vex
Related Servers
Alternatives to vex
- AlicenseAqualityBmaintenanceEnables AI assistants to search and analyze codebases using Abstract Syntax Tree (AST) pattern matching with ast-grep. Supports structural code search, pattern testing, and AST visualization across multiple programming languages.4471MIT
Related Servers
- AlicenseNot gradedqualityAmaintenanceEnables AI coding agents to query code structure efficiently through 16 MCP tools, including symbol lookup, full-text search, dependency analysis, and refactor planning, powered by tree-sitter parsing and index-backed code intelligence.3MIT
- FlicenseBqualityBmaintenanceLocal-first code intelligence for AI coding assistants: MCP tools, symbol graph search, impact analysis, and auto-index watch for Cursor, Claude Code, and Codex.622-
- AlicenseNot gradedqualityBmaintenanceEnables AI coding agents to query a local, continuously updated symbol graph of a codebase, providing ranked search, caller/callee exploration, dependency paths, and git-diff impact analysis through MCP tools.15 npmApache 2.0
- AlicenseNot gradedqualityNot gradedmaintenanceCodeGraph — Open-source code intelligence MCP server. Builds a semantic graph of your codebase (functions, classes, imports, call chains) and exposes it through 31 tools. Callers, callees, impact analysis, complexity metrics, unused code detection, AI context assembly, persistent memory, cross-project search. 15 languages via tree-sitter. Single Rust binary, local-first.301 npm-
- AlicenseAqualityAmaintenanceKnowledge graph for token-efficient code reviews. Builds a structural map of your codebase with Tree-sitter, tracks changes incrementally, and gives AI agents precise context via MCP tools. Features fixed multi-word search, qualified call resolution, dual-mode embedding (ONNX local + LiteLLM cloud), and output pagination.668Apache 2.0
- AlicenseNot gradedqualityAmaintenanceEnables AI agents to retrieve hyper-targeted, token-efficient context from a codebase by querying a locally built AST knowledge graph, and to persist cross-session agent memory through 17 MCP tools. All indexing and retrieval run entirely offline, so proprietary code never leaves the machine.1MIT
TDQS
Scored across 28 tools
Most tools have clearly distinct query modalities, and descriptions add explicit 'prefer over X' guidance for near neighbours. However, the search family (search/find_symbol/find_similar/similar/grep) and the reference family (callers/usages/paths/reachable/impact/bundle) overlap enough that an agent must read the long descriptions to choose correctly.
Names are consistently lowercase snake_case with no camelCase or casing drift. Minor deviation: a few tools use verb prefixes (find_symbol, find_similar, tests_for) while most are bare nouns or bare verbs.
28 tools is heavy for a single MCP server, even a broad code-intelligence one. Many tools are genuinely distinct, but the surface could likely be consolidated (bundle already subsumes show+callers+callees+similar, and search/find_symbol/find_similar/similar form a large cluster).
The surface covers index lifecycle (index/update/status/capabilities/eval), symbol and structural search, call graph traversal, hierarchy, references, impact analysis, tests, history, diffs, modules, duplicates, and semantic similarity. For a read-only code-intelligence agent, there are no obvious dead ends.