OpenAPI to MCP Server
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@OpenAPI to MCP Serverget the user profile for ID 12345"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
OpenAPI to MCP Server
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 syncConfigure
openapi2mcpserver/config.yamlbase_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
Related MCP server: mcpify
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.jsonAdd 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.jsonIf you use
uv.exe, replace the path with the output ofwhere 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_GetSchemato inspectcomponents.schemasTool 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.pyRuntime 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.
Related MCP Connectors
Create hosted MCP servers from any OpenAPI spec. Requires a free Kaiva Bridge account.
Zero-setup MCP gateway securely connecting AI to your tools with authentication and workflows
MCP server that lets AI assistants use all OneSchema features exposed via the public API.
The OpenRouter for tools. One MCP connection gives any AI agent 254 hosted tools, pay per call.
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