Yapi Auto MCP Server

The Yapi Auto MCP Server is a dedicated Model Context Protocol (MCP) gateway that bridges the popular YApi interface‑management platform with AI programming assistants such as Cursor and Claude Desktop. By exposing YApi’s project, category, and API data through MCP, the server lets an AI agent understand the exact shape of your backend contracts in real time. This eliminates the need to manually copy and paste API specifications into prompts, allowing developers to query, view, or modify endpoints directly while coding.

At its core, the server offers a suite of tools that map naturally to common API‑centric tasks. Search and retrieval commands let the assistant locate interfaces by name, path, or tags; detail‑fetching tools return full request and response schemas, including JSON Schema and form data representations. Creation and update utilities () let the assistant add new endpoints or patch existing ones, automatically handling status flags and category assignments. These operations are performed over the same lightweight stdio or SSE streams that MCP uses, ensuring minimal latency and seamless integration into existing AI workflows.

Key capabilities extend beyond simple CRUD. The server supports multiple YApi projects simultaneously, allowing a single AI session to switch contexts or aggregate documentation across micro‑services. A built‑in caching layer speeds repeated queries, while detailed logging and configurable log levels make debugging straightforward. The command‑line interface accepts environment variables or explicit arguments, so teams can tailor token scopes, cache TTLs, and port numbers to their deployment pipelines.

In practice, Yapi Auto MCP shines when developers need instant, accurate API guidance while writing code. An AI assistant can answer questions like “Show me the login endpoint” or “Add a captcha field to the registration API,” then generate corresponding client stubs, test cases, or documentation snippets—all without leaving the coding environment. For teams that maintain large, evolving API catalogs, this tight integration reduces copy‑paste errors, keeps documentation in sync with the codebase, and accelerates onboarding for new contributors.

Ultimately, Yapi Auto MCP provides a frictionless bridge between human intent and machine‑readable API contracts. By exposing YApi’s rich metadata through MCP, it empowers AI assistants to deliver context‑aware suggestions, automate repetitive API management tasks, and keep backend specifications consistently aligned with front‑end development.