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Analyze codebases and generate runnable MCP servers from existing capabilities.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "MCP Foundry" yet — see the docs or source repo.
Analyze this GitHub repository’s code structure and core features, identify capabilities that can be exposed, and generate a runnable FastMCP server with recommended tool definitions, connection settings, and startup instructions.
A runnable FastMCP server codebase, capability inventory, configuration recommendations, and deployment instructions.
I uploaded an internal tool project. Scan the codebase, find functions, APIs, and workflows suitable for MCP tools, prioritize them, and generate the corresponding server scaffold code.
A prioritized capability discovery report plus matching MCP tool definitions and server scaffold.
Based on this codebase, provide a conversion plan from existing modules to an MCP server, including capability mapping, dependency review, connector recommendations, and implementation code for a minimum viable runnable version.
A complete MCP integration plan and minimum viable implementation code for quick validation.
Discover and install suitable MCP servers across multiple registries.
Convert OpenAPI specs into MCP servers so AI agents can call APIs.
Build, debug, and manage software tasks with natural language across LLMs.
Search Hugging Face Papers and discover related code repositories quickly.
Turn any OpenAPI spec into a working MCP server.
Analyze code, collect code assets, and generate technical documentation automatically.