API To MCP turns REST, GraphQL, SaaS, and internal business APIs into hosted MCP servers that AI agents can use in minutes. Build visually from the dashboard, or let an AI agent create, test, and deploy tools from API docs. End users can connect live MCP servers to ChatGPT, Claude, Codex, Cursor, VS Code, Antigravity, or custom agents with OAuth, secure auth, workflows, and forkable snapshots.
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API to MCP is a hosted platform that converts REST, GraphQL, SaaS, and internal business APIs into remote HTTP MCP (Model Context Protocol) servers. These servers let AI agents—like ChatGPT, Claude, Codex, Cursor, VS Code, and Antigravity—call real API tools directly. You can build servers visually through a dashboard or let an AI agent create, test, and deploy them from API documentation. The platform handles authentication, encrypted credentials, workflow tools, and forkable snapshots, so teams can expose live data to agents without manual server setup.
A guided dashboard lets you configure authentication, define API tools and workflow tools, map output with JMESPath, test requests, and deploy a production MCP endpoint—all without writing code. You control every step before publishing.
Connect the API to MCP manager server to your coding agent once, then ask the agent to create, update, test, and deploy servers from chat. The agent handles the entire pipeline, from describing the API to returning the MCP URL.
Supports OAuth, API keys, Bearer tokens, and Basic Auth for upstream APIs. Stored credentials—including client secrets, access tokens, and refresh tokens—are encrypted at rest and masked in the owner UI. Snapshots never include live secrets.
Beyond simple API calls, you can add workflow tools that chain multiple endpoints or transform responses. JMESPath output mapping lets you shape API responses into clean tool outputs that agents can use immediately.
"Build hosted MCP servers for real APIs, from the UI or your AI agent."
This platform removes the friction of setting up and securing MCP infrastructure. Instead of writing custom server code for each API, you either click through a dashboard or describe what you need to an AI agent. The result is a production-ready, hosted MCP endpoint that agents can call with OAuth or other auth methods. It's a practical bridge between real-world APIs and the growing ecosystem of AI coding and chat tools.
You want to give AI agents live access to business platforms, marketing APIs, commerce systems, developer tools, or public data—without building and maintaining MCP servers yourself. It's especially useful if your team uses multiple AI agents (ChatGPT, Claude, Codex, Cursor) and needs a consistent way to expose authenticated API tools.
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