Sunstone Weave: Local Semantic Code Search

io.github.space-baconPublished by GitHub account space-baconv0.1.2Updated Oct 24, 2026

Semantic search over local folders of code and docs, with a code-search encoder running on your CPU.

VerifiedSTDIODesktop onlyKnowledge & MemoryDeveloper Tools

Overview

AI-generated overview

A local MCP server that semantically indexes folders of code and docs on your CPU, letting an assistant find relevant passages by plain-language or code queries

What you can do
Index a folder, or refresh its index incrementally, and run several weaves in the background when they take long. Search woven folders for the passages nearest a plain-language or code query, returning file paths, line ranges and scores. List woven folders with file and passage counts and any weave still running. Delete a folder's index without touching its files.
When to use it
Useful when you want an assistant to locate code or documentation across local repositories by meaning rather than exact text, for example answering where a particular value is parsed. Suited to offline or privacy-conscious work since search runs locally on the CPU.
Requirements
Runs as a local stdio process via npx with Node 20 or later on macOS, Linux or Windows; install once from a terminal before adding it to a client. Pass one or more --folder paths, or let the model call weave_folder. The first run downloads about 134 MB of encoder files from huggingface.co into a cache directory, configurable with BLACKWINDOW_WEAVE_CACHE or --cache. On Linux x64 the install may also fetch CUDA libraries that are not used.
Before you install
The first install can exceed a client's startup timeout and leave a broken copy in npm's cache, so install from a terminal first and pin the version. weave_folder writes index data into the cache directory, and weave_forget deletes a folder's index, though not its files. The first run contacts huggingface.co; later runs make no network requests. Indexes are stored on disk under the cache path.

Installation

In SourceWeft

  1. Open Sunstone Weave: Local Semantic Code Search in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

blackwindow-weave-mcp

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

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:

sh
npx -y [email protected] --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:

sh
ONNXRUNTIME_NODE_INSTALL=skip npx -y [email protected] --version

Add it to a client

macOS and Linux

Claude Code:

sh
claude mcp add weave -- npx -y [email protected] --folder /path/to/your/repo

VS Code, in .vscode/mcp.json:

json
{  "servers": {    "weave": { "type": "stdio", "command": "npx", "args": ["-y", "[email protected]", "--folder", "${workspaceFolder}"] }  }}

Cursor, Claude Desktop, Windsurf and most other clients:

json
{  "mcpServers": {    "weave": { "command": "npx", "args": ["-y", "[email protected]", "--folder", "/path/to/your/repo"] }  }}

Windows

On Windows npx is a batch file, which a client can only start through cmd /c. Claude Code:

sh
claude mcp add weave -- cmd /c npx -y [email protected] --folder C:\path\to\your\repo

Cursor, Claude Desktop, Windsurf and most other clients:

json
{  "mcpServers": {    "weave": { "command": "cmd", "args": ["/c", "npx", "-y", "[email protected]", "--folder", "C:/path/to/your/repo"] }  }}

In VS Code the same command and args go under servers in .vscode/mcp.json, with "type": "stdio".

Installed globally

npm install -g [email protected] 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 [email protected] in the arguments with github:space-bacon/blackwindow-weave-mcp.

optionmeaning
--folder <path>Weave this folder when the server starts. Repeatable. Optional: the model can call weave_folder itself.
--cache <dir>Where the encoder and the indexes live. Default ~/.cache/blackwindow-weave (on Windows %USERPROFILE%\.cache\blackwindow-weave), or BLACKWINDOW_WEAVE_CACHE.
--versionPrint the version and exit.

Platforms

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.

Troubleshooting

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:

  • macOS and Linux: rm -rf ~/.npm/_npx
  • Windows (PowerShell): Remove-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.

Tools

toolwhat it does
weave_folderIndex 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_searchThe 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_listThe woven folders with their file and passage counts, and any weave still running.
weave_forgetDelete a folder's index. The folder's files are not touched.

Measured

On an Apple M2 Ultra (24 CPU cores, Node 24.4.1), through the MCP SDK's own stdio client, in test/smoke.mjs:

folderfilespassagesfirst weavesecond weavesearch
this package's src/6423.8 s, with the encoder's download0.013 s5 to 6 ms
the Sunstone repository571,36720.2 s0.014 s6 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.

How it works

  • Files. A git work tree is listed by git, so .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.
  • Passages. Code is cut at definitions into passages of about 700 characters, each labelled with the nearest definition. Prose is cut at paragraphs and sentences into passages of about 420 characters. The chunkers are Black Window's.
  • Encoder. onnx/model.onnx (fp32) through transformers.js and ONNX Runtime on the CPU, CLS pooling.
  • Centring. Every vector has the model's shipped mean (centring/mean_shipped.json) subtracted and is brought back to unit length, so a score is a cosine after centring.
  • Search. Exact: every passage is scored. Before answering, a folder not checked in the last 30 s is brought up to date if fewer than 200 of its files changed; otherwise the answer says the index is stale.
  • Index. One per folder under <cache>/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.

Licence

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 [email protected].

Source: README.md at commit 4acc79d

Tools

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

3
  1. v0.1.2LatestOct 1, 2026
  2. v0.1.1Sep 30, 2026
  3. v0.1.0Sep 30, 2026

Score

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