Skip to content

grag documentation

Project memory that carries forward

Keep code, documents and decisions in a local graph your agent can use across sessions.

Set up your first project Explore the guides

What would you like to do?

  • Get connected

    Install grag, connect your agent and verify a first read and write.

    Get started →

  • Navigate a codebase

    Index selected sources and find definitions, callers and source citations.

    Index code →

  • Keep useful memory

    Save decisions, correct earlier notes and resume unfinished work.

    Save and recall →

  • Find the right context

    Retrieve relevant evidence within a budget and check its freshness.

    Retrieve context →

  • Resolve a problem

    Diagnose connection errors, missing libraries and database ownership.

    Troubleshoot →

  • Look up an interface

    Find MCP tools, CLI flags, environment settings and write contracts.

    Open the reference →

A small local setup

Start with one database per checkout and BM25 full-text search. Multiple agent clients share one owning server. Embeddings and remote serving are optional.

Bring to the graph Use it for
Code structure Definitions, signatures, line ranges and supported relationships
Documents Source text, sections and links to code
Agent memory Decisions, tasks and findings with their reasons and sources

The graph can only retrieve what was indexed or saved. Your harness chooses when to read or write, and may send retrieved context to its model provider.

How grag fits together →

Which version do these docs describe?

This guide describes grag 0.11.0 and deploys from main. Features still in development are marked on the relevant page. This is one maintained guide rather than a separate copy for each release.

For an additional generated architecture view, visit DeepWiki. Check its index date and source commit; its refresh schedule is independent of grag releases.