#multi-agent

Local execution trees for TypeScript AI agents. agent-inspect helps you understand what happened inside an AI agent run — locally. It turns manual steps, tool calls, LLM calls, structured logs, failures, durations, and run metadata into readable execution trees you can inspect from the terminal. It is built for TypeScript/Node.js developers..

Shared memory for your team's coding agents

Collaboration infrastructure for AI coding agents | AI 编程代理的协作基础设施

The .NET library to build AI agents with 30+ built-in connectors.

Define AI agent roles in YAML and run them anywhere: CLI, API server, or autonomous daemon

The collaboration layer for your AI workforce. Run a team of AI agents that coordinate over email, share memory, and get better with every task.

Self-hostable AI agents you can actually leave running — durable crash-resume, governed autonomy, seccomp sandbox, offline-replayable workflows, CI-native eval. Async-Python, YAML-config, multi-provider (OpenAI/Anthropic/Cloudflare), MIT.

A Go framework for the microagents architecture with dynamic discovery — specialized agents and tools that register their capabilities with a shared registry, find each other by logical name at runtime, and coordinate without a central conductor.

The open-source software factory — multi-agent fleet management for coding agents

Visible multi-agent CLI workspace for mixing Codex, Claude, Gemini, Kimi, Qwen, Cursor, Copilot, Pi, OpenCode, and other AI coding agents

Open-source security-first runtime for AI agents that learn and act across sessions.

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Multi-agent orchestration plugin for OpenCode. 10 configurable model slots, 30 hooks, memory search, LSP diagnostics, agent-browser integration, completion controller, auto dream/distill memory consolidation. One prompt to set up and run.

Self-hosted browser terminal manager for AI coding agents. Control Claude Code, Codex, Gemini, and shell sessions from your phone or browser over Tailscale.

File-based kanban board for autonomous agentic loop. CLI and TUI for multi-agent workflows. Skills included.

Neutral control plane for coding-agent fleets: claims, roles, mailbox reliability, receipts, audit, federation, dead-letter visibility, sandbox receipts, and cross-agent coordination.

All-in-one workspace for AI coding agents

🛠️ The meta-harness for AI agents — scaffold your own focused, branded agent harness with its own npx CLI, MCP server, memory, learning loop, and witness-signed releases. Works with Claude Code, Codex, pi.dev, Hermes, OpenClaw, and RVM (hardware-isolated sandbox).

AI partners for every person: multi-user, multi-agent memory, trusted tools, schedules, sandboxed workspaces, and chat.

Production-grade Go SDK for building AI agents with long-term memory, knowledge retrieval, and voice — runnable as a library, a daemon, or a real-time pipeline.

Autopus-ADK is of the agents, by the agents. for the agents. Multi-model orchestration (consensus/pipeline/debate/fastest). Architecture-as-Code, Lore decision tracking, SPEC/EARS engine.

The semantic layer for spatial computing and AI agents — write once, run as VR, robotics, web, or game.

助力搭建你的数字 AI 员工军团 — 多 Agent 一行命令组网协作。Claude Code / Claude Agent SDK / Codex / Grok Build 4 runtime + 8+ 家 LLM（Anthropic / OpenAI / xAI / MiniMax / DeepSeek / GLM / Kimi / 书生 / 小米 MiMo），自带 Web Dashboard，Apache 2.0 开源。

Local-first control plane for AI coding agents: repo memory, verification, sessions, and dynamic workflows.

Local-first AI assistant for long-running goals, automations, workflows, and multi-surface chat.

Local, human-in-the-loop message bus for coordinating parallel AI coding-agent sessions on one machine

Multi-agent orchestration via MCP. Persistent memory, inter-agent messaging, goal cascade, context budget pruning. One binary, zero config.

An opinionated full-stack agent harness with native memories, long running tasks, and multi-agent relay

Multi-Agent Framework

A minimal, composable Go library for building AI agent applications.