#tree-sitter

MCP Server for Tree-sitter

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

A library for indexing code repositories using Tree-sitter Stack Graphs, designed to be used in MCP servers and other tools.

Save tokens while coding — your AI agent gets structured code context, not file dumps. CodeWeave is an MCP server that gives AI agents structured code intelligence instead of dumping entire files into context. Your agent queries local indexes — AST, call graph, type graph, and hybrid semantic search — and gets back only what it needs. The result: less token waste, more relevant context, better coding decisions. It supports 7 languages (Python, TypeScript, JavaScript, Go, Rust, Java, C#) with a 6-stage hybrid search pipeline combining vector embeddings, full-text search, and structural density scoring. Everything runs locally with zero external dependencies beyond Ollama for embeddings. Monorepo and git worktree support included. A file watcher keeps indexes current as code changes — no manual reindexing needed. ATTENTION: Run "npx @codeweave/mcp" in your project directory first. The setup wizard handles everything for you. At first, it may take some time. INFO: Exhaustively tested on large Java, C#, JavaScript, TypeScript, React codebases. Contributions and feedback are welcome.

Deterministic cross-branch conflict detection for AI coding agents. Scans your git repo for function signature mismatches, HTTP route conflicts, and schema breaks across branches using tree-sitter AST analysis. Catches the merge failures that CI misses because tests only run on one branch at a time.

Ganglia indexes your project into a call graph and exposes 73 semantic tools — code_get, code_callers, code_impact, code_propagate, code_apply_batch with one-click revert, code_safe_move, deliberation chain, smart LLM-backed digests, cross-session memory, and more. Works with Claude Code, Cursor, Windsurf, Continue, Cline, Goose. Languages: TypeScript, JavaScript, Rust, Python, Go, PHP. Free during public beta. Token savings: 80–95% vs raw file-reading patterns.