Local Code Indexing for Cursor MCP Server

@LuotoCompany

Basic information

About Local Code Indexing for Cursor MCP Server

ChromaDB-powered local indexing support for Cursor, exposed as an MCP server

Local Code Indexing for Cursor MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "workspace-code-search": {
      "type": "http",
      "url": "http://localhost:8978/sse"
    }
  }
}

Local Code Indexing for Cursor MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

Fetch the live tool list directly from this server's endpoint using the button above.

Overview

What is Local Code Indexing for Cursor?

An experimental Python-based server that locally indexes codebases using ChromaDB and provides a semantic search tool via an MCP (Model Context Protocol) server for tools like Cursor.

How to use Local Code Indexing for Cursor?

Clone the repository, create a .env file with PROJECTS_ROOT and FOLDERS_TO_INDEX, then start the server with docker-compose up -d. Configure Cursor by adding the server URL http://localhost:8978/sse to ~/.cursor/mcp.json. Optionally create a .cursorrules file to prompt the Cursor Agent to use the @search_code tool.

Key features of Local Code Indexing for Cursor

Fully local code indexing using ChromaDB
Semantic code search via MCP for Cursor
Configurable project root and folders to index
Docker-based deployment for easy setup
SSE transport on port 8978

Use cases of Local Code Indexing for Cursor

Enable Cursor Agent to semantically search your codebase instead of relying on grep
Quickly find relevant code across multiple projects without leaving the IDE
Offline, privacy-preserving code search that never sends code to external servers

Frequently asked questions

What is Local Code Indexing for Cursor?

It is an experimental Python server that indexes your local projects using ChromaDB and exposes a semantic search tool via MCP for use in Cursor.

How do I configure which folders are indexed?

Set `PROJECTS_ROOT` and `FOLDERS_TO_INDEX` in your `.env` file before starting the server.

Does it require Docker?

Yes, the recommended way to run the server is using Docker Compose (`docker-compose up -d`).

How do I connect it to Cursor?

Edit `~/.cursor/mcp.json` to include the server URL `http://localhost:8978/sse` under `mcpServers.workspace-code-search`, then restart Cursor.

Where does the indexed data live?

The README does not specify the storage location, but since it uses ChromaDB and runs locally, data is stored on your machine.

Comments

More Developer Tools MCP servers

Moxie Docs

Jackalope-Dev

Automated codebase documentation for GitHub: searchable docs, MCP context for AI agents, doc drift detection, and Friday Cleanup PRs.

Vibgrate MCP

Vibgrate

Query your team's drift, vulnerability, and migration data from any AI assistant. Vibgrate MCP connects Cursor, Claude, ChatGPT, Windsurf, or VS Code to Vibgrate Cloud: 51 tools for DriftScores, CVEs and EOL runtimes, up

offprompt

MCP server that lets Claude Code, Cursor or Codex ask you for API keys on a local page and write them to .env. The agent only ever sees key names.

LastPing

Know when your AI agents, cron jobs and CI pipelines fail, stall or go quiet. Your agent sets up monitors from a plain description, tells you what is broken and why, reads run history and traces, and writes notes on inci

Foremerge

naw103

Catch intent conflicts before code conflicts. The open-source coordination protocol for coding agents, built above Git.