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0mcp
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0mcp

Turn existing APIs into MCP server

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Turn your existing APIs into production-ready MCP servers for AI agents and assistants. Import an OpenAPI spec, select the operations you want to expose, and instantly create a hosted MCP endpoint that works with modern AI clients and agent platforms.

Development · SaaS · API
Example Image
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Features

  • API to MCP — Convert existing APIs into AI-callable MCP tools without building an MCP server from scratch.
  • OpenAPI Import — Import your existing OpenAPI specification and automatically discover API operations.
  • AI-Optimized Tool Descriptions — Generate clear tool and parameter descriptions so AI models can better understand how to use your APIs.
  • Tool & Parameter Control — Choose which API operations, query parameters, path parameters, headers, and request bodies are exposed to AI.
  • Hosted MCP Endpoints — Deploy MCP servers without managing infrastructure, servers, or MCP runtime code.
  • Custom Domain Support — Use your own domain for MCP endpoints to maintain branding and production readiness.
  • One-Click Official MCP Registry Listing — Publish your MCP server directly to the official MCP registry with a single click for instant discoverability.
  • MCP Resources Support — Expose structured MCP resources alongside tools for richer context-aware AI interactions.
  • MCP Prompts Support — Define reusable prompts that AI clients can invoke to standardize workflows and behaviors.
  • Authentication & Security — Secure your MCP endpoints while keeping API credentials and sensitive request data protected.
  • Usage Monitoring — Track tool calls, response status, latency, errors, and other operational metadata.
  • Version Management — Compare API and MCP configurations across versions and safely manage changes.
  • AI Client Compatible — Connect your MCP servers with tools such as Claude, Cursor, ChatGPT, VS Code, Windsurf, Gemini, Codex, and custom MCP clients.

Use Cases

  • Make APIs AI-ready — Give AI agents access to existing SaaS APIs without rebuilding your backend.
  • Build AI Agent Integrations — Let agents securely search, create, update, and manage data through your existing APIs.
  • Expose SaaS Actions to AI — Turn product functionality into MCP tools that customers can use from their preferred AI clients.
  • Convert Internal APIs to MCP — Make private APIs accessible to internal AI assistants and automation workflows.
  • Prototype AI Integrations Faster — Test and ship MCP-based integrations without spending weeks building MCP infrastructure.
  • Connect Existing APIs to AI Clients — Bring APIs into Claude, Cursor, ChatGPT, VS Code, Windsurf, Gemini, Codex, and other MCP-compatible environments.
  • Modernize API Integrations — Extend existing REST and OpenAPI-based products into the emerging agent ecosystem without replacing your current API.
  • Control What AI Can Access — Select specific operations and parameters to expose instead of giving agents unrestricted access to an entire API.

Comments

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Founder @ 0mcp

Honestly, we built this because we kept running into the same problem: we had APIs that worked perfectly, but making them usable by AI agents meant building and maintaining a whole separate MCP layer. So we thought — why not make the boring part ridiculously simple? That’s basically how 0mcp started. Import your API, pick what you want to expose, and get an MCP server you can actually use in production. We’re still building a lot around it, and I’d genuinely love feedback from people working with MCPs. If you try it, tell me what feels useful, what feels annoying, or what you think we’re missing. 🚀

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Comments

custom-img
Founder @ 0mcp

Honestly, we built this because we kept running into the same problem: we had APIs that worked perfectly, but making them usable by AI agents meant building and maintaining a whole separate MCP layer. So we thought — why not make the boring part ridiculously simple? That’s basically how 0mcp started. Import your API, pick what you want to expose, and get an MCP server you can actually use in production. We’re still building a lot around it, and I’d genuinely love feedback from people working with MCPs. If you try it, tell me what feels useful, what feels annoying, or what you think we’re missing. 🚀

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