ContexaAI is the “Firebase for MCP servers”—a full-stack developer platform to build, test, debug, deploy, and manage Model Context Protocol (MCP) servers. Use it to standardize how your agents connect to tools and data so you ship faster, with less glue code. Directoryimage Contexa Sv

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What is ContexaAI?

A universal context layer for AI: browse a directory of thousands of MCP-powered tools (from Gmail to GitHub), convert your own APIs to MCP, and deploy production-ready servers with observability and scale—no DevOps required.
Why MCP? It’s an open standard for connecting AI to tools and data—often described as the “USB-C of AI apps”—and it’s now supported across major platforms.

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What you can do here

  • Use thousands of tools out of the box. Discover and deploy MCP context providers from the Directory.
  • Convert your APIs to MCP. Point Contexa at an OpenAPI spec to generate tools and package them as a server.
  • Import from GitHub or start from templates. Deploy a public repo as a server in a few clicks.
  • Compose and bundle. Create custom servers and bundles that group tools for specific use cases.
  • One-click deploy & scale. Push to Contexa Cloud and get logging, metrics, and versioning out of the box.
  • Test in the built-in Playground. Chat with your server and compare models.

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Why ContexaAI

  • Lightning-fast integration. Connect tools & APIs to any agent framework in minutes via MCP.
  • Universal compatibility. Works with MCP-capable clients (e.g., OpenAI Responses/Agents, Microsoft Copilot Studio, and Gemini tooling).
  • Developer-first. Clean workflows, templates, and docs designed by builders, for builders.

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How ContexaAI fits into your stack

  1. Create – Upload an OpenAPI spec, import from GitHub, or start from a template to generate an MCP server.
  2. Test – Use the Playground to validate tools, arguments, and responses with your preferred model.
  3. Deploy – One-click to Contexa Cloud; scale and observe usage.
  4. Integrate – Point your agent client at the server and go (OpenAI, Copilot Studio, Gemini CLI/SDK, etc.).

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Who is this for?

  • Product & engineering teams shipping AI features fast
  • Platform teams standardizing tool access org-wide
  • Indie builders & agencies who want less plumbing, more shipping