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<h1>Installation</h1>
<h2 id="installation-guide">🧩 Installation Guide</h2>
<p>Welcome to <strong>CodeGraphContext</strong>! This guide provides a clear and seamless path to installing and configuring the tool.</p>
<h2 id="understanding-codegraphcontext-modes">📋 Understanding CodeGraphContext Modes</h2>
<p>CodeGraphContext operates in <strong>two modes</strong>, and you can use either or both:</p>
<h3 id="mode-1-cli-toolkit-standalone">🛠️ Mode 1: CLI Toolkit (Standalone)</h3>
<p>Use CodeGraphContext as a <strong>powerful command-line toolkit</strong> for code analysis:
- Index and analyze codebases directly from your terminal
- Query code relationships, find dead code, analyze complexity
- Visualize code graphs and dependencies
- Perfect for developers who want direct control via CLI commands</p>
<h3 id="mode-2-mcp-server-ai-powered">🤖 Mode 2: MCP Server (AI-Powered)</h3>
<p>Use CodeGraphContext as an <strong>MCP server</strong> for AI assistants:
- Connect to AI IDEs (VS Code, Cursor, Windsurf, Claude, etc.)
- Let AI agents query your codebase using natural language
- Automatic code understanding and relationship analysis
- Perfect for AI-assisted development workflows</p>
<p><strong>You can use both modes!</strong> Install once, then use CLI commands directly OR connect to your AI assistant.</p>
<hr />
<h2 id="prerequisites">⚙️ Prerequisites</h2>
<p>Ensure the following are installed before you begin:</p>
<ul>
<li><strong>Python</strong>: Version 3.10 or higher (3.12+ recommended for FalkorDB Lite support)</li>
<li><strong>AI Assistant</strong> (optional): An MCP-compatible tool (e.g., VS Code, Cursor, Claude, Gemini CLI) if you plan to use Mode 2</li>
</ul>
<hr />
<h2 id="installation">🚀 Installation</h2>
<h3 id="step-1-install-from-pypi">Step 1: Install from PyPI</h3>
<p>Install the <code>codegraphcontext</code> package using pip:</p>
<pre><code class="language-bash">pip install codegraphcontext
</code></pre>
<h3 id="step-2-database-setup">Step 2: Database Setup</h3>
<p>CodeGraphContext uses a graph database to store code relationships. You have two options:</p>
<h4 id="option-a-falkordb-lite-default-recommended">Option A: FalkorDB Lite (Default - Recommended)</h4>
<ul>
<li><strong>Automatic</strong> on Unix/Linux/macOS/WSL with Python 3.12+</li>
<li><strong>No configuration needed</strong> - works out of the box</li>
<li>Lightweight, in-memory, perfect for most use cases</li>
</ul>
<p>If you're on Unix/Linux/macOS/WSL with Python 3.12+, <strong>you're done!</strong> Skip to Step 3.</p>
<h4 id="option-b-neo4j-alternative">Option B: Neo4j (Alternative)</h4>
<ul>
<li>Available on <strong>all platforms</strong> (Windows, Linux, macOS)</li>
<li>Required if you're on Windows without WSL or prefer Neo4j</li>
<li>Can be installed via Docker, native installation, or cloud (AuraDB)</li>
</ul>
<p>To set up Neo4j, run:</p>
<pre><code class="language-bash">cgc neo4j setup
</code></pre>
<p>The wizard will guide you through:
- <strong>Docker</strong> (recommended): Automatically sets up a local Neo4j container
- <strong>Native Installation</strong>: Installs Neo4j directly on Debian-based systems or macOS
- <strong>Hosted/AuraDB</strong>: Connect to a remote Neo4j instance
- <strong>Existing Instance</strong>: Use your own Neo4j server</p>
<hr />
<h2 id="mode-specific-setup">🎯 Mode-Specific Setup</h2>
<h3 id="for-cli-toolkit-mode-mode-1">For CLI Toolkit Mode (Mode 1)</h3>
<p>You're ready to go! Start using CLI commands:</p>
<pre><code class="language-bash"># Index your current directory
cgc index .
# List indexed repositories
cgc list
# Analyze code relationships
cgc analyze callers my_function
# Find complex functions
cgc analyze complexity --threshold 10
# See all available commands
cgc --help
</code></pre>
<p><strong>See the <a href="../cli/">CLI Reference</a> for all available commands.</strong></p>
<hr />
<h3 id="for-mcp-server-mode-mode-2">For MCP Server Mode (Mode 2)</h3>
<p>Configure your AI assistant to connect to CodeGraphContext:</p>
<h4 id="step-1-run-mcp-setup-wizard">Step 1: Run MCP Setup Wizard</h4>
<pre><code class="language-bash">cgc mcp setup
</code></pre>
<p>The wizard will:
- Detect your installed AI tools (VS Code, Cursor, Claude, etc.)
- Automatically configure the selected tool
- Generate <code>mcp.json</code> configuration file
- Store credentials securely in <code>~/.codegraphcontext/.env</code></p>
<p><strong>Supported AI Tools:</strong>
- VS Code
- Cursor
- Windsurf
- Claude Desktop
- Gemini CLI
- ChatGPT Codex
- Cline
- RooCode
- Amazon Q Developer</p>
<h4 id="step-2-start-the-mcp-server">Step 2: Start the MCP Server</h4>
<pre><code class="language-bash">cgc mcp start
</code></pre>
<p>Your MCP server is now running and ready to receive requests from your AI assistant!</p>
<h4 id="manual-configuration-optional">Manual Configuration (Optional)</h4>
<p>If you prefer to configure manually or your tool isn't auto-detected, add this to your tool's settings file:</p>
<pre><code class="language-json">{
"mcpServers": {
"CodeGraphContext": {
"command": "cgc",
"args": ["mcp", "start"],
"env": {
"NEO4J_URI": "bolt://localhost:7687",
"NEO4J_USERNAME": "neo4j",
"NEO4J_PASSWORD": "your-password"
}
}
}
}
</code></pre>
<p><strong>Note:</strong> If using FalkorDB Lite (default), you don't need to set NEO4J_* environment variables.</p>
<hr />
<h2 id="quick-start-examples">🧭 Quick Start Examples</h2>
<h3 id="cli-toolkit-workflow">CLI Toolkit Workflow</h3>
<pre><code class="language-bash"># Install
pip install codegraphcontext
# Index a project
cgc index /path/to/my-project
# Find all callers of a function
cgc analyze callers process_payment
# Find dead code
cgc analyze dead-code
# Check database stats
cgc stats
</code></pre>
<h3 id="mcp-server-workflow">MCP Server Workflow</h3>
<pre><code class="language-bash"># Install
pip install codegraphcontext
# Configure your AI assistant
cgc mcp setup
# Start the server
cgc mcp start
# Now use natural language in your AI assistant:
# "Index the code in /path/to/my-project"
# "Find all functions that call process_payment"
# "Show me the class hierarchy for UserController"
</code></pre>
<hr />
<h2 id="database-configuration-details">🔧 Database Configuration Details</h2>
<h3 id="falkordb-lite-default">FalkorDB Lite (Default)</h3>
<ul>
<li><strong>Platform</strong>: Unix/Linux/macOS/WSL</li>
<li><strong>Python</strong>: 3.12+ required</li>
<li><strong>Setup</strong>: Automatic, no configuration needed</li>
<li><strong>Storage</strong>: In-memory</li>
<li><strong>Best for</strong>: Most use cases, quick testing, development</li>
</ul>
<h3 id="neo4j">Neo4j</h3>
<ul>
<li><strong>Platform</strong>: All (Windows, Linux, macOS)</li>
<li><strong>Python</strong>: 3.10+ supported</li>
<li><strong>Setup</strong>: Via <code>cgc neo4j setup</code> wizard</li>
<li><strong>Storage</strong>: Persistent disk storage</li>
<li><strong>Best for</strong>: Windows users, production deployments, large codebases</li>
</ul>
<hr />
<h2 id="next-steps">📚 Next Steps</h2>
<h3 id="for-cli-users">For CLI Users</h3>
<ul>
<li>Explore the <a href="../cli/">CLI Reference</a> for all available commands</li>
<li>Check out the <a href="../cookbook/">Cookbook</a> for common analysis patterns</li>
<li>Learn about <a href="../core/">Code Analysis</a> capabilities</li>
</ul>
<h3 id="for-mcp-users">For MCP Users</h3>
<ul>
<li>See <a href="../tools/">MCP Tools Documentation</a> for available AI tools</li>
<li>Review <a href="../#natural-language-interaction-examples">Natural Language Examples</a></li>
<li>Explore the <a href="../use_cases/">Use Cases</a> guide</li>
</ul>
<hr />
<h2 id="troubleshooting">🆘 Troubleshooting</h2>
<p>If you encounter issues, see our <a href="../troubleshooting/">Troubleshooting Guide</a> for common problems and solutions.</p>
<p><strong>Common Issues:</strong>
- <strong>"cgc: command not found"</strong>: Run the PATH fix script (see main README)
- <strong>Database connection errors</strong>: Ensure Neo4j is running (if using Neo4j) or Python 3.12+ (if using FalkorDB)
- <strong>MCP server won't start</strong>: Check that your AI assistant is properly configured</p>
<hr />
<p>With <strong>CodeGraphContext</strong> installed, you're ready to explore powerful code analysis capabilities! Happy coding ✨!</p>
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