Save 6-8× tokens on AI code reviews. Builds a structural call graph via Tree-sitter + MCP. Works with Claude, Kimi, Gemini, ChatGPT, Cursor, Windsurf — any AI assistant.

Native Code Knowledge Graph plugin for Google Antigravity (AGY) powered by Tree-sitter AST, SQLite & code-review-graph. Features 22+ MCP tools, 9 workflow skills & deterministic zero-lag incremental indexing.

Token-efficient code review knowledge graph: semantic search and call-graph resolution.

Knowledge graph for token-efficient code reviews -- semantic search and call-graph resolution across your codebase.

Graph-native AI copilot for large codebases. Reviews PRs, answers questions with citations, plugs into Claude Code / Cursor / Aider / Codex / Gemini CLI via MCP.

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.

A deterministic code graph for codebases: every caller, route, page and table a change touches, with file:line evidence. CLI, MCP server and web view for AI agents and reviewers.

AI-native code-intelligence engine in Rust — risk-ranked blast radius, PR review targeting, and cross-service call graphs across 13 languages. Runs as a CLI, an MCP server for AI agents, and a resident file-watching daemon.

The Context Engine for AI Coding: Persistent incremental knowledge graph for token-efficient, context-aware reviews

5D Living Code Graph, 1-Call Subagent Context (chronos_explore), 4-Angle Review Audit, Surface Tracer, Universal Multi-Agent Synthesizer (Codex/Antigravity/Claude/OpenCode/Cursor) & Super-Mutant Gate (12 MCP Tools)

AI-powered spec generation and review using multi-repo code graph intelligence for backend teams that ship to production.

Open-source memory CLI for Claude Code, Codex & MCP — local-first SQLite, graph-aware recall, review gate. npm i -g waypath

Distill AI coding sessions (Claude Code / Codex / Cursor) into weekly reports, ADRs, incident reviews and a knowledge graph — local-first, evidence-linked.

Persistent research memory for agentic harnesses (Claude Code, Claude Desktop, Codex): a local knowledge graph of companies, sourced claims and investment theses, with SEC filing alerts and research workflows (onboard, challenge, memo, review). MCP server + plugin.

Agent memory you can code-review. Tusk indexes a folder of markdown into a typed, searchable graph your agents query over MCP. It stays plain files in git, and tusk doctor fails CI when a link dangles or a convention breaks.

AI code assistant with GraphRAG: FastAPI + React platform using LangChain agents, a Neo4j code knowledge graph, and ChromaDB hybrid retrieval for LLM-powered code generation, review, and analysis with SSE streaming and an MCP server.

Code Workbench gives Claude the tools to maintain your Obsidian vault through its own link graph (link-preserving, approval-gated MCP edits over the CLI), plus a real code editor: syntax highlighting, diagnostics, formatting, Keep/Reject diffs, git review, and inline blame for 50+ languages. Runs on your Claude subscription, not a metered API key.

MCP server that gives AI assistants deep codebase understanding. Semantic graph, BM25 search, impact analysis, code review.

Project memory and skill routing for coding agents. Share decisions, search a local knowledge graph, and run code reviews through the CLI or MCP.

One-entry orchestrator for coding agents: jailed vault, FTS knowledge graph, Obsidian-native architecture and code notes, 18-axis review. Curated packs — not a 90k-skill dump

AI Constraint Engine by Sandeep Roy — AI Patch Firewall. Diff-native review (interface breaks, protected symbols, dependency drift, schema changes, API impact), Patch Gateway (ALLOW/WARN/BLOCK verdicts), Spec Compiler (NL→constraints), Code Graph (blast r

Rustic SQLite Code Graph 2026 – 28 Languages, 238 Commands, Zero API Keys

High-throughput agent context router and deterministic static analysis engine.

Semantic code graph for AI agents — deterministic FQN resolution, impact analysis and architectural drift gates, exposed over MCP.

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.

Your codebase companion for JavaScript/TypeScript, in the browser, the terminal and your AI agent: a live dependency map, impact and call sites, affected tests and patch coverage, review order, new-only CI gates (SARIF, GitLab), git hooks, a status line a

Local-first code intelligence and MCP-native review engine for Python and TypeScript repositories

Real-time code quality gates & dependency graph for AI-assisted development. MCP server for Claude Code, GitHub Copilot, and any MCP-compatible agent.

Code intelligence for AI coding assistants: precise MCP context, security reviews, dependency analysis, and session telemetry for Claude Code, Codex, and Cursor.

Evidence-linked repository change-impact graph with a minimal MCP stdio interface. Unknowns stated as unknown.

代码知识图谱分析 Agent：Tree-sitter AST 解析 + 函数调用图 + 多 Agent 问答 + MCP 服务，支持 8 种语言

Open-source, local-first control plane for multi-model AI coding agents in VS Code and MCP: task DAGs, source intelligence, durable context and evidence-based review.

The ripgrep of AI context: a zero-dependency C++23 CLI + MCP server for coding agents. Cut agent token costs by finding code without reading the repo, then keep large codebases off the complexity wall: blast radius, tests to run, quality deltas as you write. Every guess labelled, every loss published. Paddle out with a map.

Open-source Software Intelligence Platform. Deterministic verification, structural PR reviews, interactive graph explorer, and proactive intelligence — powered by the Software Graph. 41 node types · 32 relationships · 120+ checks.

Semantic Scholar MCP server: 14 typed tools for paper search, citation graphs, author profiles, recommendations, PyPI/Docker.

Behavioral diff for AI-written code. Your agent changed 40 files — Veris tells it what behavior actually changed and whether any of it was verified. MCP-native, checker-resolved call graph, tamper-evident evidence. Never executes your code. Local-first, MIT.

Self-hosted. Understand, review, secure and fix your code in one place: questions across repositories with file:line citations, PR review that looks past the changed repo, CVE audit and CycloneDX SBOM, fixes opened as pull requests, and the same context for coding agents over MCP. AGPL-3.0.

Your AI agent writes code — but does it know WHY your code exists? Decision provenance, quality contracts, and AI anti-pattern detection for coding agents.

Your AI agent writes code — but does it know WHY your code exists? Decision provenance, quality contracts, and AI anti-pattern detection for coding agents. 19 languages. MCP compatible.

Explain your codebase in 30 seconds. Interactive architecture diagrams with AI descriptions, health scoring, and blast radius analysis. Works with Claude Code, Codex, Copilot CLI, and Gemini CLI.

Renders what a branch changed to your architecture as one picture a human can confirm at a glance, and gives a coding agent boundary verdicts it can run on itself before asking for review. Hexagonal / ports-and-adapters, Kotlin. CLI · MCP · web UI.

Evidence-chain whiteboard + MCP server for AI research agents: every claim traces back to the run and code that produced it. 讓 AI agent 做研究時，每個結論都能追到產生它的程式碼。Claude Code · Codex · Cursor · Gemini CLI

Deterministic, local-first change-impact analysis for Python, JavaScript, and TypeScript—trace blast radius, suggest tests, and gate risky PRs.

Keep code understandable. The evidence layer between the agents that write code and the people who stand behind it: where to look first, who can look, what a change did to the structure and what nobody maintains. Offline, zero dependencies, with the evidence for every claim.

The experience graph for AI agents. Self-hosted memory, human-reviewed decisions, and outcome-backed datasets for model evaluation and learning.

Literature searches in PubMed and PubMed Central for researchers and their AI assistants: full texts, the evidence around a paper and an Obsidian knowledge graph, with an MCP server and a plugin for Claude Code and Codex.

Multi-language repository map for agents and humans: MCP tools, dependency graphs, symbol indexes, impact review, and bounded source evidence.

Supervise an AI coding agent (Claude Code / Codex / ACP) overnight and keep control: block forbidden tool calls before they run, gate 'done' on real tests, checkpoint work to git, cap spend, and get a morning report where every line is sourced. Local-first, no telemetry. Rust daemon + Tauri app + Claude Code plugin.

A memory of the codebase your AI agent can't get from grep: a persistent call graph, semantic search, and per-symbol review learnings over any repo. Self-hosted MCP server — Go, tree-sitter, Apache AGE.

Native Rust code intelligence for repository navigation, change review, impact analysis, and code health, backed by per-project RocksDB.

Turn Obsidian inbox notes into checked, linked knowledge cards: one model drafts, an independent reviewer checks each card against the source, code writes the vault in one recoverable step. Daily FSRS review. Agent Skill, MCP or CLI. 把 Obsidian 收件箱笔记变成经独立复核、互相关联的知识卡片，并用 FSRS 每日复习。

Framework-aware code intelligence MCP server — 91 framework integrations, 81 languages, 72.7% fewer input tokens to review a pull request, comprehension at parity

Reliable memory and context infrastructure for AI coding agents: source-backed facts, review-gated learning, MCP/SDK/UI, and replaceable Qdrant/Graphiti retrieval.

CogmemAi: the safe memory that keeps Ai in line. Remembers across sessions, enforces your rules before actions, reviews the work. MCP server, REST and SDKs.

Safety-first context & orchestration engine for AI coding agents. MCP server with mandatory research pipeline, knowledge graph, impact analysis, decision memory, and safety guard — works with any MCP client.

Understand what your codebase builds, why it is structured that way, and what a change could affect. One shared Markdown ontology for humans and coding agents—visualized for people, accessible to agents through MCP, and reviewed with Git. Local-first. Open source.

Verifiable shared memory for AI agents and people. Every claim is an atom with a source quote checked against the real file, full revision history and human review. Hybrid search on PostgreSQL + pgvector, MCP server and CLI for Claude Code and Codex, web UI.

Point a cross-model AI engineering team at your own codebases. The Agent OS keeps named AI maintainers' identity, memory and review across labs alive between sessions — the Brain Neo.mjs runs on itself. Multi-tenant: onboarding a codebase is a config entry, not a fork.

This project replaces error-prone, 2-day manual structural reviews with a 4-minute Agentic AI workflow that parses IFC models for code compliance. It ensures structural safety through real-time 3D visual overlays, explainable reports, and automated "auto-fix" design suggestions.

Shared workspace for AI agents and human developers. See, audit, and review every change AI makes to your codebase. Multi-language graph (Python/TypeScript), MCP-native, local-first.