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emcee

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Basic Information

emcee is a command-line tool that provides a Model Context Protocol (MCP) server for any web application that exposes an OpenAPI specification. It is designed to let developers expose API endpoints as MCP tools so MCP-capable clients like Claude Desktop can discover and call those APIs similarly to ChatGPT plugins. emcee runs as a stdio process using JSON-RPC 2.0, accepts an OpenAPI spec path or URL, and can be installed via Homebrew, Docker, an installer script, or built from source with Go. It includes options for authentication, request retries, rate limiting, timeouts, and logging. emcee also supports transforming OpenAPI specifications before serving them and intentionally focuses on providing MCP tool capabilities rather than higher-level resources or sampling features.

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App URL
https://github.com/loopwork-ai/emcee
Github Repository
https://github.com/loopwork-ai/emcee/blob/main/README.md

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App Details

Features
Core features include automatic MCP server generation from OpenAPI specifications and a stdio transport that speaks JSON-RPC 2.0. The CLI exposes flags for authentication methods (bearer, basic, raw and 1Password references), retries, requests-per-second rate limiting, request timeout, and verbose or silent logging. Distribution options include a platform installer script, Homebrew formula, prebuilt Docker images, and source builds requiring Go. The project documents example JSON-RPC methods for listing tools and invoking tools. It supports transforming and filtering OpenAPI specs with standard Unix tools, and it is compatible with the MCP Inspector for testing and debugging.
Use Cases
emcee helps developers quickly make existing web APIs available as tools to AI assistants and other MCP clients without writing a dedicated MCP server. It is particularly useful for services that lack an existing MCP implementation or for in-development APIs. By accepting OpenAPI specs, handling common authentication patterns, and offering rate limiting and retries, emcee reduces integration work and lets models request tool use that users can review and approve in a client UI. The ability to transform specs and use standard packaging methods makes it practical for local development, CI, and production workflows. Integration with the MCP Inspector aids debugging.

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