I built a "context OS" that stops AI agents from drowning in your codebase
The problem every AI coding session hits
You open Claude or Copilot, paste in your task, and immediately hit the wall: the codebase is too big. You either:
- Dump everything and burn 80% of your context window on irrelevant files
- Hand-pick files and miss the one import that breaks everything
- Pay for a bigger context window and repeat the problem at scale
I got tired of this and built ContextOS — a local CLI that acts as an intelligent context layer between your repo and your AI agent.
What it does
pip install rm-contextos
cd your-project
contextos scan
contextos pack --task "add rate limiting to the auth endpoint" --budget 8000
Output: a Markdown (or JSON) context pack with only the files that matter for that task — ranked by keyword match, import graph centrality, AST symbol overlap, and git churn. Secrets redacted automatically.
Token savings report on every pack:
Packed 12 files · ~6,840 tokens · saved ~47,200 tokens (87%) vs full repo
How ranking works
Five signals combine into a score per file:
| Signal | What it catches |
|---|---|
| Keyword match | Files whose content/name overlap with your task |
| Import graph centrality | Files that everything else imports (critical shared modules) |
| AST symbol overlap | Function/class names, not just grep strings |
| Git churn score | Recently modified files are probably active code |
| Secret penalty | Credential files silently excluded |
No LLM calls. No cloud. Fully offline.
MCP server (for Claude Desktop / Claude Code)
pip install "rm-contextos[mcp]"
contextos serve --stdio
Register in claude_desktop_config.json and your AI agent can call pack_context, scan_repo, list_files, get_file, churn_report directly as tools — no CLI needed.
What's shipped
980 tests, 96% coverage
Apache-2.0, no telemetry, no accounts
Python 3.11–3.13, Linux + macOS
Export formats: Claude, Codex, Cursor, Aider, JSON
Incremental scan cache — re-scans only changed files
pip install rm-contextos pip install "rm-contextos[mcp]" # + MCP server pip install "rm-contextos[all]" # everything
GitHub: https://github.com/Rohithmatham12/ContextOS Docs: https://Rohithmatham12.github.io/ContextOS/
Would love feedback — especially on the ranking signals and MCP integration. What signals are you missing?
Discussion in the ATmosphere