code intelligence / knowledge graph / MCP
High-performance MCP server that indexes codebases into a persistent knowledge graph via tree-sitter AST and LSP, exposing fast structural queries for AI coding agents.
Same problem, same approach. Swapping one for another is a config change, not a rewrite.
if you want a C/MIT MCP server that auto-syncs a pre-indexed graph on code changes
Pre-indexed code knowledge graph, auto syncs on code changes, for Claude Code, Codex, Gemini, Cursor, OpenCode, AntiGravity, Kiro, CoPilot, and Hermes Agent — fewer tokens, fewer tool calls, 100% local
if you need large-repo (40M+ LOC) scanning with hybrid semantic search, and can accept AGPL
Enterprise-grade (40m+ LOC) codebase intelligence, zero-setup, local & private Plugin/Skill/Extension or MCP: hybrid semantic search, polyglot dependency graphs, symbol-level impact analysis & call-flow, interactive HTML viewer, cross-project & branch-aware search, DB/API/infra knowledge. 61% less tokens, 84% fewer calls, 37x faster. Cloud in beta.
if you need multi-repo support and 257 languages with a Go/Apache-2.0 MCP server
High-performance code-intelligence engine for AI agents and IDE, supports 257 languages, multi repositories, based on graph, with access via CLI, MCP Server, and API. AI coding agents teammate - expose only needed information, cutting token usage up to 50x. 100% local. Discord: https://discord.gg/39MFHu3J5d
if you want a Python/MIT local-first MCP graph tailored for code-review context reduction
Local-first code intelligence graph for MCP and CLI. Builds a persistent map of your codebase so AI coding tools read only what matters, with benchmarked context reductions on reviews and large-repo workflows.
if you can work with an unlicensed project and want a Python graph MCP server
Graph-powered code intelligence engine — indexes codebases into a knowledge graph, exposed via MCP tools for AI agents and a CLI for developers.
if you want a Rust/Apache-2.0 local MCP server for codebase intelligence
Local code intelligence MCP server and CLI for AI coding agents
Solves the same problem with a different architecture or at a different layer. Expect to rewrite the integration.
if you need a TypeScript MCP server for codebase contextual understanding rather than a C binary
Turbocharge Claude Code, Cursor, Codex, Gemini & every coding agent: faster, cheaper, with contextual understanding specific to your codebase.
if you prefer a skill/plugin that ingests docs, SQL, and PDFs alongside code into a knowledge graph
Turn any codebase, with its docs, SQL schemas, configs, and PDFs, into a queryable knowledge graph. A /graphify skill for Claude Code, Cursor, Codex, and Gemini CLI: local deterministic AST parsing, every edge explained, no vector store.
if you want a lightweight, TypeScript code-search MCP without graph-based structural queries
Code search MCP for Claude Code. Make entire codebase the context for any coding agent.
if you need an MCP toolkit that also performs code editing, not just read-only graph queries
A powerful MCP toolkit for coding, providing semantic retrieval and editing capabilities - the IDE for your agent
if you want a RAG approach combining embeddings with knowledge graphs for monorepo Q&A
The ultimate RAG for your monorepo. Query, understand, and edit multi-language codebases with the power of AI and knowledge graphs
if you need symbol-level retrieval from GitHub repos without local indexing
Cut AI token costs 95%+ on code exploration. The leading MCP server for precise, symbol-level GitHub code retrieval via tree-sitter AST. Works with Claude Code, Cursor & any MCP client. 313B+ tokens saved.
if you need to search both local code and GitHub in one MCP/CLI tool
Code research platform for AI agents; find, understand, and prove context across your code and all of GitHub, in a fraction of the tokens. One toolset, MCP or CLI
An earlier or more limited way to do the job. Still the right call when you need something small, proven, or CPU-only.
if your repo is within its 28 supported languages and you want 244 MCP tools with audit evidence
Local codebase intelligence CLI + MCP server for AI coding agents: SQLite code graph, 28 languages, 287 commands, 246 MCP tools, change-safety gates, audit evidence, zero API keys.
if your repo is within its 7 languages and you want Rust hybrid-search MCP tools
Rust-powered code intelligence CLI for AI coding agents. Builds call graphs and hybrid semantic search indexes (Dense + Sparse + RRF + Reranker) across 7 languages. Ships as native MCP tools for Claude Code and Codex CLI.
Does the same job, but ships as an app. Useful to a person, not swappable into a codebase.
a chat-style codebase Q&A product, not an embeddable MCP server
🧠 RepoBrain (formerly Antigravity) — Give your repo a brain. ChatGPT for your codebase: works in Claude Code, Cursor, Codex, Windsurf & more.
a system-intelligence platform for codebases with a human UI, not a swappable MCP server
Understand any codebase instantly. System intelligence for codebases, built for humans and AI.
These projects were analysed and named codebase-memory-mcp among their alternatives. The relationship is not symmetric — how codebase-memory-mcp rates them is a separate judgement, made when codebase-memory-mcp is analysed in its own right.
calls codebase-memory-mcp “Choose for an ultra-fast static-binary MCP server with 158-language indexing.”
Graphs that teach > graphs that impress. Turn any code into an interactive knowledge graph you can explore, search, and ask questions about. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more.
calls codebase-memory-mcp “choose for a single static binary MCP server with 158-language graph indexing and sub-ms queries.”
Pre-indexed code knowledge graph, auto syncs on code changes, for Claude Code, Codex, Gemini, Cursor, OpenCode, AntiGravity, Kiro, CoPilot, and Hermes Agent — fewer tokens, fewer tool calls, 100% local
calls codebase-memory-mcp “Same MCP code-graph job; choose when you need a single static C binary with millisecond indexing and sub-ms queries instead of a browser/JS engine.”
GitNexus: The Zero-Server Code Intelligence Engine
calls codebase-memory-mcp “Use when you need millisecond-scale indexing and query in a single static binary.”
Local-first code intelligence graph for MCP and CLI. Builds a persistent map of your codebase so AI coding tools read only what matters, with benchmarked context reductions on reviews and large-repo workflows.
calls codebase-memory-mcp “Choose when you need a static C binary and 158-language support over Python deployment.”
Your entire engineering context, deeply understood
calls codebase-memory-mcp “Choose it when you want a high-performance MCP knowledge-graph code index for near-zero token lookups instead of generic compression.”
Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens for coding agents, 60-95% fewer tokens for JSON, same answers. Library, proxy, MCP server.
calls codebase-memory-mcp “Persistent-index MCP server in a single static C binary with very broad language coverage; choose it when deployment size/speed dominate.”
A powerful MCP toolkit for coding, providing semantic retrieval and editing capabilities - the IDE for your agent
calls codebase-memory-mcp “Code intelligence MCP with 158-language indexing; choose for sub-millisecond code queries and 99% token reduction on code retrieval.”
Context window optimization for AI coding agents. Sandboxes tool output (98% reduction), persists session memory, and enforces routing across 17 platforms via MCP + hooks.
calls codebase-memory-mcp “choose it for a high-performance graph-based MCP with millisecond indexing and 158 languages.”
Code search MCP for Claude Code. Make entire codebase the context for any coding agent.
calls codebase-memory-mcp “Pick it when sub-millisecond persistent-graph queries on a single static binary beat octocode's flexible search.”
Code research platform for AI agents; find, understand, and prove context across your code and all of GitHub, in a fraction of the tokens. One toolset, MCP or CLI