Build AI agents that actually do things. Synapse is an open-source platform for creating, connecting, and orchestrating AI agents powered by any LLM — local, cloud or CLIs.

A modular Python framework implementing the Model Context Protocol (MCP). It features a standardized client-server architecture over StdIO, integrating LLMs with external tools, real-time weather data fetching, and an advanced RAG (Retrieval-Augmented Generation) system.

SkillsVote: Lifecycle Governance of Agent Skills from Collection, Recommendation to Evolution

Memory service, SDK, CLI, and plugins for agent recall and writeback.

Give AI agents ambitious work without losing the plot. nac is an open-source harness for long-running tasks, using a central orchestrator, threads, and structured episodes to stay aligned with your intent.

Let any AI coding tool — Claude Code, Cursor, Codex — drive your real Chrome. One-prompt setup, muscle memory, local-first.

a recursive self-improving harness designed to help your agents (and future iterations of those agents) succeed on any task

Durable, searchable memory of your past agent sessions.

Build autonomous AI agents in Python.

Robinhood Agentic Trading agent — a fully automated AI trading bot placing real orders through Robinhood's Agentic Trading MCP, under mechanical, auditable risk rules the model cannot override. Able to run unattended on Claude Pro, no metered API spend. Not financial advice.

Minimalist AI agent that fixes itself when things break.

Every past session, subagent, and workflow -- queryable by your agent, browsable by you

Multi-agent research automation framework for LLM agents, with adversarial lab meetings, paper-review rounds, auditable Markdown workflows, an autonomous runtime watchdog, and a pixel-art web dashboard.

Use cultivar to test your Agent Skills, run them in sandboxes, and across different agents.

"Vibe-Trading: Your Personal Trading Agent"

250+ real-world TypeScript AI projects: workflows, agents, and multi-agent systems with production-ready architecture, not chatbot demos.

The theory of LLM wikis, running as one. A framework for agent-operated knowledge: typed, linked, review-gated markdown your agents execute.

Open-source cross-agent memory layer for coding agents via MCP. Compatible with Claude Code, Codex, Cursor, Windsurf, Gemini CLI, Antigravity, OpenClaw, Hermes Agent, Oh-my-Pi, Pi, Copilot, Kiro, OpenCode, and Trae.

Touhou-inspired Agent Skills: distinct, testable, composable problem-solving workflows.

Self-hosted agent OS with skills, workflows, MCP, and second brain storage.

Open-source AI coding agent and agent runtime: one binary, any model, MCP-native. Runs in terminal, CI, or as a daemon.

A framework for discovering, compiling, and validating reusable skills for scientific agents.

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.

Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.