10 #ast MCP Servers & Clients

AST MCP Server

angrysky56

By transforming source code into a queryable Semantic Graph and a structured AST, this tool bridges the gap between "reading text" and "understanding structure." For an AI assistant, it provides the "spatial" awareness needed to navigate deep dependencies without getting lost in

Token Pilot

Digital-Threads

Save 60-80% tokens when AI reads code — MCP server for token-efficient code navigation with AST-aware structural reading

Codegraphx (cgx)

techcraze00

CodeGraphX (CGX) — a local, token-efficient codebase graph engine & MCP server for AI coding agents. Tree-sitter parsing, a bi-temporal SQLite semantic graph, O(1) symbol lookup, and impact/blast-radius tracing so agents answer 'what breaks if I change this?' in a few hundred tok

glyph

benmyles

🔮 glyph – mcp server to map your codebase with symbol outlines

CodeWeave Mcp

semihkayan

Save tokens while coding — your AI agent gets structured code context, not file dumps.

MCP server for intelligent code context — 87%+ token savings, zero resource overhead.

Memtrace — Structural Memory for AI Coding Agents

Project Scope

adityasasidhar

A production-ready MCP server that gives AI agents deep codebase understanding. Features AST-based semantic analysis, context-aware security scanning (zero false positives on source code), safe refactoring tools with previews, and comprehensive Git operations.

MCP server that detects semantic (non-textual) merge conflicts between Git branches using AST-level analysis. Catches incompatible changes that Git merges cleanly but break at runtime — like signature changes, removed exports, interface breaks, and cross-file dependency conflicts

Socraticode

giancarloerra

Enterprise-grade (40m+ lines) codebase intelligence in a zero-setup, private and local MCP: managed indexing, hybrid semantic search, polyglot code dependency graphs, and DB/API/infra knowledge. Benchmark: 61% less tokens, 84% fewer calls, 37x faster than standard AI grep.