Ast Mcp Server
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
Save 60-80% tokens when AI reads code — MCP server for token-efficient code navigation with AST-aware structural reading
Codegraphx
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
Project Scope Mcp
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.
Codeweave Mcp
Save tokens while coding — your AI agent gets structured code context, not file dumps.
Glyph
🔮 glyph – mcp server to map your codebase with symbol outlines
Socraticode
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.
Memtrace Public
Memtrace gives AI coding agents structural memory — your codebase as a live knowledge graph so agents stop re-deriving code structure from scratch and start reasoning from fact.
Semamerge
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
Graph Context
MCP server for intelligent code context — 87%+ token savings, zero resource overhead.