Best Codebase AI Skills & MCP Servers

MCP server for AI coding tools and agents. Provides semantic codebase context for Cursor, Claude Code, Codex, Copilot, Antigravity, and CLI workflows without requiring full file uploads.

Local-first code intelligence — MCP server for Claude Code, Cursor, Windsurf, Zed. Symbol graph, blast-radius, git-pinned memory. 43× fewer tokens than naive grep on the public bench. MIT, zero-config.

Code-aware browser testing agent — reads your codebase, understands functionality, tests every element, reports with screenshots. Works as MCP server for Cursor/Claude Code or standalone CLI.

Vexp — Context Engine for AI Coding Agents. Pre-indexes your codebase into a dependency graph and delivers ranked context to any MCP-compatible agent. 58% lower cost per task, 90% fewer tool calls (SWE-bench Verified). Works with Claude Code, Cursor, Copi

Lint your AI agent context files, MCP server configs, and session data against your actual codebase

Reduce Claude Code token usage by 70-90% with cross-session memory and four-layer optimization: semantic codebase indexing, PostToolUse tool compression, turn summarization, and session consolidation. MCP server powered by Ollama — zero API calls, runs en

Bounded conventions map and local-pattern discovery for AI coding agents. Local-first MCP server with AST-backed hybrid search.

AI codebase indexer and MCP server for Claude Code, Cursor, and Copilot. Pre-index your project into a compact graph and measure real token savings with `larkx bench`.

Persistent intelligence infrastructure for agentic development

AI-powered MCP server for codebase navigation and LLM prompt optimization

MCP Server for persistent code indexing. Gives AI assistants (Claude, Gemini, Copilot, Cursor) instant access to your codebase. 50x less context than grep.

MCP server that gives AI agents (Claude, Cursor, Copilot) deep understanding of your codebase patterns, conventions, and architecture. Query patterns, security boundaries, call graphs in real-time.

MCP server for semantic code search and codebase analysis — Treesitter parsing, AST extraction, and embedding-based indexing for any LLM that supports MCP

GraphQL-style codebase intelligence CLI — index, query, and analyze any codebase

MCP server & CLI: codebase index + cache for Claude Code, Cursor, OpenAI Codex, Google Antigravity/Gemini. Model Context Protocol tools (codetree_read, codetree_search, …), hooks on Claude, rules on other IDEs. Token savings, SQLite index, symbol search,

Zero-config codebase context for AI agents. One command generates a ~250-token navigation map and auto-configures Claude Code, Cursor, and Aider.

MCP server that gives Claude, Cursor, and Gemini long-term memory across sessions. Your AI remembers your codebase, decisions, and preferences — across tools and machines.

Local-first MCP server giving AI coding agents fast, structured, and semantic context over any codebase.

Local-first AI-powered codebase analysis tool for stdio or HTTP transports using environment-supplied provider credentials.

MCP server for AI-powered codebase indexing with auto-save checkpoints, incremental updates, real-time progress tracking, and index verification tools

Codebase graph analysis for AI agents — AST + call graph + type graph + hybrid semantic search via MCP

Autonomous Repository Intelligence engine with web UI and MCP server. Unified semantic code understanding, local RAG, and agent working memory.

Your codebase never forgets. Persistent, structured memory for AI coding agents.

Repository scanner that builds a structural map of a codebase (functions, imports, exports, dependencies) and adds file descriptions of what the file does,, so anagentic AI can just read the map and know the project context