindset than developer-community launches. Enterprise buyers on AWS, Azure, and GCP are spending committed cloud credits. They actively prefer marketplace listings because the spending counts against their cloud commitment (which they have already budgeted) rather than creating a new line item that requires procurement approval. This means that an API product listed on a cloud marketplace has a structural pricing advantage over the same product sold via a direct website: the buyer perceives it as "free" because it comes from existing budget.

The trade-off is complexity: cloud marketplace listings require technical integration (provisioning APIs, entitlement checks, usage metering), take 2-5 days for review, and incur a platform fee (typically 3-20% depending on the marketplace and tier). For early-stage products, this overhead is not justified. For products with enterprise customers who ask "can we pay via AWS," it is table stakes.

The recommended approach: start with RapidAPI and Postman for developer discovery (immediate, free, broad reach), then add cloud marketplace listings only when you have enterprise customers requesting it. The enterprise customer's request is the signal that the integration cost is worth it.

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6. AI Tool Directories: Where Volume Traffic Lives

AI tool directories aggregate thousands of tools and attract millions of monthly visitors. They are not developer-specific (the audience includes marketers, managers, and other non-technical users), but the traffic volume can drive meaningful discovery, especially for products with broad appeal.

There's An AI For That (theresanaiforthat.com)

The #1 AI tool directory by traffic with 7.79 million monthly visits (February 2026). Average session duration is 7 minutes 41 seconds, indicating high engagement - Semrush. 43% of traffic is organic search, which means your listing benefits from TAAFT's domain authority for AI-related queries.

Free submission. Paid featured placement is available for priority visibility. The audience is broad (India, US, Germany are the top countries), so this works best for tools with general appeal rather than developer-only APIs.

Futurepedia (futurepedia.io)

5,000+ curated AI tools, 500K+ accounts, and a YouTube channel with 2 million+ subscribers - Futurepedia. The YouTube audience is a unique advantage: a feature on the Futurepedia channel can drive thousands of signups from a single video.

Tools are "meticulously evaluated" before listing, so the editorial bar is higher than auto-indexed directories. This curation makes a Futurepedia listing a stronger signal of quality than an auto-submitted listing on larger directories.

Toolify.ai

28,815+ AI tools across 459 categories with 2.01 million monthly visits. Rankings are based on actual traffic data, not editorial picks, which means popular tools naturally rise to the top - Toolify.

TopAI.tools, ToolPilot AI, SaaSHub

TopAI.tools ranks 20K+ tools by real usage signals across 120+ categories. ToolPilot AI (DR 76) provides do-follow backlinks, which benefits your SEO. SaaSHub (77,686 products, 267K visits/month, DR 76) focuses on alternatives and comparisons, making it particularly useful for competitive positioning - TopAI, SaaSHub.

G2 (g2.com)

The world's largest software review platform with 2 million+ verified user reviews and 100,000+ products. G2 scores influence enterprise purchasing decisions. The API-specific categories include API Platforms, API Management, API Development, and API Marketplace.

A basic G2 listing is free. Reviews from verified users are the currency: more (positive) reviews mean higher rankings. For enterprise API products, G2 reviews are often required during the procurement evaluation process. Procurement teams at large organizations use G2 reports as one of their primary evaluation inputs, and a product without a G2 profile is at a structural disadvantage in enterprise sales cycles.

The G2 review strategy requires patience. You cannot buy reviews (G2 verifies reviewer identity), and soliciting reviews too aggressively triggers G2's fraud detection. The recommended approach: after a customer has been using your product for 30+ days and has expressed satisfaction (via support ticket, NPS survey, or verbal feedback), send a personalized email asking them to share their experience on G2. Provide a direct link to your G2 review page. Respond publicly to every review (both positive and negative) to show engagement.

Five genuine reviews from paying customers is the minimum threshold for appearing in G2 category rankings. Ten or more reviews with an average above 4.0/5.0 places you in the "High Performer" quadrant, which is the sweet spot for products that are gaining traction but not yet dominant.

AlternativeTo (alternativeto.net)

Crowd-sourced alternatives with 2.6 million monthly visits and 63.63% organic search traffic. AlternativeTo dominates Google results for "alternative to [competitor]" queries, which means your listing captures long-tail SEO traffic over months and years - Similarweb. Do-follow backlinks included.

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7. Developer Communities: Where Technical Credibility Is Built

Developer communities provide the highest-quality feedback and the most durable credibility. A front-page Hacker News post or a well-received DEV Community tutorial creates trust that no paid listing can replicate.

Hacker News (Show HN)

The premier technical community. A top Show HN post gets 50,000-100,000+ views from the most technically sophisticated audience on the internet. The feedback is blunt, informed, and invaluable.

Strategy: Talk as a fellow builder, not a marketer. Go deep into technical details. Open-source and privacy-first products dramatically overindex. The most successful Show HN posts explain the "why" (what problem you solved) before the "what" (your product). Answer every comment, including hostile ones, by first acknowledging the point before responding. Cross-post to Reddit the same day - Markepear.

DEV Community (dev.to)

Global rank ~13,600 with traffic growing 7.5% month-over-month and 63% organic search traffic - Similarweb. DEV is the platform for long-form technical content that drives sustained discovery.

Publish tutorials showing how to use your API/MCP server in real workflows. Tag appropriately (webdev, ai, mcp, api, tutorial). Articles that explain "how I built X" or "how to use Y for Z" consistently outperform product announcements. The SEO value of DEV articles is significant: Google indexes them quickly, and they often rank for long-tail developer queries.

Reddit

Multiple relevant subreddits, each with different cultures. r/SideProject welcomes self-promotion. r/LocalLLaMA is highly engaged with AI tools. r/webdev is large but hostile to marketing. r/MachineLearning has weekly self-promotion threads.

Critical caveat: r/programming banned all LLM content in 2026 - Tom's Hardware. Do not post AI-related tools there.

The 90/10 rule applies everywhere on Reddit: 90% value-add contributions (answering questions, sharing insights), 10% self-promotion. Open-source projects have a structural advantage because they are inherently community contributions rather than marketing.

DevHunt (devhunt.org)

"Product Hunt for devs." Open-source platform with GitHub-verified voting, which prevents the fake upvote gaming that plagues Product Hunt. Limited weekly launch slots create authentic competition - DevHunt. The audience is exclusively developers, making feedback more relevant than Product Hunt's broader community.

BetaList (betalist.com)

Curated pre-launch/early-stage directory. DR 75 with do-follow backlinks. Free submission (weeks-long queue) or $49-$129 to skip the queue. Best for building a beta tester waitlist before your full launch. Expect 50-200 monthly clicks per listing for the first 90 days - BetaList.

The Developer Community Strategy: Build, Don't Market

The common thread across all developer communities is authenticity. Hacker News, Reddit, and DEV Community are allergic to marketing language. The communities reward builders who share their process, explain their technical decisions, and engage honestly with criticism. The most successful developer tool launches on these platforms follow a consistent pattern.

First, you contribute before you promote. Spend 2-4 weeks answering questions in relevant subreddits, commenting thoughtfully on Hacker News threads, and publishing useful content on DEV Community. This builds a reputation that makes your launch post credible rather than spammy.

Second, you lead with the problem, not the product. "I was building an AI agent and couldn't find a good way to handle contact enrichment, so I built this" resonates with developer communities. "Introducing the world's most advanced enrichment platform" gets downvoted and ignored. The former invites conversation. The latter invites skepticism.

Third, you open-source something. Even if your core product is commercial, open-sourcing a component (an SDK, a utility library, a benchmark dataset) gives the community something to evaluate, contribute to, and advocate for. Open-source contributions are the strongest form of developer marketing because they create genuine value rather than just claiming it.

Fourth, you treat negative feedback as a gift. The developer who says "this doesn't handle edge case X" is telling you something your QA missed. Respond with gratitude, acknowledge the gap, and fix it publicly. The community watches how you respond to criticism more closely than they watch your product demo. A founder who engages constructively with a hostile HN comment earns more trust than one who ignores it.

This approach is slower than paid advertising or directory listings. It takes weeks instead of minutes. But the credibility it builds compounds indefinitely, and it creates organic advocates who recommend your product to other developers without being asked. For our analysis of how agents handle autonomous outreach (which is structurally similar to how developers discover new tools), see our guide to AI recruitment agents.

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8. Agent Framework Integrations: Where Agents Find Tools

If your product is a tool that AI agents use, getting listed in agent framework directories is as important as getting listed in human-browsed marketplaces. These directories are where agent developers discover and integrate tools into their workflows.

OpenAI GPT Store

The most mature AI agent marketplace, built into ChatGPT. Custom GPTs with system prompts, knowledge files, and Actions (API calls). Revenue share on U.S. user engagement. The audience is ChatGPT's hundreds of millions of users - Digital Applied.

Create a custom GPT that wraps your API's capabilities. The editorial review checks for brand safety, quality, and retention. OpenAI periodically deindexes low-quality listings, so maintaining quality is essential for long-term visibility.

Hugging Face Spaces

18 million monthly visitors platform-wide with 5 million registered users. Publish a Gradio or Streamlit demo app that showcases your API's capabilities. The "try before you clone" model means developers can interact with your tool immediately without any setup - Fueler.

The pattern: host model weights on Hugging Face Hub, inference code on GitHub, and an interactive demo on Spaces. The Trending algorithm provides discovery for new launches. Free CPU tier means zero hosting cost for demos.

LangChain Hub, LlamaIndex LlamaHub, CrewAI Tools

Contribute integration packages to the major agent frameworks. LangChain Hub has 300+ integration packages. LlamaHub provides data loaders and agent tools for LlamaIndex. CrewAI Tools are accessible through the CrewAI-tools GitHub repo. Each framework's integration directory is browsed by developers building agents in that ecosystem - LangChain Hub, LlamaHub, CrewAI Tools.

If your tool has an MCP server, it is automatically accessible to any agent framework that supports MCP. But having a native framework integration (a LangChain tool wrapper, a LlamaIndex loader) reduces friction further and increases visibility within that ecosystem.

Zapier and Make Integration Directories

Zapier has 9,000+ app integrations and recently added MCP support, meaning AI agents can access all Zapier-connected apps through a single MCP endpoint. The Zapier Developer Platform is self-serve and free - Zapier. Make (formerly Integromat) has 3,000+ integrations for visual workflow automation.

These platforms reach the no-code/low-code audience, not just developers. If your API serves a broad business function (CRM, email, payments, scheduling), a Zapier integration dramatically expands your addressable market beyond the developer community.

The economic case for Zapier integration is compelling: Zapier's 9,000+ apps mean that your API becomes combinable with every other app in the ecosystem. A user who connects your enrichment API to their CRM via Zapier would never have found you through a developer community. They found you because Zapier's interface surfaced your app as a relevant connection when they searched for "find email addresses." This cross-ecosystem discovery is unique to integration platforms and does not exist on any other type of directory.

The Make (Integromat) audience is smaller but more technical. Make users build complex multi-step workflows that often involve conditional logic, data transformation, and error handling. If your API is used in sophisticated automation scenarios, Make's visual builder makes those workflows transparent and shareable, which creates organic word-of-mouth among automation builders.

The Framework Integration Decision

The question of which agent frameworks to integrate with is not "all of them." It is "which ones reach your target user?" Each framework has a different audience profile.

LangChain (most popular, broadest audience) is the right choice if your tool serves general-purpose agent use cases. A LangChain integration makes you discoverable to the largest agent developer community. However, the LangChain ecosystem is also the most crowded: hundreds of integrations compete for attention.

LlamaIndex (data-focused, RAG-heavy) is the right choice if your tool handles document processing, data loading, or knowledge retrieval. LlamaIndex's LlamaHub is the primary discovery channel for data sources and ETL tools used in RAG pipelines.

CrewAI (multi-agent orchestration) is the right choice if your tool is used by agents that collaborate in teams. CrewAI's multi-agent model means your tool might be called by a "researcher" agent, a "writer" agent, and a "reviewer" agent in the same workflow.

The MCP protocol cuts across all frameworks: if your tool has an MCP server, any framework that supports MCP can use it without a framework-specific integration package. This is the strongest argument for building an MCP server first and framework-specific integrations second. The MCP server gives you universal compatibility; the framework integration gives you first-class visibility within a specific ecosystem.

Dify Marketplace, Vercel Marketplace, Cloudflare AI

Dify marketplace serves agentic workflow builders with model, tool, and data source plugins - Dify. Vercel Marketplace has a dedicated Agents category for AI services within the Next.js/React developer ecosystem (curated, not open submission) - Vercel. Cloudflare runs agents on Workers with inference-metered pricing, billing only for model inference while Workers execution is free - Cloudflare.

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9. Standards and Open Directories: The Machine-Readable Layer

Beyond marketplaces and registries, there is a layer of standards and open directories that enable machine-to-machine discovery. These are the lowest-effort, highest-persistence listings.

llms.txt

Place a file at yourdomain.com/llms.txt that describes your product for LLM consumption. Current adoption: 10.13% across 300K surveyed domains, with Anthropic, Stripe, Zapier, and Cloudflare already implementing it - AEO.press.

The format is simple Markdown: a title, a brief description of what your product does, and links to the most important pages (API docs, pricing, getting started guide). Developer tools like Cursor and Aider already read this file. No major AI platform has committed to reading it as first-class input yet, but the cost of implementation is near-zero and the upside is future-proofed discovery.

APIs.guru / OpenAPI Directory

"Wikipedia for Web APIs." 4,432 API definitions in OpenAPI 3.0 format, updated daily, CC0-1.0 license. Submit your OpenAPI spec via GitHub PR. The directory is consumed by tooling that builds on top of standardized API specs - APIs.guru, GitHub.

Schema.org Structured Data

Implement Schema.org markup on your documentation and product pages. This structured data acts as a "nutrition label" for search engines and AI systems, helping them understand and recommend your product. AI systems in 2026 favor well-structured content with explicit metadata over keyword-optimized prose - Zoer.

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10. The Launch Sequence: Week-by-Week Strategy

Listing on all 47 platforms simultaneously is a waste of effort. The order matters. Here is the sequenced approach that maximizes impact while managing effort.

Pre-launch (Week -2 to -1): Ship your package to npm and/or PyPI. Push source code and a polished README to GitHub. Implement llms.txt on your domain. Register on the Official MCP Registry (if you have an MCP server). Submit your OpenAPI spec to APIs.guru.

These are infrastructure-level listings that should exist before any marketing activity. They are permanent, low-effort, and high-value.

MCP Registration Wave (Week 1): Submit to PulseMCP, Glama, Smithery, mcp.so, MCP Market, and open a PR on Awesome MCP Servers. Submit to Claude Desktop Extensions if your server meets Anthropic's quality bar. Register on Composio if your server benefits from managed auth.

MCP registries are fast (most review within days) and free. Listing across all of them costs nothing and maximizes the surface area for programmatic discovery. Listings that are updated within 30 days rank 2-3x higher than those untouched for 90+ days - TrueFoundry.

API Marketplace Wave (Week 2): List on Postman API Network (create public workspace with testable collections), RapidAPI (set freemium pricing model). If enterprise-ready, begin AWS/Azure/GCP Marketplace onboarding (2-5 day review cycles).

Launch Day (Week 3, Tuesday 12:01 AM PT): Launch on Product Hunt. Same day: submit a Show HN post. Publish a technical tutorial on DEV Community. The Product Hunt algorithm in 2026 rewards engagement signals (comments, maker replies, time-on-page) over raw upvotes, so focus on responding to every comment quickly - LaunchList.

You need 200+ first-hour supporters queued from your waitlist, and the critical upvote window is 6-9 AM PT. Tuesday and Wednesday launches consistently outperform other days. Products that bring new users to PH (rather than just activating existing PH users) get algorithmic boost.

Post-Launch Wave (Week 4-6): Submit to DevHunt, BetaList ($49-129 to skip queue). Post to Reddit (r/SideProject, r/LocalLLaMA if AI-related). Submit to agent framework directories (LangChain, LlamaIndex, CrewAI) if you have integration packages.

Long-Tail Wave (Week 6-12): Submit to AI tool directories: There's An AI For That, Futurepedia, Toolify, TopAI.tools. Register on review platforms: G2, AlternativeTo, SaaSHub. These directories generate sustained traffic over months (not spikes), so the investment pays off gradually through SEO and organic discovery.

Why This Order Matters

The sequencing is not arbitrary. It follows a dependency chain where earlier listings support later ones.

Infrastructure first because every other listing links back to your GitHub repo, npm package, or PyPI page. If a developer discovers your product on Product Hunt, the first thing they do is check the GitHub repo. If it does not exist or looks abandoned, the Product Hunt upvote is wasted. Similarly, the Official MCP Registry listing provides programmatic discoverability that every subsequent listing benefits from.

MCP registries second because they have the fastest review cycles (hours to days) and provide the broadest machine-discovery surface. Once your server is in PulseMCP, Glama, and the Awesome list, any MCP client can discover it. This means developers using Claude, Cursor, or any MCP-compatible tool can find you before your marketing launch even happens.

API marketplaces third because they require more preparation (Postman collections, RapidAPI pricing configuration) but provide long-term, high-intent traffic. A developer searching for "email verification API" on RapidAPI is closer to a purchase decision than one browsing Product Hunt.

Launch day fourth because it requires the most preparation and generates the most concentrated traffic. By this point, your GitHub repo has stars (from MCP registry browsers), your npm package has initial downloads (from MCP server installations), and your API marketplace listing has been tested by early users. This social proof makes your Product Hunt and Hacker News launches more credible.

Long-tail directories last because they generate sustained but lower traffic. Submitting to TAAFT, Futurepedia, and G2 in week 1 would waste the initial momentum that Product Hunt and HN generate. Submitting in week 6-12 extends the visibility window and captures the SEO traffic that builds slowly over months.

Common Mistakes to Avoid

The most common mistake is launching on Product Hunt before your GitHub repo exists. The PH audience clicks through to your site, finds no source code or documentation, and bounces. The second most common mistake is neglecting MCP registries entirely and wondering why AI agents cannot discover your tool. The third is submitting to 20 directories on day one and then never updating any of them (stale listings rank 2-3x lower than updated ones).

The approach that works is disciplined sequencing with consistent follow-through. Submit to 5-7 platforms per week over 12 weeks, update each listing monthly, and invest the most effort in the platforms with the highest impact (GitHub, npm/PyPI, Official MCP Registry, Product Hunt, Hacker News).

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11. How to Write a Listing That Gets Discovered

The same product listed with good metadata gets 10x more discovery than one listed with bad metadata. Here is what matters for each platform type.

For MCP registries: Your tool name should be descriptive (not clever). @yourorg/mcp-github-issues is better than @yourorg/octopus. The description should state what the server DOES in one sentence (not what it IS). "Create, search, and manage GitHub issues and pull requests via MCP" is better than "A GitHub integration for AI agents." Include the number of tools exposed, supported transports (stdio, Streamable HTTP), and any authentication requirements.

For package registries (npm/PyPI): Keywords matter for search. Include mcp, ai-agent, tool, and your domain-specific keywords. The README is your landing page: start with a one-line description, then installation command, then a minimal usage example that runs in under 30 seconds. Do not start with a logo, badges, or contributor guidelines. Those go at the bottom.

For API marketplaces: Include a freemium tier. APIs with a free tier on RapidAPI get 5-10x more trial activations than paid-only APIs. Set the free tier at a level that lets developers evaluate your API in a real workflow (100-1,000 calls/month, not 10). Include example response payloads in your documentation so developers know exactly what they are getting.

For AI tool directories: Submit a screenshot of your product in action (not a logo). Directories with screenshots get 3-5x more clicks than those with just text listings. Include pricing in the description: directories that surface pricing rank higher because users can evaluate without clicking through. Tag your listing with every relevant category. TAAFT, Toolify, and Futurepedia all use category-based browsing, and missing a relevant tag means missing an entire discovery pathway.

For Product Hunt: The tagline matters more than the description. It should be under 60 characters and state the benefit ("One API for 30+ agent capabilities"), not the technology ("Unified REST API with waterfall provider routing"). Include a 2-minute demo video. First comment from the maker should explain the backstory (why you built it, what problem it solves).

The Product Hunt algorithm in 2026 has shifted significantly from pure upvote counting. The platform now rewards engagement depth: comments that spark conversations, maker replies that add value, and time-on-page for visitors who view your listing. This means that 50 genuine comments with maker replies outperform 500 drive-by upvotes with no engagement. Prepare thoughtful responses to common questions before launch day. Have 5-10 genuine beta users ready to post detailed reviews as comments during the critical 6-9 AM PT window.

The "hunter" system (where a well-known PH user "hunts" your product for visibility) is less impactful than it was in 2024. The algorithm has been tuned to reduce the influence of individual power users and increase the weight of authentic community engagement. Self-hunting is now the default recommendation from PH's own team.

For Hacker News: The title should be modest and specific. "Show HN: I built an MCP server that connects Claude to 500+ APIs" works. "Revolutionary AI tool that changes everything" will be flagged and buried. Respond to every comment, even the critical ones. The HN community respects builders who engage honestly with feedback.

The timing of your HN post matters more than you think. The best time to post is typically between 8-10 AM ET on weekdays, when the US East Coast is active but the post queue is not yet saturated. Posts on Monday mornings compete with a backlog from the weekend. Posts on Friday afternoons get buried by weekend traffic. Tuesday through Thursday mornings are the sweet spot.

Cross-posting strategy: post on HN and Product Hunt on the same day, but stagger by a few hours. HN upvotes and comments create social proof that PH visitors see when they research your product. Similarly, a trending PH launch creates a Google-searchable page that HN commenters reference when discussing your product. The two platforms amplify each other when timed correctly.

For developer communities (Reddit, DEV, Twitter/X): Authenticity is the only currency that works. Write about the problem you solved before you write about the solution. Share your build process, including the mistakes. Developers respect honesty about limitations more than they respect polished marketing. If your MCP server does not handle a particular edge case, say so upfront. The community will respect the transparency and often contribute solutions.

The long-term value of developer community engagement exceeds the short-term value of directory listings by an order of magnitude. A single well-received Hacker News post or a viral DEV tutorial generates GitHub stars, npm downloads, and organic word-of-mouth that no directory listing can match. The directory listings provide the infrastructure (so developers can find you when they search). The community posts provide the catalysts (so developers want to search for you in the first place).

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12. The Trust Problem and How to Solve It

The final piece of the distribution puzzle: trust. With 21,000+ MCP servers in the ecosystem, only 12.9% score "high trust" (70+ out of 100) - Bloomberry. AgentSeal scanned 1,808 servers and found 66% had security findings. Endor Labs analyzed 2,614 implementations and found 82% use file operations prone to path traversal - AgentSeal, DEV Community.

This means the developer evaluating your listing has strong reasons to be skeptical. Building trust requires deliberate effort across every listing.

Open source your server. Open-source MCP servers are inherently more trustworthy because the code is auditable. The Awesome MCP Servers list, which has 85.2K stars, focuses exclusively on open-source servers. Closed-source MCP servers face a structural trust deficit that no amount of marketing can overcome.

Get GitHub stars. Stars are the primary trust signal in the MCP ecosystem. MCP Market ranks by GitHub stars. Developers use star count as a proxy for community validation. This means your GitHub repo's README, documentation quality, and community engagement directly affect your discovery across all platforms that reference GitHub data.

Pass security audits. If you are listed on Smithery's hosted infrastructure, ensure your server does not expose sensitive file paths, environment variables, or credentials. If you are distributing via npm, ensure your package does not include source maps (the Claude Code leak happened because a source map was accidentally included in the npm package). Run basic security scanning (npm audit, Snyk) before publishing.

Maintain freshness. Listings updated within 30 days rank 2-3x higher than stale listings across most registries - TrueFoundry. Set a calendar reminder to update your listings monthly, even if the changes are minor (version bumps, documentation improvements, new examples).

Collect reviews on G2 and similar platforms. Enterprise buyers check G2 before making procurement decisions. Five genuine reviews from paying customers outweigh any number of directory listings. Actively ask satisfied users to leave reviews, and respond to every review (positive or negative) publicly.

The structural insight is that trust compounds across platforms. A well-maintained GitHub repo with stars, a verified listing on the Official MCP Registry, a positive G2 profile, and an open-source codebase create a reinforcing trust loop that no single listing can achieve alone.

The Trust Hierarchy

Not all trust signals are equal. Here is the hierarchy, ordered from strongest to weakest for developer tools in 2026.

Tier 1 (Strongest): Open-source code on GitHub with active maintenance, verified namespace on the Official MCP Registry, passing security scans (npm audit, Snyk). These are verifiable, objective signals that cannot be faked.

Tier 2: GitHub stars (social proof, but can be gamed), G2 reviews from verified users, Product Hunt upvotes (weaker than stars because the audience is less technical).

Tier 3: AI directory listings (TAAFT, Futurepedia, Toolify), marketing website claims, blog posts. These are self-reported and carry minimal independent verification.

Tier 4 (Weakest): Social media mentions, paid placements, "as seen on" badges. These signal marketing budget, not product quality.

The mistake most developers make is investing heavily in Tier 3 and 4 signals (directory listings, marketing) while neglecting Tier 1 (open source, security, maintenance). A developer evaluating your MCP server will check your GitHub repo before they check your Product Hunt page. If the repo has 3 commits, no tests, and no documentation, no amount of directory listings will save you.

Measuring Distribution Effectiveness

After listing across multiple platforms, you need to understand which ones actually drive usage. Track these metrics per platform.

For package registries (npm/PyPI): Weekly download counts, trending position, referral traffic to your documentation.

For MCP registries: Discovery via programmatic queries (if the Official Registry provides analytics), rankings on mcp.so (call volume), and GitHub stars trajectory (which MCP Market uses for rankings).

For API marketplaces: API calls from marketplace-provisioned keys, conversion from free tier to paid, average revenue per user.

For launch platforms: Day-one traffic spike, sustained traffic after 7/30 days, conversion to signups, quality of feedback received.

For communities: Referral traffic from HN/Reddit/DEV, new GitHub stars attributable to the post, quality of issues and PRs opened by community members.

Most builders do not track these metrics per platform, which means they cannot tell whether a listing on RapidAPI is worth more than a listing on Futurepedia. The data almost always shows that infrastructure-level listings (npm, GitHub, Official MCP Registry) and community posts (HN, DEV) drive more sustained usage than directory listings, which generate traffic spikes that decay within weeks. But without measuring, you are allocating effort blindly.

As we covered in our analysis of how the big pipe of LLM inference is eating software, the distribution landscape for developer tools is being reshaped by the same forces that are reshaping software itself: AI agents are increasingly the entities that discover, evaluate, and adopt tools. The developers and directories are still important, but the machine-readable layer is where the growth is.

For builders using platforms like Suprsonic that provide unified API access to 17+ agent capabilities, the distribution strategy is to be present across both the human-browsed directories (for brand awareness) and the machine-readable registries (for agent discovery). The shift from human-first to agent-first discovery means that the machine-readable layer (Official MCP Registry, llms.txt, OpenAPI specs) will eventually generate more usage than the human-browsed layer (Product Hunt, G2, AI directories). But in 2026, you need both.

This guide reflects the API, MCP, and developer tool distribution landscape as of April 2026. Marketplace policies, traffic patterns, and listing requirements change frequently. Verify current details on each platform before listing.