MCP LLM Bridge

@virajsharma2000

リポジトリ

基本情報

カテゴリ

AI とエージェント

ライセンス

MIT license

トランスポート

stdio

作者

virajsharma2000

MCP LLM Bridge について

A Simple bridge from Ollama to a fetch url mcp server

MCP LLM Bridge の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "simple-mcp-ollama-bridge": {
      "command": "uv",
      "args": [
        "venv"
      ]
    }
  }
}

MCP LLM Bridge のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is MCP LLM Bridge?

MCP LLM Bridge connects Model Context Protocol (MCP) servers to OpenAI‑compatible LLMs such as Ollama. It is intended for developers who want to use local or remote LLMs with MCP‑based tooling.

How to use MCP LLM Bridge?

Clone the repository, set up a Python virtual environment with uv, install the package, then edit src/mcp_llm_bridge/main.py to configure the MCP server parameters and LLM connection (API key, model, base URL). The bridge supports any endpoint implementing the OpenAI API specification, including Ollama running locally.

Key features of MCP LLM Bridge

Connects MCP servers to OpenAI‑compatible LLMs
Works with any OpenAI‑compliant endpoint (e.g., Ollama, GPT‑4o)
Configured via a single Python file (main.py)
Supports local LLM models for privacy and offline use
Uses uv for dependency management and installation

Use cases of MCP LLM Bridge

Run MCP‑enabled tools with a local Ollama model instead of a cloud API
Bridge existing MCP servers to OpenAI‑compatible LLMs for sampling or tool use
Test MCP integrations against a local LLM before deploying to a production endpoint

よくある質問

What does MCP LLM Bridge do?

It bridges any MCP server to an OpenAI‑compatible LLM, allowing the LLM to use MCP resources, prompts, and tools.

What dependencies are required?

Python, `uv`, and an LLM endpoint that implements the OpenAI API (e.g., Ollama). No additional runtime beyond the Python environment.

How do I configure the bridge?

Edit `src/mcp_llm_bridge/main.py` to set `mcp_server_params` (pointing to your MCP server) and `llm_config` (API key, model, base URL). Example configurations for Ollama and GPT‑4o are shown in the file.

Does it work with cloud LLMs?

Yes, the bridge can connect to any OpenAI‑compatible API, including GPT‑4o, by setting the appropriate `api_key` and `model`.

What is the transport mechanism?

The MCP server communicates over stdio (via `StdioServerParameters`), while the LLM is accessed via HTTP using the OpenAI API format.

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