repowise MCP工具

<a href="https://www.repowise.dev"><img src=".github/assets/banner.png" alt="repowise: the codebase intelligence layer for your AI coding agent" width="100%" /></a>

<p align="center"><strong>Five intelligence layers · Nine MCP tools · 15 languages · Multi-repo workspaces · One <code>pip install</code></strong></p>

<p align="center"> <a href="https://www.repowise.dev"><img src="https://img.shields.io/badge/LIVE_DEMO-repowise.dev-F59520?style=for-the-badge&labelColor=0A0A0A" alt="Live demo: repowise.dev" /></a> <a href="https://github.com/repowise-dev/repowise"><img src="https://img.shields.io/badge/Star_this_repo-1E293B?style=for-the-badge&logo=github&logoColor=white&labelColor=0A0A0A" alt="Star repowise on GitHub" /></a> </p>

<p align="center"> <a href="https://pypi.org/project/repowise/"><img src="https://img.shields.io/pypi/v/repowise?style=for-the-badge&color=1E293B&labelColor=0A0A0A&logo=pypi&logoColor=white" alt="PyPI version" /></a> <a href="https://www.gnu.org/licenses/agpl-3.0"><img src="https://img.shields.io/badge/License-AGPL--v3-059669?style=for-the-badge&labelColor=0A0A0A" alt="License: AGPL v3" /></a> <a href="https://pypi.org/project/repowise/"><img src="https://img.shields.io/badge/Python-3.11%2B-1E293B?style=for-the-badge&labelColor=0A0A0A&logo=python&logoColor=white" alt="Python 3.11+" /></a> <a href="https://modelcontextprotocol.io"><img src="https://img.shields.io/badge/MCP-compatible-1E293B?style=for-the-badge&labelColor=0A0A0A" alt="MCP compatible" /></a> <a href="https://github.com/repowise-dev/repowise/stargazers"><img src="https://img.shields.io/github/stars/repowise-dev/repowise?style=for-the-badge&logo=github&color=1E293B&labelColor=0A0A0A&logoColor=white" alt="GitHub stars" /></a> </p>

<p align="center"> <a href="https://www.repowise.dev/#contact"><strong>Hosted for teams →</strong></a> · <a href="https://docs.repowise.dev"><strong>Docs</strong></a> · <a href="https://discord.gg/cQVpuDB6rh"><strong>Discord</strong></a> · <a href="mailto:hello@repowise.dev"><strong>Contact</strong></a> </p>

<p align="center">_{<a href="#the-five-layers">Layers</a> · <a href="#-code-health-the-layer-nobody-else-nails">Code Health</a> · <a href="#refactoring-intelligence">Refactoring</a> · <a href="#benchmarks">Benchmarks</a> · <a href="#supported-languages">Languages</a> · <a href="#quickstart">Quickstart</a> · <a href="#nine-mcp-tools">MCP tools</a> · <a href="#how-it-compares">Comparison</a> · <a href="#for-teams--enterprises">Hosted</a>}</p>

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<p align="center"> <strong>measure, locate, and fix what your AI ships</strong><br/> <strong>code health that predicts real bugs</strong> &nbsp;·&nbsp; <strong>ROC AUC 0.74 across 21 repos</strong> &nbsp;·&nbsp; <strong>2.3×</strong> CodeScene's defects under a fixed review budget<br/> <strong>graph-aware refactoring plans</strong> your agent can execute &nbsp;·&nbsp; <strong>up to −96% context tokens</strong> &nbsp;·&nbsp; <strong>−70% agent tool calls</strong> at answer-quality parity </p>

<p align="center">_{Measured, reproducible, on public codebases. <a href="#benchmarks">See the benchmarks ↓</a>}</p>

<img src=".github/assets/demo.gif" alt="repowise demo: Claude Code querying the codebase through repowise's MCP tools, then a tour of the local dashboard" width="100%" />

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AI now writes a large and growing share of the code, and the humans accountable for it have to trust what ships. A score that says "this file is risky" isn't enough: you need to know where the risk concentrates and how to fix it.

repowise closes that loop. It indexes your codebase once and scores every file for defect risk, maintainability, and performance from 25 deterministic markers, calibrated against a real defect corpus, no LLM, in under 30 seconds (the proof ↓). The same index then locates the risk through a real dependency graph and git history, and generates the fix: concrete, graph-aware refactoring plans (split this god class, move this method, break this dependency cycle, dedup this clone) that your coding agent can execute.

And because it is all one index, your agent gets the rest for free: five intelligence layers: dependency graph, git history, auto-generated docs, architectural decisions, and code health, exposed to Claude Code, Codex, and any MCP-compatible agent through nine task-shaped tools. Your agent answers "why does auth work this way?" instead of "here is what auth.ts contains", with fewer tool calls, fewer file reads, and lower cost per query, at comparable answer quality (benchmarks ↓). One index: context your agent can use, signals your team can trust, and the fix it can apply.

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