Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@codeweave show me the file tree of src/"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Make any repo instantly AI-ready via MCP — a self-hosted, zero-API-key context server for your codebase.
codeweave runs locally alongside your AI coding tool. It indexes your entire repo into a fast SQLite database and exposes it as an MCP server, giving AI assistants deep, accurate context about your code — file tree, full-text search, git history, dependencies, stack detection, and coding conventions — without ever sending your code to a third party.
# 1. Install globally (or use npx)
npm install -g codeweave
# 2. Generate a config in your project root
cd /path/to/your/project
codeweave init
# 3. Start the MCP server
codeweave startThen add codeweave to your AI client (see AI Client Setup below).
Related MCP server: MCP Codebase Context Server
Feature | Description |
File tree | Annotated JSON tree with language tags for every file |
Full-text search | SQLite FTS5 with porter stemming — sub-millisecond queries |
File content | Line-numbered file content with optional line range slicing |
Git history | Recent commits with author, date, and changed files |
Dependency graph | Parsed from |
Stack detection | Automatically detects language, framework, database, test runner, styling |
Convention detection | File naming style, import patterns, component structure |
File watcher | Re-indexes changed files in < 1s with 300ms debounce |
Incremental indexing | mtime-based cache — warm starts in < 30ms |
Zero API keys | Runs entirely locally. No cloud. No telemetry. |
codeweave uses the stdio MCP transport and works with any MCP-compatible client.
Add to .claude/settings.json in your project root:
{
"mcpServers": {
"codeweave": {
"command": "npx",
"args": ["codeweave"],
"cwd": "."
}
}
}Add to .cursor/mcp.json in your project root:
{
"mcpServers": {
"codeweave": {
"command": "npx",
"args": ["codeweave"],
"cwd": "${workspaceFolder}"
}
}
}Add to ~/.config/zed/settings.json:
{
"context_servers": {
"codeweave": {
"command": {
"path": "npx",
"args": ["codeweave"]
}
}
}
}Add to .continue/config.json:
{
"mcpServers": [
{
"name": "codeweave",
"command": "npx",
"args": ["codeweave"]
}
]
}codeweave [command] [options]
Commands:
start Start the MCP server (default)
init Generate codeweave.config.js in the current directory
status Show indexing stats for the current repo
Options:
--verbose Enable debug logging
-V, --version Show version number
-h, --help Show helpSee the full CLI reference →
Run codeweave init to generate a codeweave.config.js. All fields are optional — defaults work well for most projects.
// codeweave.config.js
export default {
// Directories to index (relative to config file)
include: ['src'],
// Extra patterns to exclude beyond .gitignore
exclude: ['**/*.generated.ts'],
// Files larger than this are truncated (KB)
maxFileSizeKB: 100,
// How many git commits to read
gitDepth: 50,
// Port for future HTTP transport
port: 3333,
// Enable verbose/debug logging
verbose: false,
};See the full configuration reference →
codeweave exposes 7 MCP tools that AI assistants can call:
Tool | Description |
| Annotated file tree, filterable by language |
| File content with line numbers and optional line range |
| Full-text search with snippet context |
| Detected naming style, import patterns, test framework |
| All dependencies from parsed manifest files |
| Recent commits, filterable by file path |
| Detected language, framework, database, tooling |
See the full API reference →
your repo on disk
│
▼
┌─────────────────────────────────────────────────────┐
│ codeweave process │
│ │
│ ┌──────────┐ ┌──────────┐ ┌───────────────────┐ │
│ │ File │ │ Git │ │ Manifest Parser │ │
│ │ Scanner │ │ Reader │ │ (9 formats) │ │
│ └────┬─────┘ └────┬─────┘ └────────┬──────────┘ │
│ │ │ │ │
│ └──────────────┴─────────────────┘ │
│ │ │
│ ┌────────▼────────┐ │
│ │ SQLite DB │ │
│ │ (WAL + FTS5) │◄──────────────────┤
│ └────────┬────────┘ File Watcher │
│ │ │
│ ┌───────────────┼───────────────┐ │
│ ▼ ▼ ▼ │
│ get_file_tree search_codebase get_stack_info │
│ get_file get_conventions get_dependencies │
│ get_git_history │
│ │ │
│ └──────────────────────────────────────────┐ │
│ MCP Server (stdio) │ │
└───────────────────────────────────────────────────┘
│
┌─────────┘
▼
AI client (Claude Code, Cursor, Zed…)Key design decisions:
SQLite over in-memory — the full file content lives on disk, not in the Node.js heap. Memory usage stays flat regardless of repo size.
FTS5 porter tokenizer — full-text search that handles stemming (authenticate → authenticat) without any external dependencies.
mtime cache — unchanged files are never re-read. Warm starts on a 1K-file repo take ~28ms.
Stdio transport — no port conflicts, no firewall rules. Works in any environment where the AI client can spawn a subprocess.
codeweave detects and parses:
Languages: TypeScript, JavaScript, Python, Go, Rust, Dart, Ruby, PHP, Java, Kotlin, Swift, and more
Frameworks: Next.js, Nuxt, Remix, SvelteKit, Astro, Vite+React, Express, Fastify, NestJS, Hono, Django, Flask, FastAPI, Rails, Laravel, Symfony, Angular, Vue, Svelte
Databases: Prisma, TypeORM, Drizzle, MongoDB, PostgreSQL, MySQL, SQLite, Redis, Sequelize
Manifest formats: package.json, pubspec.yaml, Cargo.toml, go.mod, requirements.txt, pyproject.toml, composer.json, Gemfile, build.gradle
Contributions are welcome! Please read CONTRIBUTING.md for guidelines on how to fork, develop, test, and submit PRs.
git clone https://github.com/MdAbdullahAlMahmud/codeweave.git
cd codeweave
npm install
npm test # run tests
npm run typecheck # type check
npm run lint # lintMIT © Abdullah — see LICENSE for details.
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