Harnesses & SDKs

Open-source Python and TypeScript SDK for model-driven agents, with tools, MCP, multi-agent patterns and streaming.

Open-source agent harness that runs the model loop for you, with MCP tools, skills, sandboxing, approvals and a chat UI.

Go framework for LLM applications with chat-model agents, multi-agent coordination, graph workflows and human-in-the-loop resume.

Open-source Python framework for multi-agent systems: agent societies, memory, RAG, code interpreters, synthetic data and large-scale simulation.

TypeScript SDK for persistent AI agents on Cloudflare Durable Objects, with state sync, scheduling and MCP support.

CLI-first Python agent framework and coding agent with MCP, A2A and Agent Skills support, live streaming and human input.

Policy enforcement, identity, sandboxing and reliability tooling for autonomous AI agents, installable with one pip command.

Open-source framework that builds, evaluates and self-improves multi-agent LLM workflows from a goal.

Python framework that models an application as a state machine, with a trace UI and persisted state.

Python framework for LLM apps built from collaborating agents that hold conversation state, tools and vector-store memory.

TypeScript agent framework with persistent cognitive memory, multi-agent orchestration and one dispatch interface across 13 LLM providers.

Python library for autonomous agents that run scheduled tasks and exchange messages on the Fetch.ai network.

Python runtime and framework for long-running agents, with durable sessions, approvals, spend caps and multi-agent collaboration.

Code-first Java toolkit for building and testing AI agents, with multi-agent hierarchies, a dev UI and Maven packages.

Python multi-agent framework with PEER and DOE collaboration patterns and configurable LLM vendors such as Qwen, DeepSeek and OpenAI.

Open agent harness for AI applications, with a YAML-configured coding agent, sessions, tools, MCP support and a CLI.

Python agent framework for OpenAI-compatible agents with tools, memory, MCP connections, multi-agent collaboration and workflows.

Python platform that gives agents a cryptographic identity, A2A communication and x402 payment requirements behind one bindufy() call.

Framework for AI agents and multi-agent networks where a router picks which agent runs, with tools and MCP support.

Low-code Python framework for YAML-defined agents and multi-agent Cogs, with personas, prompt templates and memory nodes.

JavaScript framework for multi-agent teams whose tasks move across a Kanban-style board you can watch.

Python framework for autonomous agents that work in a sandboxed workspace, and task agents with tools and MCP support.

Python framework for MCP-based agents with composable workflow patterns, MCP server creation and Temporal-backed durable execution.

Go framework for multimodal AI agents with models, tools, memory, middleware, chains and structured output.