GitHub
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
Descripción del creador (original en inglés)
A local map of your codebase over time: symbols, callers, subgraphs and structural change.
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.
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Descargar el archivo .mcpb del creador
El enlace lleva al archivo del propio creador; no lo alojamos ni lo reempaquetamos. Abre el archivo y Claude Desktop lo instalará.
Ejecuta esto en tu terminal
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.
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.
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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 7 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub RedholeTechnologies, dueña del repo
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 (0.7.1) llegó al registro hace 40 días.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas MCPB 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 | 한국어
Treering draws a map of your codebase and keeps a copy of it for every commit, so you can see how the structure changed: which types started depending on each other last week, or when a class began to collect callers. It runs entirely on your machine and sends nothing over the network. It doesn't use an LLM, so the same code always produces the same graph.
*Click a box to go inside it; the part you opened frames what it holds. Then back out, and the same sheet as a chip.*
*The sample project's modules as a schematic, compared with a month earlier. Green is new: a Billing module now implements the payment interface. Red dashed is gone: the web pages used to call the database directly.*
| Map. Modules as bubbles and the calls between them. New lines are green, broken ones red. | Blueprint. One level as boxes in tiers, each with its role and what the others use it for. |
| Inside a module. The module you opened frames what it holds; wires cross its edge at sheet ports. | One class. Its fields and methods, the types it works with, and which member ties them. |
| Chip. Where the weight is: each region as big as its code, libraries as pads on the edge. |
All of these are the sample project that comes with Treering (treering sample), a small made-up shop.
Treering is still in development, and the database format may change between releases. The design notes are in treering-plan.md (in Korean).
Windows (PowerShell):
irm https://raw.githubusercontent.com/RedholeTechnologies/Treering/main/install.ps1 | iex
Linux (x86-64):
curl -fsSL https://raw.githubusercontent.com/RedholeTechnologies/Treering/main/install.sh | sh
Each script downloads the latest build from Releases, checks it against the published checksum, and puts treering on your PATH. On Windows it also adds Treering to the Start menu. Neither needs administrator rights, and running a script again updates Treering. If you'd rather not run a script, download the zip or tarball from Releases and unpack it anywhere.
Then run treering, or open it from the Start menu. It starts the server and opens http://127.0.0.1:7377 in your browser. If Treering is already running, it only opens the browser.
To look around before importing anything, choose Or look around a sample project first on the first screen. It adds acme-shop, a small made-up online shop with a month of history. treering sample adds it from the command line.
Treering doesn't parse source code itself. It reads SCIP indexes, which each language's indexer produces. Install the indexers for the languages you use:
dotnet tool install --global scip-dotnet # C#
npm install -g @sourcegraph/scip-typescript # TypeScript and JavaScript npm install -g @sourcegraph/scip-python # Python
treering import /path/to/repo
treering serve
import looks at which languages the repository contains and runs each indexer with the flags it needs. For C# it indexes the solution at the root, or each project if there's no solution. For TypeScript it indexes each topmost package.json, and for Python each pyproject.toml. The graph is stored in your user folder, never inside the repository, and treering projects lists what you've imported.
treering serve opens the map at http://127.0.0.1:7377. Without a database argument it serves every imported project, and you can switch between them in the menu at the top of the page.
You can also import from the page. Open the project menu, choose Import…, then Choose a folder…. The server opens your system's folder picker (Explorer on Windows, the standard dialog on macOS, zenity or kdialog on Linux), because a browser won't give a page the full path of a folder. You can type the path instead. The import starts when you pick a folder, and the dialog shows each indexer as it runs. If one fails, it tells you why and what to try.
The import and folder endpoints only accept JSON requests sent by the page itself, so another site open in your browser can't start an import or open a window.
The map shows modules, namespaces and types as nodes, and the references between them as edges.
/ or Ctrl+K to search. Picking a result takes you to where it lives.treering update /path/to/repo
treering watch /path/to/repo # every 10 minutes treering watch /path/to/repo 30 # every 30 minutes
update re-indexes only the projects whose files changed. Each changed file goes to its nearest project (.csproj, package.json, or pyproject.toml and setup.py) and that language's indexer, so a repository with several languages updates each part with its own tool. If an indexer is missing, Treering prints the command that installs it.
watch runs update on a timer and adds a snapshot only when something changed, so the history fills in while you work. It starts from the commit recorded in the last snapshot, so you can stop and restart it without losing anything, and it counts uncommitted changes as well as commits.
You usually don't need to run watch yourself: treering serve does the same for every imported project while it runs. Every 10 minutes it re-indexes what changed and adds a snapshot, and if you're looking at the latest snapshot the page moves to the new one by itself. A re-index that leaves the graph as it was adds no snapshot. Turn it off with --no-watch or under Settings on the page, change the period with --watch-minutes N, and pick another port with --port N.
You can run an indexer yourself and load its output. For C#:
scip-dotnet index YourSolution.slnx --allow-global-symbol-definitions --output index.scip
treering load index.scip graph.db treering serve graph.db treering callers graph.db OrderRepository treering map graph.db type --own
Always pass --allow-global-symbol-definitions to scip-dotnet. Without it, symbols don't carry their package name, and once you index projects separately or add snapshots, one symbol turns into several. In one test that recorded 6,784 symbols as added and 6,790 as removed.
To compare over time, load more snapshots:
treering snap index-new.scip graph.db 1
treering diff graph.db 0 1 treering growth graph.db InvoiceModel
diff lists the dependencies added and removed between two snapshots, and growth shows when a type's callers increased.
treering mcp
This runs a Model Context Protocol (MCP) server over stdio for the projects you've imported. It has six tools: list_projects, find_symbol, callers_of, subgraph, changed_since and snapshots. Each tool takes a project (a name or id from list_projects); left empty, it asks the most recently imported one. They run the same queries as the page, with the same size limits. When a result would be too large, the response says what was left out so the agent can narrow the question and ask again. treering mcp graph.db answers about that one database only.
To add it to Claude Code:
claude mcp add treering -- treering mcp
In other hosts, the command is treering with the argument mcp. Each release also carries MCP bundles (treering-win-x64.mcpb, treering-linux-x64.mcpb) for hosts that install MCPB in one step, and is published to the MCP Registry as io.github.RedholeTechnologies/treering.
On Acme.Shop (4 projects, 632 .cs files):
| Step | Result |
|---|---|
| Indexing (scip-dotnet) | 89s |
| Loading into the graph | 2.6s, 53 MB peak memory |
| Database size | 5.9 MB, from an 8.2 MB index.scip |
| Cost of a second snapshot | 27% more (5.9 MB to 7.5 MB) |
| Whole-map query | 29 ms by module, 30 ms by namespace, 48 ms for every type |
| Drill-down query | 182 ms (384 types, 2,933 edges) |
| Incremental update | 17s, of which 16.6s is indexing |
On a large C# repository (11,385 .cs files):
| Step | Result |
|---|---|
| Indexing | 3 min 28s, 34.5 MB index |
| Symbols and edges | 43,932 and 185,266 |
| Memory while scanning | 41.6 MB, the same as for the 8.2 MB index |
| Loading | 11 to 15s, 103 MB, 40.3 MB database |
| Whole-map query | 26 ms for 115 modules, 48 ms for 406 namespaces, 210 ms for every type (capped at 2,000) |
Scanning memory doesn't grow with the size of the index, and every whole-map view stays under 300 ms at this size. That's because edges are summarised per module, namespace and type once, when the index is loaded, instead of on every query. The module map went from 327 ms to 26 ms with that change.
C#, TypeScript and Python work end to end. Because the input is SCIP, adding a language mostly means adding its indexer: TypeScript needed no changes to Treering, and the module level became npm packages and namespaces became folders on their own. Constructor injection is recognised from .ctor, , __init__ and . update and watch handle TypeScript too; on ShopWeb, 19 changed files in one package took 52s.
scip-python 0.6.6 doesn't start on Windows: it builds a regular expression from the path separator, and \ isn't a valid pattern on its own. Treering loads a small script ahead of scip-python that escapes that one pattern. It also finds pip for scip-python, looking in the repository's .venv first and then at any Python the py launcher knows. If there's no pip, it indexes with an empty package list, which only loses the names of third-party packages. On python-sample this produced 1,800 symbols and 6,564
Solo se muestra el principio; lee el resto en el repo