Product
The missing memory layer for AI engineering.
Atlas builds the repository structure your coding agent cannot keep in context: dependencies, citations, impact paths and validated local memory.
Capabilities
Ask about behavior, not filenames.
Atlas is not a chatbot over your repo. It is a deterministic local index your agents can query when they need grounded context.
- 01
Dependency graph
A local map of modules, imports, hubs, cycles and dependency paths.
- 02
Impact
Deterministic what-breaks analysis from the resolved graph before you edit.
- 03
Debug
Start from a symptom or traceback and get a grounded investigation path.
- 04
Plan Change
Generate a change plan around the files and symbols Atlas found.
- 05
MCP export
Serve the same local index to Claude Code, Cursor and Codex.
Evidence
Every answer has a trail back to the code.
Atlas gives the agent file-level evidence rather than asking it to infer structure from a shrinking prompt window.
Scan
Read local source files and resolve symbols/imports.
Map
Build graph relationships and evidence rows.
Serve
Expose cited context to agents through MCP.
Integrations
One local index, multiple agents.
Atlas complements your coding agent; it does not replace it.
Limits
The honest parts are part of the product.
Numbers are self-measured on one Windows development machine; your hardware will differ.
The 50-scenario suite runs against a reference repository we built, not a random sample of OSS projects.
Large monorepo indexing is slower and is an active work item.
Retrieval quality is not the same as end-to-end task success with a coding agent.