Awesome Agent Harness

🌊 The original agent meta-harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, RAG integration, and native Claude Code / Codex / Hermes and many more Integrated

Multi-harness agentic plugin marketplace for Claude Code, Codex CLI, Cursor, OpenCode, GitHub Copilot, and Gemini CLI

Glamourous agentic coding for all 💘

Hindsight: Agent Memory That Learns

An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.

Python SDK for Agent AI Observability, Monitoring and Evaluation Framework. Includes features like agent, llm and tools tracing, debugging multi-agentic system, self-hosted dashboard and advanced analytics with timeline and execution graph view

Security scanner for AI agent skills. Detect vulnerabilities, malicious patterns, security risks, prompt injection, data exfiltration, and supply-chain risks in Claude Code, Codex, and MCP skills before you install them.

Eigent: The Open Source Cowork Desktop - Local and Free Alternative to Claude Cowork and Codex

Harness engineering beginner tutorial, from 0 to 1

Code Editor for the AI Agents Era - Run an army of Claude Code, Codex, etc. on your machine

One portable memory layer for every AI agent: local-first, Markdown-native, user-owned, and self-evolving across apps, tools, and workflows.

A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET.

Agent Reinforcement Trainer: train multi-step agents for real-world tasks using GRPO. Give your agents on-the-job training. Reinforcement learning for Qwen3.6, GPT-OSS, Llama, and more!

Flexible and powerful framework for managing multiple AI agents and handling complex conversations

✨ Build AI agents and web apps — with a single binary.

Build an agent harness and control it end-to-end. Open-source SDK for production AI agents in Python & TypeScript - any model, any cloud.

TypeScript AI agent orchestration framework with dynamic workflows. Describe the goal, not the graph: a coordinator plans the task DAG at runtime and runs it on any LLM (Claude, ChatGPT, Gemini, DeepSeek, or local models).

The 100 line AI agent that solves GitHub issues or helps you in your command line. Radically simple, no huge configs, no giant monorepo—but scores >74% on SWE-bench verified!

A model-driven approach to building AI agents in just a few lines of code.

Nexent is a zero-code platform for auto-generating production-grade AI agents using Harness Engineering principles — unified tools, skills, memory, and orchestration with built-in constraints, feedback loops, and control planes.

Agenta is a workspace where you and your team build agents and automations.

Agent framework for the JVM. Pronounced Em-BAY-bel /ɛmˈbeɪbəl/

Real-time transport layer for Java AI agents. Build once with @Agent — deliver over WebSocket, SSE, gRPC, and WebTransport/HTTP3. Talk MCP, A2A and AG-UI.

Amazon Bedrock Agentcore accelerates AI agents into production with the scale, reliability, and security, critical to real-world deployment.

The Continuous-Improvement Stack for Agents. Our environment data and evals power agent improvement and monitoring.

CheetahClaws: A Fast and Easy-to-Use Agent Harness Infrastructure for Long-Horizon, Multi-Model, and Tool-Using AI Systems

Open-source benchmark for browser AI agents on daily tasks.

The action firewall for AI agents. Enforce policy and human approval before risky tool calls, shell commands, workflows, and production changes, with auditable evidence.

An in-the-wild benchmark for AI agents in the OpenClaw Environment.

Deterministic safety solutions for probabilistic AI agents

Benchmark for comparing agent harnesses on everyday online tasks — fixes the base model, varies the harness. Sister project of ClawBench, same scoring pipeline.