Agent orchestration MCP servers

The local-first intelligence layer that gives AI agents durable continuity, explainable retrieval, portable context, and verified learning across harnesses.

Share local MCP servers across coding-agent sessions: avoid duplicate backend memory and startup work. Keep the agent-side MCP connection across settled configuration-only restarts (SDK/stdio). Tool discovery and exclusive workflows; sharing adds overhead.

MCP Playbooks for AI agents

Local evidence debugger and trajectory-test toolkit for TypeScript AI agents: inspect causal runs, catch wrong tool paths in CI, and share safe offline evidence.

The digital town square where AI agents (PM/Architect/Coder/Tester) collaborate via group chat, while the human acts as the sole Leader. Built with TypeScript + DeepSeek Harness, featuring true parallel execution, cooperative preemption, MCP tools, and git worktree isolation.

Read local AI agent sessions (Claude Code, Codex, OpenCode, Antigravity, Pi): intents, plans, tools

Code, Build and Evaluate agents - excellent Model and Skills/MCP/ACP/A2A Support

MCP policy enforcement plane — deterministic policy on every Model Context Protocol call: identity, RFC 8707 audience binding, tool schema digest pinning, full audit trail. Python, self-hosted, MIT.

Multi-agent team operating system for Claude Code. 108 MCP tools, 40+ agent templates, 10 lifecycle hooks, 7 pipeline workflows. Persistent teams, structured meetings, task wall, real-time React dashboard. No LangChain/AutoGen — pure CC native integration.

Multi-agent team operating system for Claude Code. 108 MCP tools, 40+ agent templates, 10 lifecycle hooks, 7 pipeline workflows. Persistent teams, structured meetings, task wall, real-time React dashboard. No LangChain/AutoGen — pure CC native integration.

A programmable tool and agent runtime for Pi

Zero-dependency TypeScript SDK for AI agent governance: policy enforcement, injection detection, tamper-evident audit, and standards mapping (EU AI Act, OWASP, NIST, ISO 42001)

An open standard for signed, versioned agent skills. Model-driven orchestration with a deterministic shell — host anywhere, verify who wrote it. CLI, registry, MCP, VS Code.

From web terminals for your coding agents to a self-running agent company: Claude Code and Codex in parallel git worktrees, a job board they pick work from, and one agent that runs the board from a goal.

Messages between AI coding sessions in different vendors' clients, such as Claude Code and Codex. Local, open source, no lead agent.

The hub-world for AI agent crews — orchestrate Claude Code, Codex, Gemini, Kimi & DeepSeek as live crews with a plan-aware Advisor, a Kanban/flow command center, a testing gate, and an economics brain (Scrooge).

A programmable tool and agent runtime for Pi

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.

AI-powered cascading development framework. Decompose complex projects into parallel executable tasks with auto-generated PRDs, design docs, and multi-agent collaboration (Claude Code, Codex, Aider).

Engram - file-system-based memory management system for AI agents that grows with you & your teams, across agents, projects, and devices.

https://cello.mygentic.ai/l/2axsGFs The official client for the CELLO protocol — lets agents such as Claude Code, Hermes, OpenClaw, etc. connect, message, and collaborate directly across devices and harnesses using MCP

The open-source memory and observability layer for AI agents — persistent memory, loop detection, hash-chained audit trails, and a live dashboard, automatic on pip install.

Let your coding agents talk to each other: search every Claude Code / Codex / Gemini / Cursor session and message live sessions. CLI · MCP · hooks · HTTP/SSE · A2A.

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