MCP Host CLI

@VyacheslavVanin

代码仓库

基本信息

分类

开发工具

传输方式

stdio

作者

VyacheslavVanin

关于 MCP Host CLI

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

MCP Host CLI 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

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

MCP Host CLI 工具

工具列表暂未提供

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。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

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

常见问题

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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