OpenAPI Slice MCP Server

@vvarp

代码仓库

基本信息

分类

其他

传输方式

stdio

作者

vvarp

提交者

Maciek Szczesniak

关于 OpenAPI Slice MCP Server

An MCP (Model Context Protocol) server that helps you work with large OpenAPI specifications by extracting only the relevant portions for specific endpoints. This is particularly useful when working with LLMs that have context limitations - instead of loading an entire large Open

#openapi

OpenAPI Slice MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "openapi-slice-mcp": {
      "command": "uvx",
      "args": [
        "openapi-slice-mcp"
      ]
    }
  }
}

OpenAPI Slice MCP Server 工具

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当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。

概览

What is OpenAPI Slice MCP?

OpenAPI Slice MCP is a Model Context Protocol server that extracts only the relevant portions of large OpenAPI specifications for specific endpoints. It helps developers and LLMs work with large specs by reducing context size through automatic dependency resolution, supporting both local files and remote URLs.

How to use OpenAPI Slice MCP?

Run the server with uvx openapi-slice-mcp. It communicates via STDIO and provides tools to load specs (from file or URL), list endpoints, extract endpoint slices, and check server status.

Key features of OpenAPI Slice MCP

Endpoint-specific extraction with automatic dependency resolution
Supports local YAML/JSON files and remote URLs (HTTP/HTTPS)
Output in YAML or JSON format
Discovery tool to list all endpoints in a loaded spec
Recursively includes all referenced components (schemas, parameters, etc.)

Use cases of OpenAPI Slice MCP

Extracting a minimal spec for a single API endpoint to fit within LLM context limits
Reducing token usage when sending OpenAPI definitions to AI assistants
Isolating endpoint definitions for testing or documentation generation

常见问题

What makes OpenAPI Slice MCP different from loading the full spec?

It extracts only the requested endpoint and its dependencies, unlike loading the entire OpenAPI specification. This is especially useful when working with LLMs that have context limitations.

What are the runtime requirements?

The server is run via `uvx` (from the uv package manager) and requires Python. No additional dependencies are listed beyond those bundled in the package.

Where does the data live?

Specifications can be loaded from local files (YAML/JSON) or fetched from remote URLs. No data is persisted on the server beyond the currently loaded spec.

What transport and authentication does it use?

The server uses STDIO transport and does not mention any authentication mechanism. It is designed for local or trusted setups.

Can I get the output in different formats?

Yes, the `extract_endpoint_slice` tool accepts an `output_format` parameter that can be set to `"yaml"` (default) or `"json"`.

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