This guide gets you from zero to working in ~5 minutes.
- Python 3.11+
- An Anthropic API key (
ANTHROPIC_API_KEY) - Git
# Clone and install
git clone https://github.com/jessekemp1/cortex && cd cortex
python -m venv .venv && source .venv/bin/activate
pip install -e .
# Initialize data directories and config
cortex init --root-dir /path/to/your/projects
# Verify the CLI works
cortex statusYou should see session context output (project name, recent commits, focus area). If you see errors about missing modules, run pip install -e ".[all]" for the full dependency set.
# Required: set your API key
export ANTHROPIC_API_KEY=sk-ant-...
# Optional: point Cortex at your project workspace
export CORTEX_ROOT_DIR=/path/to/your/projectsCortex stores all data locally in ~/.cortex/. Nothing leaves your machine unless you configure an external embedding provider.
# 1. Onboard — auto-detect your projects and seed memory
cortex onboard --root ~/Dev
# 2. Status — shows your current session context (git branch, recent work, goals)
cortex status
# 3. Health check — verify all subsystems
cortex doctorThe bridge server (api/bridge_endpoint.py) powers intelligence queries and MCP integration. Basic commands (status, onboard, doctor) work without it.
# Start the bridge (runs on :8765)
python api/bridge_endpoint.py
# Or with uvicorn directly
uvicorn api.bridge_endpoint:app --host 127.0.0.1 --port 8765
# Verify it's running
curl http://127.0.0.1:8765/healthOnce the bridge is running, you can use:
# Intelligence query — ask Cortex anything about your project
cortex intelligence "What patterns should I watch out for?"
# Briefing — daily context summary
cortex briefingIf you use Claude Code (or any MCP-compatible client), add Cortex as a tool server:
{
"mcpServers": {
"cortex": {
"command": "python",
"args": ["/path/to/cortex/mcp_server.py"],
"env": {
"ANTHROPIC_API_KEY": "sk-ant-...",
"CORTEX_ROOT_DIR": "/path/to/your/projects"
}
}
}
}This lets Claude query cortex_intelligence, cortex_recommendations, and cortex_anomalies as native tools — no prompt engineering needed.
from cortex.bridge import CortexBridge
bridge = CortexBridge(root_dir="/path/to/projects")
# Query intelligence
result = bridge.query_intelligence("implement caching", project="my-api")
# Get session context
session = bridge.get_session_context()Cortex includes a Gateway module for Telegram (@KempionBot) and web chat (:8765/chat). This feature is not yet active by default. To enable it, you'll need:
- A Telegram bot token (
CORTEX_TELEGRAM_TOKEN) from @BotFather - The bridge server running (
cortex serve)
See cortex/gateway/ for configuration details.
- First session: Cortex starts with an empty memory. It learns from your git history, commits, and interaction patterns.
- After a few sessions: Anti-patterns and insights start accumulating. Briefings become more useful.
- After a week+: Cross-session patterns emerge. Cortex surfaces relevant context before you ask for it.
The more you use it, the more context it builds. This is the compound intelligence effect.
| Issue | Fix |
|---|---|
ModuleNotFoundError: anthropic |
Run pip install -e . (dependencies not installed) |
cortex: command not found |
Activate your venv: source .venv/bin/activate |
ANTHROPIC_API_KEY not set |
Export the key: export ANTHROPIC_API_KEY=sk-ant-... |
Permission denied: ~/.cortex/ |
mkdir -p ~/.cortex && chmod 755 ~/.cortex |
| Intelligence queries return empty | Normal on first run — Cortex needs interaction history to surface patterns |
- Install friction — anything confusing or broken in setup?
- First impressions — does the value prop click within 5 minutes?
- Missing features — what would make this 10x more useful for your workflow?
- Bugs — anything that crashes, hangs, or returns garbage?
File issues at https://github.com/jessekemp1/cortex/issues.