MCP Server for AI-powered code review using Hy3 (Tencent Hunyuan)
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# hy3-code-review-mcp [](https://pypi.org/project/hy3-code-review-mcp/) [](https://pypi.org/project/hy3-code-review-mcp/) [](LICENSE) An MCP (Model Context Protocol) Server that brings **Hy3**'s 295B-parameter reasoning model into any MCP-compatible AI client as a plug-and-play code review assistant. Plug it into **Claude Code**, **CodeBuddy**, **Cursor**, **Cline**, or any MCP client and get: - Structured, severity-tagged code reviews from `git diff` - Deep single-file analysis (security / performance / bugs / style) - One-command pre-merge review of your local repository --- ## Requirements | Dependency | Notes | |---|---| | Python ≥ 3.10 | | | An OpenAI-compatible API endpoint | Local Hy3 (via vLLM/SGLang) **or** [OpenRouter](https://openrouter.ai/) | | `uv` (recommended) or `pip` | For installation | ### Option 1 — Local Hy3 (vLLM / SGLang) Follow the [Hy3 deployment guide](https://github.com/Tencent-Hunyuan/Hy3#deployment) to start vLLM or SGLang. The default endpoint is `http://127.0.0.1:8000/v1`. ```bash # Example: vLLM on 8×H20 GPUs vllm serve tencent/Hy3 \ --host 0.0.0.0 --port 8000 \ --tensor-parallel-size 8 \ --trust-remote-code ``` ### Option 2 — OpenRouter (no GPU required) Get a free API key at [openrouter.ai](https://openrouter.ai/), then set: ```bash export HY3_BASE_URL=https://openrouter.ai/api/v1 export HY3_API_KEY=<your-openrouter-key> export HY3_MODEL=tencent/hy3:free # or google/gemini-2.5-flash for faster responses ``` --- ## Installation ### Option A — one-liner with `uvx` (no install needed) ```bash uvx hy3-code-review-mcp ``` ### Option B — `pip install` ```bash pip install hy3-code-review-mcp hy3-code-review-mcp # starts the MCP server on stdio ``` ### Option C — from source ```bash git clone https://github.c…
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