Code Index

Name: Code Index
Author: achreftlili

by achreftliliversion 1.0.6i★ –iRuns on your computer

Registry nameio.github.achreftlili/code-index

Install

Overview

Description from the maker (original English)

SQLite-backed hybrid (vector + FTS) code search index for Claude Code over MCP.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Search & AI memory

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
You fill in yourself: CODE_INDEX_EMBEDDER, CODE_INDEX_EMBED_MODEL, CODE_INDEX_EMBED_DIM, CODE_INDEX_DB, CODE_INDEX_EMBED_BATCH, CODE_INDEX_EMBED_DEVICE

You need

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "code-index": {
      "command": "uvx",
      "args": [
        "mcp-code-index"
      ],
      "env": {
        "CODE_INDEX_EMBEDDER": "your-value",
        "CODE_INDEX_EMBED_MODEL": "your-value",
        "CODE_INDEX_EMBED_DIM": "your-value",
        "CODE_INDEX_DB": "your-value",
        "CODE_INDEX_EMBED_BATCH": "your-value",
        "CODE_INDEX_EMBED_DEVICE": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add code-index --env CODE_INDEX_EMBEDDER=your-value --env CODE_INDEX_EMBED_MODEL=your-value --env CODE_INDEX_EMBED_DIM=your-value --env CODE_INDEX_DB=your-value --env CODE_INDEX_EMBED_BATCH=your-value --env CODE_INDEX_EMBED_DEVICE=your-value -- uvx mcp-code-index

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "code-index": {
      "command": "uvx",
      "args": [
        "mcp-code-index"
      ],
      "env": {
        "CODE_INDEX_EMBEDDER": "your-value",
        "CODE_INDEX_EMBED_MODEL": "your-value",
        "CODE_INDEX_EMBED_DIM": "your-value",
        "CODE_INDEX_DB": "your-value",
        "CODE_INDEX_EMBED_BATCH": "your-value",
        "CODE_INDEX_EMBED_DEVICE": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "code-index": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "mcp-code-index"
      ],
      "env": {
        "CODE_INDEX_EMBEDDER": "your-value",
        "CODE_INDEX_EMBED_MODEL": "your-value",
        "CODE_INDEX_EMBED_DIM": "your-value",
        "CODE_INDEX_DB": "your-value",
        "CODE_INDEX_EMBED_BATCH": "your-value",
        "CODE_INDEX_EMBED_DEVICE": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

CODE_INDEX_EMBEDDER env
Embedder backend. Only 'jina' (local jina-embeddings-v2-base-code via sentence-transformers) is supported; the variable exists for future expansion.
CODE_INDEX_EMBED_MODEL env
HuggingFace model id. Defaults to 'jinaai/jina-embeddings-v2-base-code'. Override only if you know the model is dim-compatible.
CODE_INDEX_EMBED_DIM env
Embedding dimension. Defaults to 768 (matches jina-embeddings-v2-base-code). Must match the model's output dim.
CODE_INDEX_DB env
Path to the SQLite index database. Defaults to .claude/index.db relative to the working directory.
CODE_INDEX_EMBED_BATCH env
Encode batch size (default 32). Lower (e.g. 8 or 4) to reduce peak memory if the GPU OOMs on large files.
CODE_INDEX_EMBED_DEVICE env
Torch device override: 'cpu', 'mps', or 'cuda'. Unset = auto-detect. Set 'cpu' to avoid Apple-Silicon MPS out-of-memory errors.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account achreftlili, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

More stars than 0% of the other 7249 servers in this category
Published to the registry more recently than 12% of the other 7249 servers in this category
Basic checks equal to or better than 100% of the other 7249 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Code Index safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.0.6) reached the registry 6 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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Codebase Memory

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Exa

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Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated last month

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

code-index

A local, SQLite-backed code index for Claude Code, exposed over MCP. It replaces blind Read / Grep / Glob exploration with targeted retrieval — "where is parseAuthToken defined", "what calls Indexer.reindex_all", "find the rate-limiting code" — answered in milliseconds against an offline index.

No API keys. No external services. The embedder runs locally on your machine.

How it works (30-second tour)

Parse your repo with tree-sitter (Python, TypeScript/JavaScript, Go, Rust).
Chunk code per symbol and expand identifiers (getUserAuthToken → get user auth token) so search matches both styles.
Embed each chunk locally with jina-embeddings-v2-base-code (768-dim) via sentence-transformers.
Store symbols, chunks, vectors, and call/import edges in .claude/index.db (SQLite + sqlite-vec + FTS5).
Serve 14 retrieval tools + 1 admin tool over MCP (see Tools).
Stay fresh via an optional PostToolUse hook that incrementally re-indexes touched files.

Tools

Retrieval

Tool	Purpose
`code_search`	Hybrid (vector + FTS) search for conceptual queries (e.g., "auth flow", "where do we parse JSON").
`symbol_lookup`	Exact-name lookup of functions / classes / methods / types. Prefer over `code_search` for identifiers.
`file_outline`	Symbols (with signatures) in a file, in source order. Use instead of `Read` when you only need shape.
`module_outline`	Symbols across a directory subtree in one call. Use instead of looping `file_outline`.
`where_am_i`	Given `path` + `line`, returns the innermost symbol and the full enclosing chain.
`get_symbol_body`	Full chunk for a `symbol_id` from `symbol_lookup` / `code_search` / `file_outline`.
`get_symbol_bodies`	Batch version of `get_symbol_body` (up to 20 ids per call).
`callers`	Symbols that CALL the given symbol. `depth` (1-5) expands transitively.
`callees`	Symbols that the given symbol CALLS. `depth` (1-5) expands transitively.
`references`	Non-call uses (subclasses, free identifier references). Companion to `callers` / `callees`.
`trace`	Build a call-graph tree from an entry symbol; `flat=true` returns nodes/edges for cheap LLM scans.
`file_imports`	Files this file imports (`direction=imports`) or that import it (`direction=imported_by`).
`recent_changes`	Files touched in the last N git commits.
`propose_rename`	v1: same-file rename. Returns an edit list the agent applies via its own `Edit` tool; refuses on clash.

Admin

Tool / op	Purpose
`admin op=init`	Build or refresh the index. Incremental by default; `force=true` rebuilds from scratch.
`admin op=setup_check`	Diagnose hook wiring + embedder + host. Round-trip-tests the hook end-to-end.
`admin op=install_hook`	Wire the auto-reindex `PostToolUse` hook into `.claude/settings.json`. Idempotent.
`admin op=stats`	Read-only: file counts by language, symbol totals, embed model fingerprint, last-index time.
`admin op=verify`	Integrity sweep: orphan rows, parse-failure files, dangling edges.

embed_query_debug is a dev-only ranking diagnostic, hidden from list_tools unless CODE_INDEX_DEBUG=1 is set.

All tools return bounded JSON; large bodies use get_symbol_body rather than inlining whole files.

Requirements

Python 3.10+ with loadable SQLite extension support (required by sqlite-vec).
Python 3.13 has this enabled by default.
On 3.10–3.12, install via the python.org installer or via pyenv with PYTHON_CONFIGURE_OPTS=--enable-loadable-sqlite-extensions pyenv install 3.12.x.
Homebrew Python often ships without the extension hook — use one of the two methods above instead.
`uv` / `uvx` (install) — recommended runner. Or pip if you prefer a permanent install.
~600 MB free disk for the embedding model on first init.

Quick start (Claude Code)

One command, no API keys:

claude mcp add-json -s user code-index "$(cat <<'JSON'

{ "type": "stdio", "command": "uvx", "args": ["--refresh", "--from", "mcp-code-index", "code-index-mcp"] } JSON )"

Then open Claude Code in any repo and ask:

_"Build the code index for this repo."_

Claude calls the init MCP tool, which writes .claude/index.db. From then on, ask things like _"where is parseAuthToken defined?"_ or _"what calls Indexer.reindex_all?"_ — Claude routes them through symbol_lookup / callers / code_search instead of grepping.

What `--refresh` does — fetches the latest PyPI release on every Claude

Code launch. Convenient during preview; drop it once you want to pin a

version (saves ~1s of startup).

Project-only install — drop -s user to register the server in the

current project's .claude/settings.json instead of the global ~/.claude.json.

First-run model download — the first init pulls

jina-embeddings-v2-base-code (~600 MB) into ~/.cache/huggingface and

caches it forever. Subsequent runs are fully offline. If your network

blocks Hugging Face, pre-warm the cache from a machine that has access.

Already installed without `--refresh`? Run claude mcp remove code-index

first, then re-run the command above.

Alternative: permanent install (no uvx)

pip install mcp-code-index

claude mcp add -s user code-index -- code-index-mcp

Optional: keep the index live as you edit

Without a hook, the index drifts when files change outside the agent (mv, git checkout, IDE saves) until you call init again. With one, every Edit / Write / MultiEdit Claude performs triggers an incremental reindex of the touched file.

Easiest path: ask Claude. On first use in a new project, ask _"set up the code-index"_ — Claude calls setup_check → install_hook → init. The hook command is derived from how the MCP server was launched (uvx-aware), so it uses the same Python toolchain. Hook output goes to .claude/code-index-hook.log so failures are debuggable.

Manual install — add this block to the project's .claude/settings.json under hooks.PostToolUse (the version you want depends on how you launch the server — install_hook derives the right one for you):

"matcher": "Edit|Write|MultiEdit", "hooks": [ { "type": "command", "command": "uvx --with 'sentence-transformers<5' --with 'numpy<2' --from mcp-code-index code-index-hook" } ] }

In other MCP-compatible agents

The server speaks standard MCP over stdio, so any client that supports MCP servers works (Cursor, Continue, Cody, Zed, etc.). Configure the client to launch uvx --refresh --from mcp-code-index code-index-mcp (or code-index-mcp after pip install mcp-code-index). Once connected, call the init tool from inside the client to bootstrap the index. Drop --refresh when you want to pin to a stable version instead of always pulling latest.

From source (development)

git clone https://github.com/achreftlili/code-index

cd code-index pip install -e . code-index init # CLI alternative to the init MCP tool code-index-mcp # starts the MCP server on stdio (for manual wiring)

Configuration

All settings are optional — the defaults work out of the box. Override them via environment variables. Inside Claude Code, set them in the env block of your code-index server entry in ~/.claude.json (then reconnect the MCP server).

Common knobs (most users only ever touch these):

Var	Default	When to set it
`CODE_INDEX_EMBED_DEVICE`	_auto_	Force the torch device: `cpu`, `mps`, or `cuda`. Set `cpu` on Apple Silicon if `init` fails with MPS out-of-memory.
`CODE_INDEX_EMBED_BATCH`	`32`	Encode batch size. Lower (e.g. `8` or `4`) to cut peak GPU memory while staying on `mps`/`cuda`.
`CODE_INDEX_DB`	`.claude/index.db`	Override the SQLite index path (e.g. to share an index across sibling worktrees).

Advanced (rarely needed):

Var	Default	Notes
`CODE_INDEX_EMBEDDER`	`jina`	Only `jina` (local sentence-transformers) is supported today; the variable exists for future expansion.
`CODE_INDEX_EMBED_MODEL`	`jinaai/jina-embeddings-v2-base-code`	HuggingFace model id. Only override if you know the model is dim-compatible (768d).
`CODE_INDEX_EMBED_DIM`	`768`	Must match the embedding model's output dimension.

Troubleshooting

`init` fails with `MPS backend out of memory` on Apple Silicon. A large file produced a chunk batch bigger than your GPU's free VRAM. Quickest fix — re-run on CPU (slower but bulletproof):

"env": {

"CODE_INDEX_EMBED_DEVICE": "cpu" }

To stay on the GPU, shrink the batch instead: "CODE_INDEX_EMBED_BATCH": "8". Reconnect the MCP server (/mcp → reconnect, or restart Claude Code) so the new env takes effect. init is incremental — already-embedded files are skipped on the retry.

`init` fails with a Hugging Face network error on first run. Your network is blocking model downloads. Pre-warm the cache on a machine that has access:

huggingface-cli download jinaai/jina-embeddings-v2-base-code

then copy ~/.cache/huggingface/ to the offline machine

`sqlite3.OperationalError: not authorized` or `sqlite-vec` fails to load. Your Python build doesn't have loadable SQLite extensions. See Requirements — install via python.org or a pyenv build with PYTHON_CONFIGURE_OPTS=--enable-loadable-sqlite-extensions.

`code_search` / `symbol_lookup` returns stale paths after a refactor or branch checkout. The auto-reindex hook only fires on Claude's Edit / Write / MultiEdit. After bulk file moves outside the agent (mv, git checkout, IDE rename), re-run init (it's incremental). Or wire up the hook so the index keeps up with agent edits automatically.

Layout

src/code_index/

db.py SQLite schema, connection, sqlite-vec loading parser.py Tree-sitter wrapper, symbol + edge extraction imports.py Per-language import target → file path resolution chunker.py Per-symbol chunks, identifier expansion embedder.py Local Jina (sentence-transformers) backend indexer.py Pipeline: walk → parse → chunk → embed → write reindexer.py Per-root engine cache; one entry point for "reindex one file" retriever.py Hybrid search (vector + FTS5) with RRF watcher.py File watcher (watchdog) admin.py setup_check / install_hook / init logic (pure, no MCP state) mcp_server.py MCP wiring, shared helpers, schema fragments tool_registry.py Shared @_tool decorator + _TOOLS registry tools/ Per-domain MCP handlers (graph, paths, refactor, …) hook.py code-index-hook console script — the PostToolUse entry point cli.py init / r

Only the beginning is shown; read the rest in the repo

Code Index

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Search & AI memoryi

Common questions

Alternatives

Context7

Codebase Memory

Exa

README from the maker

code-index

How it works (30-second tour)

Tools

Retrieval

Admin

Requirements

Quick start (Claude Code)

Alternative: permanent install (no uvx)

Optional: keep the index live as you edit

In other MCP-compatible agents

From source (development)

Configuration

Troubleshooting

then copy ~/.cache/huggingface/ to the offline machine

Layout