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MCP Host CLI

@VyacheslavVanin

About MCP Host CLI

Local http server that proxies requests o LLMs and uses mcp-servers if needed

Basic information

Category

Developer Tools

Runtime

python

Transports

stdio

Publisher

VyacheslavVanin

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "mcp-http-host": {
      "command": "uv",
      "args": [
        "run",
        "main.py"
      ]
    }
  }
}

Tools

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Overview

What is MCP Host CLI?

It is a FastAPI server for chat interactions with LLMs, using OpenAI-compatible providers. It is configured via environment variables and CLI arguments, and supports tool approval workflows.

How to use MCP Host CLI?

Configure via environment variables (e.g., LLM_API_KEY, LLM_MODEL) or CLI arguments (e.g., --model, --port). Start the server using uv run main.py with desired options. Send requests to endpoints like POST /user_request and POST /approve.

Key features of MCP Host CLI

  • FastAPI server for chat interactions with LLMs
  • Configurable via environment variables and CLI arguments
  • Supports OpenAI-compatible providers (e.g., OpenRouter)
  • Tool approval workflow with request/response endpoints
  • Streaming mode and retry on LLM errors

Use cases of MCP Host CLI

  • Building a backend for chat interfaces with LLMs
  • Integrating LLM chat with tool approval mechanisms
  • Running a local or remote LLM chat server with OpenAI-compatible API

FAQ from MCP Host CLI

How do I configure the LLM model?

Use the LLM_MODEL environment variable or the --model CLI argument. Default is qwen2.5-coder:latest.

How do I provide the API key?

Set the LLM_API_KEY environment variable or use the --api-key-file CLI argument pointing to a file with the key.

What LLM providers are supported?

Only openai provider is supported, but the base URL can be changed (default OpenRouter).

How do I approve a tool call?

Send a POST request to /approve with request_id and approve boolean in the JSON body.

Where are debug messages logged?

If --debug-messages is enabled, logs are written to /tmp/llm-requester.messages.log.

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