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# Cerebro 🧠

**Persistent code-knowledge memory across AI chat sessions.**

Every new chat re-analyzes your project's folders from scratch to understand it,
burning tokens re-discovering what a previous chat already learned. Cerebro caches
the *understanding* — not just the files — in a small SQLite "brain" that lives
**outside** the chat. New sessions **query** it instead of re-reading folders.

Instead of reading 50 files (~100k tokens) to understand a project, the model makes
one `cerebro_map()` call (~2-3k tokens) plus a few targeted lookups.

## How it works

Three layers of "traces", cheapest first:

1. **Structural map** (free, no LLM) — `tree-sitter` extracts symbols + imports and
   builds a dependency graph. Imports resolve both relative paths and **tsconfig /
   jsconfig path aliases** (`@/...`), so Next.js / NestJS monorepos get real edges.
   **PageRank** ranks the most important modules. Each file is hashed so changes
   are detectable. Languages: Python, JavaScript / TypeScript (incl. JSX/TSX)
   and Dart / Flutter.
2. **Cached summaries** (the big saver) — as a chat understands a file, it calls
   `cerebro_record(path, summary)` to store a 1-3 sentence **English** summary
   (English tokenizes ~15-30% cheaper than Spanish). Future sessions reuse it.
3. **Freshness** — each summary is tied to the file's hash. If the file changed,
   the trace is flagged **stale** so only that file gets re-read.

> Why not Dijkstra? Code knowledge is a *relevance* problem, not a shortest-path one.
> The useful algorithms are graph traversal (BFS/DFS, for impact) and centrality
> (PageRank, for ranking) — not weighted routing.

## MCP tools

| Tool | Purpose |
|------|---------|
| `cerebro_map(top=30)` | Cheap project overview, modules ranked by centrality. **Call first.** |
| `cerebro_get(path)` | Summary + symbols + dependencies of a file, without reading it. |
| `cerebro_search(query)` | Hybrid semantic + keyword search; semantic hits resolve to the exact symbol (`path:line`), not just the file. |
| `cerebro_record(path, summary)` | Leave a trace: store your understanding of a file. |
| `cerebro_note(content, topic?)` | Record a decision / domain rule / gotcha (the *why*). |
| `cerebro_recall(query?)` | Recall decisions recorded by past sessions. |
| `cerebro_stale()` | Files changed since last index + stale summaries. |
| `cerebro_sync()` | Catch branch switch / git pull / external edits and reindex them. |
| `cerebro_reindex(paths?)` | Refresh the structural index (only changed files). |
| `cerebro_impact(path)` | Transitive blast radius: everything that (in)directly imports a file. |
| `cerebro_cycles()` | Circular-import groups (architecture smell). |
| `cerebro_orphans(prefix?)` | Code files nothing imports — dead-code candidates (file-level). |
| `cerebro_dead_symbols(prefix?)` | Unused-export candidates: functions/classes/methods referenced nowhere *in their own project*, inside files that *are* imported (symbol-level dead code). |
| `cerebro_callers(name)` | Call sites of a symbol (who calls it, with enclosing fn + line). |
| `cerebro_calls(path)` | Internal functions a file calls (outgoing call edges). |

## Install

**One command** (published on PyPI) — add the MCP server to Claude Code:

```bash
claude mcp add cerebro -- uvx cerebro-code-memory
```

Or install the full **Claude Code plugin** (MCP server + session hooks + cerebro-first subagents):

```
/plugin marketplace add marcodavidd020/cerebro-code-memory
/plugin install cerebro@cerebro
```

Requires Python ≥ 3.10. Point Cerebro at a repo with `CEREBRO_ROOT=/path/to/repo`; it
also auto-detects the nearest ancestor `.cerebro/` brain (handy in monorepos).

## Quick start

One command onboards any repo — it indexes and prints the exact registration line:

```bash
uv tool install --from . cerebro          # installs the `cerebro` command globally (dev)
cd /path/to/your/repo
cerebro setup --summarize --embed          # index (+ warm summaries / semantic index), then prints next steps
```

`cerebro setup` is idempotent. Then run the `claude mcp add …` line it prints, reload
your editor, and the `cerebro_*` tools are available in chat.

## Unified CLI

```
cerebro                 # no args -> MCP server (stdio); this is what the registration runs
cerebro setup           # index this repo + print MCP registration
cerebro index [--force] # build/refresh the index
cerebro search <query>  # hybrid semantic + keyword search
cerebro map             # project overview
cerebro graph           # interactive dependency-graph HTML
cerebro obsidian        # export an Obsidian vault
cerebro summarize / embed
cerebro impact / cycles / orphans / callers / calls / recall
cerebro doc-audit <vault>   # living docs: flag knowledge notes whose referenced code changed
```

### Living documentation (`doc-audit`)

`cerebro doc-audit <markdown-vault>` cross-checks a curated knowledge vault against
the code index: it parses each note's code references (`path:line`, backticked
symbols) and the note's `ultima_verificacion`/`fecha`, then flags notes whose
referenced files **changed after** they were verified, **moved/were deleted**, or
mention a **symbol that no longer exists**. `--aliases` maps wiki app names to repo
dirs (`backend_app=fenix-store-backend,…`); `--fix` patches stale notes' frontmatter
to `estado: revisar`. This is the bridge between an auto-fresh code index and a
human-curated wiki — documentation that can't silently rot.

`cerebro doc-refresh <note>` closes the loop: it re-audits one stale note against
the *live* code and prints a briefing — current symbols, summary and dependents for
each reference, plus the new location of any moved file — exactly the context an
agent needs to propose the update (self-healing docs, human-reviewed).

Without a global install, prefix any command with `uv run` (e.g. `uv run cerebro setup`).

Point Cerebro at a specific repo with `CEREBRO_ROOT=/path/to/repo`. It honors
`.gitignore` plus an optional **`.cerebroignore`** (same syntax) for excluding
heavy non-source dirs (`backup/`, `**/uploads/`, …) without touching your VCS
config. `node_modules/`, `.next/`, `dist/`, `build/` are ignored by default.

Works on monorepos: index the whole thing at once (a single brain at the root,
with cross-package alias resolution) or per sub-app (`CEREBRO_ROOT` per package).

### Register with Claude Code

```bash
claude mcp add cerebro -- uv --directory /path/to/cerebro run cerebro
```

Set `CEREBRO_ROOT` to the project you want the brain to cover. See `plugin/` for the
optional Claude Code plugin that auto-injects the map at session start and flags
edited files as stale.

## Scope (MVP) 

In: structural map, cached summaries, freshness, keyword search, tsconfig/jsconfig
alias resolution, `.cerebroignore`, batch summary warming (`cerebro-summarize`, via
headless `claude -p` — no API key), a decision log (`cerebro_note` /
`cerebro_recall`, surfaced at session start), and git-aware freshness
(`cerebro_sync` catches branch switch / pull / external edits across nested repos),
and optional local semantic search (`cerebro-embed` + `--extra semantic`: model2vec
embeddings — one vector per symbol — no torch, no API key, nothing leaves the
machine — `cerebro_search` becomes hybrid semantic + keyword and lands on the exact
symbol (`path:line`), not just the file), and visualizations (`cerebro-graph` →
self-contained interactive HTML dependency graph; `cerebro-export-obsidian` → an
Obsidian vault where imports are `[[links]]`), and architecture insights
(`cerebro_impact` transitive blast radius, `cerebro_cycles` circular imports,
`cerebro_orphans` dead-code candidates), and a symbol-level call graph
(`cerebro_callers` / `cerebro_calls`, tree-sitter name-resolved).
Deferred to v2: a live file watcher, and LSP-backed call graph for type-precise
resolution (the current call graph resolves by name).

## License

MIT © 2026 Marco Toledo — see [LICENSE](LICENSE).

TDQS

A4/5.0

Scored across 16 tools

Disambiguation5/5

Each tool targets a clearly distinct aspect of code analysis: call sites, call edges, circular imports, dead symbols, endpoints, file info, impact analysis, project overview, note-taking, orphan files, recall, file recording, reindexing, search, stale index, and sync. Even similar tools like dead_symbols vs orphans and note vs record vs recall are differentiated by scope and purpose.

Naming Consistency5/5

All tools follow a consistent 'cerebro_' prefix with snake_case naming (e.g., cerebro_callers, cerebro_dead_symbols). The second part is either a noun (callers, cycles) or a verb (get, search), maintaining a predictable pattern throughout.

Tool Count5/5

With 16 tools, the server covers a comprehensive set of code intelligence operations without being overly numerous. Each tool serves a specific purpose in the workflow of understanding and navigating a large codebase, fitting well within the typical 3-15 range for focused servers.

Completeness4/5

The tool set covers core code analysis needs: dead code detection, call graphs, dependency analysis, search, project overview, and knowledge persistence. Minor gaps include lack of direct file content retrieval or file listing, but the server's focus on precomputed index data means these are reasonable omissions.

Maintenance

ActivityInactive
ResponsivenessNo issues