A Python MCP server that exposes the Graphify knowledge graph as MCP tools, prompts, and resources, enabling AI assistants to explore codebases through a token-budgeted, structural graph during development.
Supercharges AI coding agents with a pre-indexed semantic code graph, enabling instant symbol relationships, impact analysis, and context retrieval across 20+ languages.
A graph-powered code intelligence engine that indexes codebases into a structural knowledge graph to provide AI agents with deep context on function calls, types, and execution flows. It offers local, zero-dependency tools for hybrid search, impact analysis, and dead code detection across Python, JavaScript, and TypeScript projects.
Enables developer agents to perform semantic codebase search, dependency and impact analysis, cross-file refactoring, and full-stack API tracing through a unified query DSL over a high-performance graph engine.
Indexes a codebase into a symbol-level graph and exposes tools for finding symbols, querying relationships, and assessing impact, letting AI coding agents answer structural questions in a single call within a token budget.
Provides a semantic understanding of your codebase by parsing with tree-sitter and building a graph of symbols and dependencies. Enables AI assistants to navigate code, analyze changes, and discover architecture using 18 tools with minimal context overhead.
Extracts deterministic architecture maps from codebases for AI agents, enabling queries about blast radius, routes, security findings, and production readiness without sending code anywhere.