Graphify-Labs/graphify
Graphify transforms codebases, documentation, and other files into queryable knowledge graphs, enhancing developer productivity with local AST parsing and detailed edge explanations.
Awesome MCP › Software Development
wrale/mcp-server-tree-sitter
The project "mcp-server-tree-sitter" is a Model Context Protocol (MCP) server that leverages the tree-sitter parsing library to provide advanced code analysis capabilities. It is designed to enable AI assistants, such as Claude Desktop, to intelligently access and understand codebases with effective context management. The server supports multiple programming languages including Python, JavaScript, TypeScript, Go, Rust, C, C++, Swift, Java, Kotlin, Julia, and APL, making it language-agnostic and versatile for various development environments. Key features of the server include flexible exploration of code at different levels of granularity, AST-based structure awareness with efficient cursor-based traversal, and the ability to perform text and tree-sitter query searches. It also offers caching of parse trees to optimize performance, symbol extraction for functions, classes, and other code elements, and dependency analysis to understand code relationships. The server maintains state persistence, keeping project registrations and cached data between invocations, and incorporates security measures such as input validation and security boundaries. Installation is straightforward with Python 3.10+ and tree-sitter language parsers as prerequisites. The server can be installed via pip or cloned for development. It integrates seamlessly with Claude Desktop through MCP CLI or manual configuration, allowing users to register and run the server easily. The server can also be run standalone using the MCP CLI, Makefile targets, or installed scripts. Users can register projects, explore files, analyze code structure, search code, and analyze complexity through the server's API or command interface. The project also supports direct Python usage for programmatic access to its features. Overall, this MCP server enhances AI-driven code analysis by providing structured, context-aware access to codebases using tree-sitter technology.
https://github.com/wrale/mcp-server-tree-sitter
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