v0.12.3 · Apache-2.0
Agent-native TypeScript framework for building MCP servers. Build tools, not infrastructure. Declarative definitions with auth, multi-backend storage, OpenTelemetry, and first-class support for Bun/Node/Cloudflare Workers.
v2.0.4 · MIT
The fullstack MCP framework to develop MCP Apps for ChatGPT / Claude & MCP Servers for AI Agents.
v1.9.40 · MIT
Open-source self-hosted AI agent runtime and multi-agent framework for autonomous agent swarms. Agent memory, MCP tools, schedules, delegation, and 23+ LLM providers (Claude, GPT, Gemini, OpenRouter, Ollama). A practical Claude Code and LangChain alternative.
v0.0.1 · MIT
The fullstack TypeScript framework for MCP and APIs — write one action, serve HTTP, WebSocket, CLI, background tasks, and MCP tools.
— · MIT
MCP Server Framework and Tool Development library for building custom capabilities into agents.
— · Apache-2.0
🔥 Java enterprise application development framework for full scenario: Restrained, Efficient, Open, Ecologicalll!!! 700% higher concurrency 50% memory savings Startup is 10 times faster. Packing 90% smaller; Compatible with java8 ~ java26; Supports LTS. (Replaceable spring)
— · Apache-2.0
A lightweight, modular Java application framework for web and CLI development, designed for AI integration and plugin-based architecture. Enabling developers to create robust solutions with ease for building efficient and scalable applications.
— · Apache-2.0
Production-Ready MCP Server Framework • Build, deploy & scale secure AI agent infrastructure • Includes Auth, Observability, Debugger, Telemetry & Runtime • Run real-world MCPs powering AI Agents
v4.0.3 · Apache-2.0
Trigger.dev – build and deploy fully‑managed AI agents and workflows
v0.3.7 · Apache-2.0
Local-first AI agent runtime with sandboxed sessions, MCP tools, memory, credentials, audit/replay, and a built-in console. Run OpenAI, Anthropic, MiniMax, DeepSeek V4, and OpenAI-compatible models on your infrastructure.
v3.38.20 · MIT
🌊 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
v0.1.0 · MIT
MetaHarness — mint a custom AI agent harness from any repo. Browser Studio + `npx metaharness` CLI. Runs on Claude Code, Codex, pi.dev, Hermes, OpenClaw, RVM, Prime Agent.
v3.45.0 · MIT
Multi-Agent + Automation: Workflows, Automation, Self-Improving Agents
v0.1.0 · MIT
🛠️ 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).
v2026.8.20 · MIT
Deployment tool and support utility for AI context. Copies agents, skills, commands, rules, and behaviors into the paths each AI platform reads (Claude Code, Codex, Copilot, Cursor, Warp, OpenClaw, and 6 more) so one source of truth works across 10 platfo
v0.88.3 · no license
AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents
— · Apache-2.0
Code, Build and Evaluate agents - excellent Model and Skills/MCP/ACP/A2A Support
v0.1.0 · no license
Create AI Agents in a No-Code Visual Builder or TypeScript SDK with full 2-way sync. For shipping AI assistants and multi-agent AI workflows.
v5.27.3 · MIT
🛡️ The approval and policy layer for AI agents. Intercept risky actions before they run, block them, or approve them remotely.
— · AGPL-3.0
A Plugin-Based Multi-Agent System for In-Editor Academic Writing, Review, and Editing
— · Apache-2.0
Shared Single-file memory layer for all your agents, sub mili-second RAG over text, photo and video on Apple Silicon.. No Server. No API. One File. Pure Swift
— · no license
Adversary simulation and Red teaming platform with AI
— · Apache-2.0
Self-hosted AI agent harness in a single Go binary — writes, sandbox-tests and repairs its own tools, and lets Claude Code, Codex and any MCP client build and share them.
— · MIT
MCP Toolkit for Flutter AI Agent Driven Development (MCP/CLI + custom client side tools) - via closed feedback loop (visual & semantic snapshot) and high client side customization adaptable for any Flutter app. Nowadays it is often called as agentic harness.