MCP
@otoTree
About MCP
No overview available yet
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"mcp-ototree": {
"command": "uv",
"args": [
"init",
"project",
"-",
"name"
]
}
}
}Tools
No tools detected
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Overview
What is MCP?
MCP (Model Context Protocol) is a client tool that exposes local MCP servers through Flask, enabling platforms like Coze, Dify, and FastGPT to interact with local resources via self-hosted intranet penetration.
How to use MCP?
Set up the environment with uv, create a project directory, activate a virtual environment, and install dependencies from pyproject.toml. Configure mcp_server.json with server definitions and set environment variables in a .env file. Run python server.py to start the Flask server. Use POST requests to endpoints like /list_tool, /call_tool, /list_server, /list_files, and GET requests to /get_download_link/<secret_key>/<filename>.
Key features of MCP
- Exposes local MCP servers via HTTP API.
- Supports multiple server definitions in a JSON config.
- Provides endpoints to list tools, call tools, and list servers.
- Includes file listing and download link generation.
- Uses secret key authentication for API requests.
- Works with self-signed certificates for local development.
Use cases of MCP
- Integrate local MCP tools (e.g., weather, filesystem) with cloud AI platforms.
- Allow Coze, Dify, or FastGPT to call local Python scripts via API.
- Securely expose file management capabilities to external services.
- Debug and test MCP server interactions with a simple REST interface.
FAQ from MCP
What is required to run MCP?
You need uv installed, a virtual environment, and dependencies from pyproject.toml. A mcp_server.json file defines the servers to expose, and a .env file holds sensitive keys.
How do I configure servers in MCP?
Edit mcp_server.json with entries containing desc, command, and args. Each entry represents an MCP server that will be exposed via the Flask API.
Is authentication supported?
Yes, all API endpoints require a secret_key in the request body (or URL path for downloads). The secret is defined in the .env file.
Can I use MCP in production?
The README recommends using formal SSL certificates from a trusted CA (e.g., Let’s Encrypt) for cloud deployment, as self-signed certificates may cause issues on platforms like Coze.
What transports does MCP support?
MCP uses HTTP POST and GET endpoints via a Flask server. The default transport is REST over HTTP/HTTPS. No other transports (like WebSocket) are mentioned.
Frequently asked questions
What is required to run MCP?
You need `uv` installed, a virtual environment, and dependencies from `pyproject.toml`. A `mcp_server.json` file defines the servers to expose, and a `.env` file holds sensitive keys.
How do I configure servers in MCP?
Edit `mcp_server.json` with entries containing `desc`, `command`, and `args`. Each entry represents an MCP server that will be exposed via the Flask API.
Is authentication supported?
Yes, all API endpoints require a `secret_key` in the request body (or URL path for downloads). The secret is defined in the `.env` file.
Can I use MCP in production?
The README recommends using formal SSL certificates from a trusted CA (e.g., Let’s Encrypt) for cloud deployment, as self-signed certificates may cause issues on platforms like Coze.
What transports does MCP support?
MCP uses HTTP POST and GET endpoints via a Flask server. The default transport is REST over HTTP/HTTPS. No other transports (like WebSocket) are mentioned.
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