AST Knowledge Graph Server for Claude Code

An MCP server creating AST knowledge graphs for code, enabling semantic search and impact analysis across 10 languages.

AST Knowledge Graph Server for Claude Code

The AST Knowledge Graph Server for Claude Code is an open-source MCP (Meta-Cognitive Programming) server designed to process and analyze codebases. It transforms Abstract Syntax Trees (ASTs) into a knowledge graph, providing a structured representation of code that facilitates advanced querying and analysis. This tool is particularly valuable for developers working with large or complex code repositories, enabling deeper understanding and more efficient code management.

What it Does

This MCP server ingests source code written in up to 10 different programming languages. It parses the code to generate an Abstract Syntax Tree (AST) for each file. These ASTs are then used to construct a comprehensive knowledge graph. This graph captures the relationships between code elements, such as function calls, variable declarations, class inheritance, and more. The primary output is a queryable graph database that allows for semantic search and impact analysis of the codebase.

Key Features

Multi-language Support: Capable of processing code from 10 distinct programming languages.
AST to Knowledge Graph Conversion: Automatically generates a knowledge graph from code ASTs.
Semantic Search: Enables searching code based on meaning and relationships, not just keywords.
Impact Analysis: Facilitates understanding how changes in one part of the code might affect other areas.
Open Source: Developed and maintained on GitHub, allowing for community contributions and transparency.

Who it's For

This tool is targeted at AI builders, software engineers, and developers who require sophisticated code analysis capabilities. It is ideal for individuals and teams working on:

Large-scale codebases: Where manual analysis is impractical.
Complex software systems: Requiring a deep understanding of interdependencies.
Code refactoring and migration projects: To assess the scope and impact of changes.
Developing AI agents for code understanding: Providing a structured data source for training and inference.