code-intelligence
60 servers · 44,460★ total
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.
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.
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
Local codebase intelligence CLI + MCP server for AI coding agents: SQLite code graph, 28 languages, 285 commands, 244 MCP tools, change-safety gates, audit evidence, zero API keys.
MCP server that orchestrates language servers into agent-native workflows. 65 tools, 30 CI-verified languages.
A Model Context Protocol (MCP) server that provides advanced code analysis and reasoning capabilities powered by Google's Gemini AI
Repo memory for coding agents. Local-first MCP for Claude Code, Cursor, Windsurf, and Codex CLI: symbol graph, blast radius, diff-aware review, and git-pinned decisions. MIT; no API keys or code upload.
MCP server for AI coding agents. Instead of reading files one by one, your agent gets dependency graphs, git intent, blast radius, and change health in a single call. Works with any language deep analysis for TypeScript,Java, Go, and C#.
Codebase Context gives AI agents understanding of your codebase through semantic code search, team conventions, patterns, and memory, so they use fewer tokens, spend less time, and produce better, more familiar output.
Universal MCP to LSP bridge - expose Language Server Protocol capabilities as MCP tools for AI agents
Local-first MCP server that gives coding agents structured context packets, code/schema facts, and diagnostics - backed by a local SQLite store.
IDE-style navigation for structured data — code, JSON, YAML. Jump to definitions, find callers, follow references. Available as an MCP server or a mounted folder.
The semantic layer for software engineering: Connect code to meaning, build on understanding
Local-first, auto-injecting context + memory layer for Claude Code, Codex and MCP. Per-prompt hook injection, explicit freshness/Trust Contract, AST indexing, call graphs, hybrid search, wiki + architecture dashboard. Everything stays on your machine.
Whole-codebase knowledge for AI coding agents. A field-aware code graph (functions, classes, methods, fields, references) plus persistent memory. Rust, Postgres + pgvector, MCP.
An experimental, 100% AI-generated, high-performance code intelligence server providing AI assistants with a graph-based understanding of codebases.
Unity-aware AI infrastructure for Claude Code — a knowledge graph + 88 MCP tools that let your AI agent know your project, not just grep its files.
Semantic F# for AI coding agents (Claude Code · Cursor · Copilot · Codex) — an MCP server that gives LLMs real FCS/FSAC compiler intelligence (find, check, types, rename) instead of grepping F#.
MCP server for Unity Editor — 160 tools for scene, assets, animation, VFX, playtest & more
Local pre-flight linter and architecture gate for AI agents. Uses tree-sitter, Stack Graphs, and Datalog to mechanically block structural drift, layering bypasses, and scope creep on virtual ASTs before code changes land.
m1nd is a local-first context runtime for coding agents: an evidence-bound, continuously verified model of your code, memory, and change.
MCP server for deep semantic analysis of Scala via SemanticDB — exact find-usages, class hierarchies, implicit resolution & call paths for AI coding agents like Claude Code. Beyond grep and standard LSP.
Nomik is an AI-native code intelligence graph. It transforms your codebase into Neo4j and connects directly to AI agents via MCP.
Local-first MCP server giving AI coding agents fast, structured, and semantic context over any codebase. Zero config, zero cloud, full context.
Code intelligence for agents: find the code that matters and keep your context window and tokens lean.
Code Intelligence Engine — indexes your codebase and gives AI assistants deep understanding via MCP (semantic search, call graphs, 20+ tools)
A Go symbol and call-graph database backed by SQLite. Query symbols, callers, callees, blast radius, dead code, and interface implementors as structured JSON — typed code navigation for AI agents (MCP) and humans.
Semantic code intelligence for AI agents — compile repositories into navigable concept graphs with impact analysis, coupling detection, and prophecy.
A live, graph-verified map of your codebase for AI coding agents — real call graphs, compiler-verified edges, and hard safety gates on the write path.
Proof-backed, drift-resistant AI memory for your codebase. 11 languages, 28 MCP tools, evidence-linked claims.
Persistent memory for AI coding agents via MCP — a bitemporal knowledge graph of your codebase, served to Claude Code, Cursor, Gemini CLI, and any MCP client. Tree-sitter + Gemini Flash → Neo4j (via Graphiti). 12 MCP tools, hierarchical clusters, two-regime confidence decay.
Verified, fully-local code context for AI agents. MCP-native. No cloud, no editor lock-in.
Deterministic code-graph (GraphRAG) over your repo for LLM agents — local-first, git-native, zero-infra, served via MCP. Python, TS/JS, Rust, Go, Java, C#.
Local Rust codegraph and verifiable workflow for AI coding agents — project maps, change and test impact, MCP queries, and diff-backed implementation audits.
Self-maintaining and persistent codebase memory for AI coding agents — a deterministic AST index plus agent-written notes that flag themselves stale when the code changes. Works with Claude Code, Cursor, and Codex via MCP + CLI.
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.
Cut AI-agent token waste ~90% — query a local SQLite structural index of your JS/TS/CSS codebase with SQL in one round-trip instead of 3–5 file reads. Symbols, imports, calls, components, CSS tokens, coverage, markers. CLI, MCP (21 tools), HTTP, GitHub Action, ESM API. 71 recipes; AST+resolver; SARIF/audit/baselines for CI.
Local-first semantic knowledge graph with magnetic-pull retrieval
Code knowledge graph and MCP search server with tree-sitter parsing, vector + reranker retrieval, and bitemporal knowledge.
AI-powered search capabilities for AI assistants using the Tavily API and Model Context Protocol (MCP)
X-ray vision for your codebase — semantic knowledge graph & MCP server with 16 tools that saves AI coding agents 30%+ tokens. TF-IDF search, call graphs, impact analysis, dead code detection. Works with Claude Code, Cursor & Windsurf.
Multi-repo code intelligence for coding agents, indexed spaces served over read-only MCP
Turn code tasks, diffs, and stack traces into local, relationship-aware context packs for coding agents.
Weld connected structure toolkit for agent-first repository discovery
Persistent code-knowledge memory for AI chats. An MCP server that caches a codebase's structure and summaries in a local SQLite "brain" so sessions query it instead of re-reading files — token-cheap, 100% local.
🧠 The AI that finds the code you didn't know you needed - Sublinear-intelligence MCP server for discovering GitHub leverage
Local code intelligence graph for AI coding agents: Tree-sitter static analysis, structural code search, dependency impact, blast-radius analysis, CLI and MCP server.
Offline MCP server for AI coding agents with semantic code search, symbol intelligence, dependency graphs, and safe file operations.
Gives LLMs precise answers from pre-researched code across repositories and languages - instead of re-scanning files and rebuilding context every session
Public distribution surface for jarvis — local-first code intelligence MCP server (SCIP navigation + Zoekt search). Installer, Claude Code / Codex / Cursor plugins, and prebuilt binaries.
Local graph memory for AI coding agents, giving MCP-compatible tools precise codebase context before they edit.
A token-frugal MCP server that gives coding agents structural understanding of a codebase: repo maps, symbol outlines, ranked search, import tracing, and parsed diagnostics — every result under a token budget it honours.
Persistent, semantically-searchable memory and a symbol-level code graph for AI coding agents. One static Rust binary — SQLite or PostgreSQL, MCP-compatible.
Roslyn code intelligence for AI coding agents, over MCP. Navigate C# by structure — symbols, references, call graphs, surgical edits — for 81% fewer tokens than reading files. Works with Claude, Cursor & Copilot.
AI-powered code search MCP server using Exa API for intelligent code search and retrieval in AI assistants
Production-ready context database and MCP server for AI assistants. Provides code intelligence with hybrid search, call graphs, impact analysis, and semantic search for Cursor, VS Code, and Claude Desktop. Docker-first, 248 languages, auto-indexing.
Loupe for large codebases: focused MCP tools for code search, symbols, maps, diffs, and safe edits.
AI Architect Codebase: cross-platform code intelligence MCP for Claude Code, Codex, Gemini, Cursor, VS Code, and Zed. Tree-sitter AST to LadybugDB graph, hybrid search, and impact analysis.
CodeGraphX (CGX) — a local, token-efficient codebase graph engine & MCP server for AI coding agents. Tree-sitter parsing, a bi-temporal SQLite semantic graph, O(1) symbol lookup, and impact/blast-radius tracing so agents answer 'what breaks if I change this?' in a few hundred tokens.
Local, deterministic code intelligence for developers and AI coding assistants — cited answers about symbols, callers, references, routes, and change impact, without dumping your repo into a context window.