Generating MCP servers from OpenAPI: Lessons from building 50+ production MCP servers
Blog post from Speakeasy
The article outlines the challenges and solutions in generating Machine Communication Protocol (MCP) servers from OpenAPI documents, emphasizing the importance of optimizing OpenAPI descriptions for large language models (LLMs) that AI agents use. It highlights the tool explosion issue, where too many endpoints result in an overwhelming number of tools for LLMs to process, recommending pruning non-essential endpoints and optimizing OpenAPI documents to balance verbosity with clarity. The text also addresses the complexities LLMs face with intricate JSON formats and suggests transforming data into simpler structures to improve processing. Moreover, it discusses using scopes for enhanced access control, allowing server-side restrictions on tool usage rather than relying on client-side toggling. Speakeasy's approach involves customizing MCP servers through overlays and extensions to maintain clarity and usability while reducing manual adjustments, ultimately aiming to prevent hallucinations and errors in AI interactions.