File-based message queue for local agent-to-agent communication (Maildir-style)

The design layer for agentic AI — design context, interface checks, and verification for coding agents.

Structural memory for AI coding agents. Bi-temporal graph, MCP-native, zero LLM calls. Cursor · Claude Code · Codex · DeepSeek Harness · Hermes · VS Code · Windsurf.

Persistent Context Across Sessions for Every Agent – Captures everything your agent does during sessions, compresses it with AI, and injects relevant context back into future sessions. Works with Claude Code, OpenClaw, Codex, Gemini, Hermes, Copilot, OpenCode + More

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

Git-native memory for coding agents. Repo memory before the diff.

Agent-managed GitHub merge queue for Codex, Claude Code, Cursor, and MCP clients

Agent-assisted maintainership and development framework for Apache projects — Triage, Mentoring, Drafting (agent-authored fixes with human review), and Pairing (developer-side dev-cycle) skills shipping; Agentic Autonomous (auto-merge) on the roadmap.

The IM for agents. Shared Agent Context & Memory, supervised execution, and cross-agent audit across AI providers.

Workflow orchestration for AI coding agent swarms, from task to merged PR.

IJFW — It Just F*cking Works. Ferrox Labs' local-first infrastructure for AI coding agents: shared memory, smart routing, multi-AI cross-audits, disciplined workflow.

One memory shared by Claude Code, Codex, Cursor, Copilot CLI, OpenClaw and 20 more coding agents, built from the session history already on disk. A fix found in one agent comes back in any of them, including months of sessions from before you installed it. No LLM, no embeddings, one local Go binary.

Turn your team's AI coding sessions, GitHub code, and docs into one shared, searchable memory — a self-hosted git truth store you query right from your editor over 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.

Ask Codex, Gemini, Grok, and 400+ OpenRouter models (Qwen, Kimi, DeepSeek) for second opinions or arbiter-mediated consensus. One MCP server for Claude Code, Codex, Cursor, Kiro, OpenCode. Measures which models earn their seat.

The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.

Cezar is a parallel coding agents orchestrator. Type a task, pick a workflow and an agent — Claude Code, Codex or OpenCode, or a mix of them per step — and watch it work live: steps, tool calls ... or: fire and forget, PR will land and issue will be fixed. Run ot locally (Linux, Mac, WSL2) or on VPS!

Graph-based long-term memory skill for AI (LLM) coding agents — faster context, fewer tokens, safer refactors

Full AI context and content layer for coding agents over one MCP server — tree-sitter code-map, document RAG, shared memory, multi-agent comms, web crawl, git history + blame. 300+ languages, 10+ agent harnesses, pure Rust.

Uses only the subcriptions you have. Control different agents with agents. Free, local, workspace for AI agents. Let one agent (Claude Code, Codex, Hermes, DeepSeek, Kimi, ...) spawn and drive others over MCP. No API keys, no changes to your Agent.md or Claude.md. TUI, Web UI, CLI, MCP in one package.

An agentic skills framework & software development methodology that works.

Measure token savings per AI coding agent, optimize context, and share a live local knowledge graph across 16 CLI clients.

Gentle-AI configures the AI coding agents you already use: Claude Code, Cursor, OpenCode, Codex, Pi, and more. Choose persistent memory, Spec-Driven Development, curated skills, MCP servers, personas, and optional bounded review. Open source, no agent lock-in.

Professional context and harness engineering for Claude Code and OpenAI Codex. Build production-grade software with spec-driven development, TDD, persistent memory, quality gates, code intelligence, human oversight, and end-to-end verification.