Code Review Agent

AI 代码质量评审服务（Code Review as a Service）。把代码送给 LLM，返回结构化质量报告，亦可作为 MCP 工具被 Claude Code / Codex / Cursor 等 Agent 调用。

Submission for X-Agent AI MCP Hackathon 2026 · Open Innovation Challenge.

What it does

POST /v1/review — 提交代码片段，返回结构化评审报告（正确性 / 安全 / 性能 / 可维护性 / 最佳实践）
GET /health — 健康检查，返回当前部署 Commit
GET /.well-known/xagent-verification.json — 部署证明（slug + commit）
GET / — 在线演示页（粘贴代码即时出报告）
MCP 工具 review_code — 供 Agent 调用（stdio / streamable HTTP）

Quick start (local)

python -m venv .venv
source .venv/bin/activate        # Windows: .venv\Scripts\activate
pip install -r requirements.txt
cp .env.example .env             # 填入 LLM_API_KEY 等
uvicorn app.main:app --reload

Open http://127.0.0.1:8000 (demo page) or http://127.0.0.1:8000/docs (Swagger).

Example call:

curl -X POST http://127.0.0.1:8000/v1/review \
  -H "Content-Type: application/json" \
  -d '{"code": "def foo(a, b):\n    return a / b", "language": "python"}'

MCP usage

python -m app.mcp_server          # stdio transport for Claude Code / Codex / Cursor

Or register in your client config:

{
  "mcpServers": {
    "code-review-agent": {
      "command": "python",
      "args": ["-m", "app.mcp_server"]
    }
  }
}

Configuration (env vars)

Var	Default	Description
`LLM_BASE_URL`	`https://api.deepseek.com/v1`	OpenAI-compatible base URL
`LLM_API_KEY`	—	API key (required)
`LLM_MODEL`	`deepseek-chat`	Model name
`LLM_TIMEOUT_SECONDS`	`120`	LLM request timeout
`COMMIT`	`dev`	Deployed commit, returned by /health and /.well-known/xagent-verification.json

Deployment

Docker: docker build -t code-review-agent . && docker run -p 8000:8000 code-review-agent
Render: push to repo, set env vars, use render.yaml — set COMMIT to the exact deployed commit.

After deploy, verify:

curl https://<your-host>/health
curl https://<your-host>/.well-known/xagent-verification.json

License

UNLICENSED — submission-only use for X-Agent AI MCP Hackathon 2026.