AI Developers
Ideal for developers using AI coding agents to enhance productivity.
Skip if:
Not using AI coding agents.

Open source alternative to Atlassian Code Context and Cursor
Last verified
Index codebases into a local MCP knowledge graph so AI coding agents can query structure, call paths, and impact without rereading every file.
Ideal for developers using AI coding agents to enhance productivity.
Not using AI coding agents.
Useful for teams managing large codebases needing quick insights.
Working with small, simple codebases.
AI coding agents often waste tokens and time exploring codebases by reading files one at a time. This project provides a solution by indexing codebases into a knowledge graph, allowing for efficient querying.
Indexes an average repository in seconds and the Linux kernel in 3 minutes.
Reduces token usage by ~120x for structural queries compared to file-by-file exploration.
Supports 158 programming languages with tree-sitter parsing.
All processing happens locally, ensuring code privacy.
Interactive UI for exploring the knowledge graph.
Matches REST routes to HTTP call sites across services.
Install the local MCP server on macOS or Linux, then restart your coding agent so it can detect the new MCP configuration. The upstream one-line installer is available, or you can clone the repository and run the installer after review.
```bash
git clone https://github.com/DeusData/codebase-memory-mcp.git
cd codebase-memory-mcp
./install.sh
codebase-memory-mcp config set auto_index true
```
For Windows, download the PowerShell installer from the project repository, inspect it, and run `.\install.ps1`. Use `--ui` on supported releases when you also want the local graph visualization server.No, all processing happens locally.
Yes, it is MIT licensed and available on GitHub.
Use the one-line install command: curl -fsSL https://raw.githubusercontent.com/DeusData/codebase-memory-mcp/main/install.sh | bash.
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