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.

Multi-harness control plane for Claude Code, Codex, Cursor, and OpenCode: quota-aware rotation across multiple Claude/Codex subscriptions, shared thread context, and cross-model review.

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.

The fastest workflow for every AI coding agent. Live status, quick prompts, worktrees, and diff review from one tmux TUI.

Multi-model AI code review server using OpenRouter - get diverse perspectives from multiple LLMs in parallel

Your AI can write the UI. This makes sure it writes your UI. A deterministic scanner scores your design system 0-100 against 34 public repos, writes rules for Claude, Cursor, Copilot and Windsurf with --apply, and runs as a local MCP server with --mcp.

Reverse engineer anything with agents, from app behavior down to native binaries.

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

Ghidra MCP Server — 200+ MCP tools for AI-powered reverse engineering. GUI plugin + headless server, lazy tool loading, convention enforcement, batch operations, Ghidra Server integration, and Docker deployment.

All-in-One malware analysis tool.

Deterministic, local-first memory and guardrails for AI coding agents with no LLM in the hot path.

Official SonarQube MCP Server for code quality and security in AI agents

MCP server that runs CLI AI coding agents (Claude Code, Codex, opencode, Antigravity) as sub-agents from any MCP client, with background sessions and structured code review

Local code intelligence MCP server and CLI for AI coding agents

Enables AI agents to perform read-only static analysis of Node.js backend projects, detecting database query anti-patterns, async bottlenecks, connection pooling mistakes, and dependency hygiene issues while returning structured evidence-backed findings.

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