Structural codebase indexer with MCP server for AI-assisted development

MCP server for AI-powered codebase indexing with semantic memory, smart bootstrap, and intelligent context compilation

A precise local codebase map for AI coding agents: find, trace, and predict with file-line evidence.

17 MCP query tools for codebase navigation — functions, classes, imports, dependency graphs, change impact. Zero dependencies. 87% token reduction.

Local code intelligence engine — three-tier FAISS + SQLite index with 10 MCP tools for semantic code search, blast radius analysis, and architectural investigation

Trace SQL Server tables to C# callers, controller actions, and Razor pages locally. MCP server and CLI with confidence labels. MIT.

Stacklit: AI Codebase Indexing 2026 – Zero-Setup Local Repo Mapping for Agents

Index codebases for AI agents with one command. Build a local map of your repository without server requirements or setup.

Zero-config grammar-free structural codebase indexer and MCP server. ~0.16s builds, sub-ms queries, 4.7MB binary.

A Retrieval-Augmented Generation (RAG) Model-Controller-Provider (MCP) server designed to assist AI agents and developers in understanding and navigating codebases.. It supports incremental indexing and multi-language parsing, enabling LLMs to understand and interact with code.

🧠 Go-based MCP server for RAG code intelligence. Index, query, and analyze your codebase using natural language.

A fact base and lenses for any codebase. Zero-LLM-cost indexing, MCP server for coding agents, BYOK.

High-performance code intelligence MCP server. Indexes codebases into a persistent knowledge graph — average repo in milliseconds. 158 languages, sub-ms queries, 99% fewer tokens. Single static binary, zero dependencies.

MCP server that indexes any codebase with tree-sitter into one local SQLite file — function inventory, call graph, call chains, module dependency graph, control-flow graph, impact analysis and dead-code detection for AI coding agents (Claude Code, Cursor,

Local memory, a codebase index, and working discipline for AI coding agents. Zero dependencies, no network, MCP included. Measured, not asserted.

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

A set of tools to use while coding using the Claude code cli. "smartgrep" is a grep-like tool that uses a semantic index of the codebase to provide Claudes with information tailored for how they think. Claudes love it! A "codebase-curator" Claude to assist the "developer" Claude in his coding tasks, together they implement fully integrated code.

High-performance Rust MCP server & CLI codebase indexer for AI agents. Unlocks deep codebase understanding through semantic vector search, structural graph traversal, and cross-repo dependency resolution. Empowers AI coding agents with semantic and structural search for maximum token efficiency.

A live map of how a big codebase fits together, for Claude Code and for you, with a local import index, an MCP server and the Map.

A local codebase index for coding agents.

Indexed semantic & BM25 code search for AI agents. Give your AI instant memory of your codebase. Rust | MCP Server.

MCP server that indexes a codebase's public API at startup and serves it via compact tool responses. Pluggable parsers for C#, Go, Java, TypeScript, Python, C++, and more.

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

Retrieve CVEs and index them inside your codebase. Offline CVE + exploit intelligence: one SQLite index, one CLI, one MCP server.

A fast codebase indexer and knowledge wiki for AI agents.

Local codebase indexing and search tool. Supports hybrid search, flow tracing and impact analysis.

Retrieve CVEs and index them inside your codebase. One SQLite+FTS5 index, one CLI, one MCP server. Never answer a CVE from memory again.

YATS — Yet Another Token Saver. One-command MCP server that indexes your codebase into a knowledge graph so AI agents (Claude, Cursor, Copilot) can search and navigate it without burning tokens.

Save 94% on AI coding tokens. Index your codebase, agents search instead of reading files. Works with Claude Code, Codex, Copilot, Cursor, Gemini CLI. Local MCP server, free, open source.

Save 94% on AI coding tokens. Index your codebase, agents search instead of reading files. Works with Claude Code, Cursor, Codex, Copilot, Gemini CLI. Local MCP server, free, open source.

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`.

A fast codebase indexer that helps AI assistants understand and navigate your projects using the Model Context Protocol (MCP)

Largescale MCP server for codebase search with background indexing and automatic updating to git commits in rust

MCP server with local vector search for your codebase. Smart indexing, semantic search, Git history — all offline.

Lightweight code indexing and semantic search engine that helps AI agents write code faster while using fewer tokens. Parses codebases with Tree-sitter AST to generate structured headers, with optional LLM insights and vector embeddings. Integrates via MCP server or CLI. Supports TypeScript, JavaScript, C#

Local-first MCP server that indexes a codebase into SQLite and exposes token-efficient search/read/navigation/impact tools.

MCP server that indexes codebases into a SQLite database, exposing file metadata, exports, dependency graphs, and per-file change tracking.

Token-efficient local code retrieval MCP server — index a codebase once with tree-sitter, query exact symbols instead of re-reading files.

Agentmako is a local project intelligence CLI and MCP server for codebases and databases, with repo-aware indexing, schema snapshots, and secure live database connectivity.

A persistent, Git-versioned map of your whole codebase and database schema that coding agents read before they touch anything. Local-first MCP server + CLI in Go: a governed repository index of code knowledge that gives Claude Code, Codex, Cursor, and opencode long-term context, memory, and code intelligence.

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,

Index codebases for AI agents with a single local binary providing semantic search, symbol graphs, and grep capabilities without API keys.

Index codebases into a local knowledge graph to provide accurate context for AI coding tools through a direct MCP server connection.

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

Code intelligence for AI coding assistants — AST-level semantic code search with keyword boost. Index your codebase, search by meaning, keep everything local.

Local-first semantic code search for AI coding assistants. Indexes your codebase with local embeddings and serves context over MCP — find code by meaning, check impact before editing, and surface complexity hotspots, all without sending code externally.

A local-first code retrieval MCP server for AI coding agents. Hybrid keyword + vector search over Graphify-indexed codebases, with domain-aware ranking profiles.

Model Context Protocol server for static analysis of Go codebases with shadow SQLite indexing, background sync, call graphs, import graphs, interface topology, struct lifecycle, endpoints, maintainability metrics, and repo-aware config.

Token-efficient codebase graph engine for AI coding agents. Tree-sitter parsing, SQLite semantic graph, impact tracing, and an MCP server with zero-config auto-indexing.

A high-performance Model Context Protocol (MCP) server written in Rust that extends AI models into autonomous coding agents with semantic memory, built-in Git tools, and codebase indexers

Agentic code discovery: ask your codebase a question, get exact file + symbol + line span in milliseconds. No re-reading, no guessing, no index to build.

Reduce Claude Code token usage by 70-90% using a free local LLM (Ollama). MCP server + Stop hook with codebase indexing, tool output compression, and turn summarization.

A code context MCP server backed by Oracle AI Database 26ai: indexes codebases, hybrid search, call graph, module wiki and agent memory for AI coding tools.

Alcove is an MCP server that gives AI coding agents on-demand access to your private project docs — BM25 + vector hybrid search for precision retrieval, tree-sitter code indexing so agents understand your codebase structure, and policy enforcement for doc consistency.

Memos builds a structural index (symbols, call edges, imports) of a codebase using tree-sitter and stores it in SQLite. It is the first layer of a larger Memory OS for AI coding agents — instead of grep-ing text, agents query structure (definitions, callers, callees).

Local-first hybrid semantic code search tool. Indexes codebases into PostgreSQL with pgvector embeddings via Ollama, combines vector similarity + keyword search with RRF fusion. Supports 30+ languages. Features CLI, MCP server, WEB dashboard and interactive REPL.

NoStale extracts knowledge from your codebase, indexes it, and generates PRD/TDD documents that stay in sync with every commit, no stale docs, no manual regeneration. Browse it from a web UI; ask it questions from the coding agent you already use, over MCP.

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

Ontology-driven codebase indexer and query service. Parses C#, TypeScript/JS, Go, Python, and SQL into an embedded graph database. Exposes Model Context Protocol (MCP) tools for AI agents to perform deep static analysis, cross-project call-graph tracing, and data lineage mapping.