CORTEX

Getting started

Install

The fastest way to install Cortex:

npx @1337xcode/cortex install

This downloads the binary for your platform, detects your AI coding agents, and writes the MCP config for each one. No manual configuration needed.

Alternatives:

# Shell script (macOS/Linux)
curl -fsSL https://raw.githubusercontent.com/1337Xcode/cortex/main/install.sh | sh

# Build from source
git clone https://github.com/1337Xcode/cortex.git && cd cortex
cargo build --release
cp target/release/cortex ~/.local/bin/

Index your repository

cd /path/to/your/project
cortex index

This parses every source file with tree-sitter, extracts functions, classes, call edges, and import relationships, then stores them in a local SQLite database at .cortex/graph.db.

Indexing is fast. A 3500-file Python project (CPython) indexes in under 60 seconds. A typical 100-file project takes about 500ms.

Start the MCP server

cortex serve

This starts the MCP server over stdio (JSON-RPC 2.0). Your AI agent connects to it and gains access to 32 structural query tools.

For reduced context overhead (agents see 5 tools instead of 32):

cortex serve --smart-tools

In smart-tools mode, the ask meta-tool handles everything. The agent sends a natural language question, Cortex routes internally to the right graph queries, and returns a composed answer.

You don’t usually run this manually. The cortex install command configures your agent to launch cortex serve automatically when it starts a session.

Configure your agent

If you didn’t use npx @1337xcode/cortex install, configure manually:

cortex install

This detects installed agents and writes the correct config for each:

AgentConfig location
Claude Code~/.claude/settings.json
Claude Desktop (macOS)~/Library/Application Support/Claude/claude_desktop_config.json
Claude Desktop (Windows)%APPDATA%\Claude\claude_desktop_config.json
Cursor~/.cursor/mcp.json
Windsurf~/.codeium/windsurf/mcp_config.json
VS Code.vscode/mcp.json (workspace)
Zed~/.config/zed/settings.json
JetBrains~/.config/github-copilot/mcp.json
Kiro~/.kiro/settings/mcp.json
Cline.cline/mcp.json

Verify it works

Ask your agent: “What are the most-called functions in this codebase?”

The agent should use the get_architecture or search_symbols tool and return structural results from the graph rather than reading files.

What happens next

Once indexed, Cortex keeps the graph up to date automatically:

  • The file watcher detects changes and re-indexes modified files in sub-second time
  • Observations you write persist across sessions
  • The bundle (cortex.json) can be committed to git for team sharing

Common next steps

# Generate a security report
cortex security report

# See what breaks if you change a function
cortex impact MyClass.my_method

# Export an interactive graph visualization
cortex viz --export graph.html

# Set up auto re-indexing on commit
cortex hook install

# Add another repo to the federation
cortex federate add ../shared-lib

# Ingest documentation into the graph
cortex ingest ./docs

# Show build system workspace members
cortex modules --build-system

# Find high-churn risky code
cortex hotspots

# Cross-reference test coverage with call graph
cortex coverage --lcov coverage.lcov