Context7
Up-to-date docs for AI agents
Descripción del creador (original en inglés)
Semantic search over local folders of code and docs, with a code-search encoder running on your CPU.
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.
BLACKWINDOW_WEAVE_CACHENecesitas
¿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": {
"blackwindow-weave": {
"command": "npx",
"args": [
"-y",
"blackwindow-weave-mcp"
],
"env": {
"BLACKWINDOW_WEAVE_CACHE": "your-value"
}
}
}
}Ejecuta esto en tu terminal
claude mcp add blackwindow-weave --env BLACKWINDOW_WEAVE_CACHE=your-value -- npx -y blackwindow-weave-mcpCompleta los valores vacíos antes de ejecutarlo.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"blackwindow-weave": {
"command": "npx",
"args": [
"-y",
"blackwindow-weave-mcp"
],
"env": {
"BLACKWINDOW_WEAVE_CACHE": "your-value"
}
}
}
}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": {
"blackwindow-weave": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"blackwindow-weave-mcp"
],
"env": {
"BLACKWINDOW_WEAVE_CACHE": "your-value"
}
}
}
}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.
BLACKWINDOW_WEAVE_CACHE envEsta 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 space-bacon, 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 (0.1.2) llegó al registro hace 38 días.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Node.js en tu computadora.
En la misma categoría: Context7, Codebase Memory, Exa
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
Up-to-date docs for AI agents
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Connect AI agents to Exa for web search, content fetching, and multi-step research.
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.
Semantic search over the folders on your machine, for any MCP client. The server cuts source code and documentation into passages, embeds them with Motherlode, a 33M-parameter code-search encoder, on your CPU, and answers questions such as "where is a pairing line parsed into url, key and name" with file paths, line ranges and the passages themselves.
The only network requests are to huggingface.co on the first run: six requests, which leave five files, 133,752,819 bytes, in the cache. With the files cached, a run makes none.
This is the weave from Black Window and the Sunstone VS Code extension, packaged for clients that speak the Model Context Protocol. It runs on macOS, Linux and Windows with Node 20 or later.
Install it once from a terminal, before adding it to a client. This installs the package and ONNX Runtime and prints the version once the runtime has loaded:
npx -y blackwindow-weave-mcp@0.1.2 --version
On GitHub's hosted runners, from an empty npm cache, this first install took 7 to 13 s on Linux and macOS and 55 to 69 s on Windows. Clients wait a limited time for a server to start (the MCP SDK's default is 60 s), and a client that stops waiting in the middle of an install can leave a broken copy in npm's cache (see Troubleshooting). Once installed, the server starts in under 3 s.
Keep the version in the client's configuration the same as here. With a version given, npx starts the copy it installed; with the bare name, npx (npm 11) looks for a newer version on every start and installs it while the client waits.
On Linux x64, ONNX Runtime also downloads 236 MB of CUDA libraries during the install. This server runs on the CPU and never loads them, so you can skip them:
ONNXRUNTIME_NODE_INSTALL=skip npx -y blackwindow-weave-mcp@0.1.2 --version
Claude Code:
claude mcp add weave -- npx -y blackwindow-weave-mcp@0.1.2 --folder /path/to/your/repo
VS Code, in .vscode/mcp.json:
{
"servers": { "weave": { "type": "stdio", "command": "npx", "args": ["-y", "blackwindow-weave-mcp@0.1.2", "--folder", "${workspaceFolder}"] } } }
Cursor, Claude Desktop, Windsurf and most other clients:
{
"mcpServers": { "weave": { "command": "npx", "args": ["-y", "blackwindow-weave-mcp@0.1.2", "--folder", "/path/to/your/repo"] } } }
On Windows npx is a batch file, which a client can only start through cmd /c. Claude Code:
claude mcp add weave -- cmd /c npx -y blackwindow-weave-mcp@0.1.2 --folder C:\path\to\your\repo
Cursor, Claude Desktop, Windsurf and most other clients:
{
"mcpServers": { "weave": { "command": "cmd", "args": ["/c", "npx", "-y", "blackwindow-weave-mcp@0.1.2", "--folder", "C:/path/to/your/repo"] } } }
In VS Code the same command and args go under servers in .vscode/mcp.json, with "type": "stdio".
npm install -g blackwindow-weave-mcp@0.1.2 installs a blackwindow-weave-mcp command, which a client can start directly (cmd /c blackwindow-weave-mcp on Windows). To run from this repository instead of npm, replace blackwindow-weave-mcp@0.1.2 in the arguments with github:space-bacon/blackwindow-weave-mcp.
| option | meaning |
|---|---|
--folder | Weave this folder when the server starts. Repeatable. Optional: the model can call weave_folder itself. |
--cache | Where the encoder and the indexes live. Default ~/.cache/blackwindow-weave (on Windows %USERPROFILE%\.cache\blackwindow-weave), or BLACKWINDOW_WEAVE_CACHE. |
--version | Print the version and exit. |
Every push runs CI on Linux (x64 and arm64), Windows (x64) and macOS (Apple silicon), each with Node 20, 22 and 24. Each job runs the stdio smoke test below from a checkout. It then installs the packed package through npx from an empty npm cache, starts it the way a client does and weaves a folder. On Windows it also starts it through cmd /c. Last, it installs the package globally and starts it by its command. Other platforms, such as Windows on Arm, Intel Macs and Alpine Linux, are not tested.
The client times out when it first starts the server, or the server stops with `Cannot find module ... transformers.node.mjs`. A first install was interrupted, usually by a client that stopped waiting, and npm kept the half-installed copy. Delete npm's npx cache and install again from a terminal with the line under Install:
rm -rf ~/.npm/_npxRemove-Item -Recurse -Force "$env:LOCALAPPDATA\npm-cache\_npx"Updating. Install the new version from a terminal as above, then change the version in the client's configuration.
| tool | what it does |
|---|---|
weave_folder | Index a folder, or bring its index up to date. Only files whose size or modification time changed are read again. A run longer than 25 s returns at once and continues in the background. |
weave_search | The passages nearest a plain-language or code query, with file, line range and score. Searches the folders woven in this session, or every woven folder if none was, or one folder when asked. |
weave_list | The woven folders with their file and passage counts, and any weave still running. |
weave_forget | Delete a folder's index. The folder's files are not touched. |
On an Apple M2 Ultra (24 CPU cores, Node 24.4.1), through the MCP SDK's own stdio client, in test/smoke.mjs:
| folder | files | passages | first weave | second weave | search |
|---|---|---|---|---|---|
this package's src/ | 6 | 42 | 3.8 s, with the encoder's download | 0.013 s | 5 to 6 ms |
| the Sunstone repository | 57 | 1,367 | 20.2 s | 0.014 s | 6 ms |
Embedding runs at about 68 passages a second on that machine, so a repository of 10,000 passages takes about two and a half minutes the first time. Those figures are one run each on one machine. The smoke test's three questions about this package's own source each return the expected file first; they are a check that the pieces are wired together, not a measure of retrieval quality. For retrieval quality see the model card.
.gitignore holds. Any other folder is walked, skipping node_modules, build output, virtual environments, lock files and minified files. Files over 1 MB and files that read as binary are skipped. JSON and XML are left out: in the Sunstone repository, result files under bench/results/ took ranks 2 and 3 of the question above when they were included.onnx/model.onnx (fp32) through transformers.js and ONNX Runtime on the CPU, CLS pooling.centring/mean_shipped.json) subtracted and is brought back to unit length, so a score is a cosine after centring. /index/: a Float32 matrix and a JSONL of passages, named by a manifest that is written to a temporary file and renamed into place, so an interrupted write leaves the previous index. An index that cannot be read is moved aside rather than overwritten.Business Source License 1.1 with an internal-use grant. You may use it for any internal purpose, including commercial development on your own or your employer's code, with no limit on seats. You may not offer it to others as a hosted search service or ship it inside a product you supply. On 15 September 2030 it becomes Apache-2.0. The encoder is downloaded under its own licence, which has the same shape. For other terms, write to burton@sunstonenorth.com.