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?
SOCIAL SHARE CARD GENERATOR