GitHub
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
Descripción del creador (original en inglés)
Codebase intelligence for AI coding agents — graph, git history, docs, decisions, code health.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"repowise": {
"command": "uvx",
"args": [
"repowise",
"mcp",
"--transport",
"stdio"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add repowise -- uvx repowise mcp --transport stdioPégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"repowise": {
"command": "uvx",
"args": [
"repowise",
"mcp",
"--transport",
"stdio"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"repowise": {
"type": "stdio",
"command": "uvx",
"args": [
"repowise",
"mcp",
"--transport",
"stdio"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 6 nov 2026
El nombre en el registro se verificó con el dominio repowise.dev (el registro comprueba quién es dueño del dominio)
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (0.60.1) llegó al registro hace 4 días.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Python (uv) en tu computadora.
En la misma categoría: GitHub, Desktop Commander, Cloudflare MCP
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
MCP server for terminal commands, file operations, and process management
Cloudflare MCP servers
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
English | 简体中文
Stop paying your agent to re-read your codebase.
Repowise indexes your code, git history, tests and decisions once, on your machine.
Your coding agent asks the index instead of grepping and opening files, so it does about half the work.
You get the same answers in a dashboard: what calls this, what breaks, what to fix first, and why.
Half the tool calls your agent opens 3 files where it opened 7 · 31.6% less output Up to 99% less noise from test runs, installs and git output · every error line kept 88% of the right files found in one call · next best tool: 61%
Graph, risk, health, tests and dead code make zero LLM calls · no API key to index · 28 languages · Claude Code, Codex, Cursor and any MCP host · free and open source
Quickstart · For your agent · What it does · Hosted · Benchmarks · Teams · Docs
Open Claude Code, Codex, Cursor or any MCP-capable agent in your repository and paste:
Read https://docs.repowise.dev/setup.md and set up Repowise in this repository.
The agent installs Repowise, indexes the repo with no API key, connects itself to the index, and asks you before anything costs money. To do it by hand:
uv tool install repowise # or: pipx install repowise / pip install repowise
cd /path/to/your/repo repowise init --yes --no-prose # graph, git, health, dead code, docs. No key, no spend.
repowise serve # dashboard + MCP server (needs Node 20+; first run downloads the UI)
serve opens the dashboard in your browser. After a first index it starts with a short guided tour, and Setup is where you connect agents, turn on sync and add coverage or a model.
Restart Claude Code or run /mcp, then ask *"What breaks if I change src/auth.py?"* or *"Use Repowise get_overview to summarize this repository."* init wires Claude Code for this repo and adds the global repowise MCP entry when there is none; it never moves one that serves another repo. Full setup for every agent →
Without an index, an agent rediscovers your codebase on every task: grep, open a file, open three more, grep again. Repowise answers those questions ahead of time, so the agent asks once and gets on with the work.
In a measured run on django/django, an agent with Repowise made 3.8 tool calls instead of 7.2, opened 3.0 files instead of 7.2 and wrote 31.6% less, with answers just as good. That is the largest saving of the five context tools we tested. On a small local model the output cut reaches 47.9%. How it was measured →
repowise distill trims test, install and git output before the agent reads it and keeps every error line. Distill →CLAUDE.md and AGENTS.md current from the index.repowise saved and the dashboard's Usage and savings page count the tokens your agent no longer has to read.One index of your code, its history and its decisions, used three ways: to understand the code, to change it safely, and to keep improving it.
See how it fits together A call graph across 28 languages, an architecture map you can explore, C4 views, and a generated wiki for every module and file.
The graph · Docs
Know what breaks Every caller of what you changed, the files that usually change with it but are missing from your diff, and the tests that reach it.
Change risk · Tests
Fix what matters A 1 to 10 health score for every file, validated against real bug history, a ranked fix-first queue, refactoring plans and dead code.
Code health · Refactoring
Follow it across repos Services and the HTTP, gRPC and event contracts between them, with a guard for breaking changes and the consumer files they affect.
Workspaces
Ask it anything Cited answers and charts from the dashboard, or the same answers through MCP for your agent.
Dashboard · MCP tools
Remember why Decisions mined from ADRs, comments, commits, PRs and agent sessions, each tied to the code it governs, plus docs checked against the code.
Decisions · Doc drift
Every question it answers
| You ask | Repowise gives you |
|---|---|
| *How does checkout work in this repo?* | A cited answer built from the call graph and the generated docs, in one call. Search and answers |
| *What calls this function, and what does it call?* | A call graph across 28 parsed languages, every edge stamped with how it was resolved and how far to trust it, plus traced execution flows from each entry point. The graph |
| *Can I get docs for this codebase?* | A wiki for every module and file, rendered from the code's structure with no key, or written by a model when you choose. It updates incrementally after each commit. Docs |
| *Which of our docs are wrong?* | Markdown checked against the tree: every reference to a file or symbol the code no longer has, with the line to edit. Doc drift |
| *Why is it built this way?* | Decisions mined from ADRs, # WHY: comments, commit and PR history and your agent sessions, each tied to the code it governs and flagged when it goes stale. Decisions |
| *Who knows this code?* | Owners, bus factor, fading ownership when the main author goes quiet, and suggested reviewers. Ownership |
| *Can I see the architecture?* | An explorable dependency map, C4 views, and a Structurizr export, no model involved. Dashboard |
| You ask | Repowise gives you |
|---|---|
| *What breaks if I change this?* | Symbol-level blast radius: the callers of what you changed, the files that historically change with it but are missing from your diff, and the tests that reach it. Change risk |
| *How risky is this PR?* | Where the change ranks against your repository's own recent commits, with the reasons, as a directive your agent can act on. Change risk |
| *Which tests should run?* | The tests a diff actually exercises, from a coverage report if you have one and from the call graph if you do not. Test intelligence |
| *Did this PR add untested lines?* | Patch coverage, branch coverage on changed lines and path-scoped gates in CI, on GitHub, GitLab or any runner. CI gates |
| *Will this API change break another r
Solo se muestra el principio; lee el resto en el repo