OpenAPI to MCP Server

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This project spins up a Model Context Protocol (MCP) server directly from the supplied openapi.yaml, using uv for dependency management. Every HTTP endpoint becomes an MCP tool that AnythingLLM (or any MCP-aware client) can call.

Quick Start

Install dependencies
```
uv sync
```

Configure openapi2mcpserver/config.yaml

base_url: "https://localhost:12001"
verify_ssl: false
openapi_path: "../openapi.yaml"           # Optional, defaults to the repo root copy
log_file: "../logs/openapi2mcpserver.log" # Optional, enables file logging
log_level: "INFO"                         # Optional, supports DEBUG/INFO/WARNING/ERROR

auth:
  mode: "basic"                           # Options: none/basic/bearer/header/query
  username: "your-username"
  password: "your-password"
  # basic_token: "cHJlLWVuY29kZWQtY3JlZHM="
  # extra_headers:
  #   X-API-Version: "1"

# default_headers:
#   X-Request-Source: "mcp"

Start the MCP server
```
uv run openapi2mcpserver
```

Using This MCP Server in AnythingLLM

The steps below target the AnythingLLM desktop plugin system and list the default paths for macOS and Windows. Create the file if it does not exist and replace the sample paths with the values on your machine.

macOS

Open ~/Library/Application Support/anythingllm-desktop/storage/plugins/anythingllm_mcp_servers.json

Add or merge the following configuration:

{
  "mcpServers": {
    "rhino-agent": {
      "command": "/Users/<你的用户名>/.local/bin/uv",
      "args": ["run", "--project", "/Users/<你的用户名>/workspace/AIProjects/openapi2mcpserver", "openapi2mcpserver"]
    }
  }
}

Windows

Open %APPDATA%\anythingllm-desktop\storage\plugins\anythingllm_mcp_servers.json

If you use uv.exe, replace the path with the output of where uv, for example:

{
  "mcpServers": {
    "rhino-agent": {
      "command": "C:\\Users\\<YourUser>\\AppData\\Roaming\\Python\\Scripts\\uv.exe",
      "args": ["run", "--project", "C:\\Users\\<YourUser>\\workspace\\AIProjects\\openapi2mcpserver", "openapi2mcpserver"]
    }
  }
}

Restart AnythingLLM (or reload plugins in settings) after saving, and you should see rhino-agent available in the tool list for your workspace.

Highlights

Automatically parses every OpenAPI path and registers a matching MCP tool
Exposes OpenAPI_GetSchema to inspect components.schemas
Tool inputs cover path params, query params, headers, and request bodies
Flexible authentication (none/basic/bearer/custom header/query) plus global default headers
Structured logging to both console and file for easier LLM troubleshooting

Layout

openapi2mcpserver/
    __init__.py
    __main__.py
    client.py
    config.py
    openapi_loader.py
    server.py

Runtime Notes

At startup the server ingests the OpenAPI description, builds JSON Schema input for every tool, and forwards calls to the upstream API. Responses (status, headers, and JSON/text bodies) are returned verbatim to the MCP client so you can chain follow-up actions such as polling task status.

MCP Servers