Harnesses & SDKs

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

DSPy-style toolkit for typed LLM signatures, agents and flows, TypeScript-first with Python, Java, C++, Go and Rust libraries.

Python framework for multi-agent teams and workflows, with a CLI and Docker, MCP and A2A deployment options.

Low-level Python orchestration framework for long-running stateful agents, with durable execution, human review points and short- and long-term memory.

Python and TypeScript framework for multi-agent systems, with MCP and A2A interop, YAML orchestration and OpenTelemetry tracing.

Opinionated agent harness on LangGraph with sub-agents, filesystem access, context management, persistent memory and approval of tool calls.

Typed Python SDK for building agents with swappable model providers, plus optional capabilities for memory, sub-agents, planning and durable execution.

Open-source toolkit for building, evaluating and deploying agents in Python, TypeScript, Go, Java and Kotlin, tuned for Gemini but model-agnostic.

Open-source Python framework for multi-agent workflows, with role-based Crews and event-driven Flows.

Open-source framework that routes each user query to one of several AI agents, with Python, TypeScript and Swift runtimes.

Python framework and runtime for building agents, serving them over a REST API and MCP server, and managing them from a web control plane.

Open-source Python framework for real-time voice and multimodal agents, built from composable pipelines with handoffs between specialist agents.

Python agent framework from Alibaba that lets the model drive tool use, with team pipelines, MCP, agent skills, A2A, memory and tracing.

Python SDK for multi-agent workflows with handoffs, guardrails, sessions and built-in tracing, usable with OpenAI and other LLMs.

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

Open-source Python framework for AI agents that cooperate on tasks, with human-in-the-loop workflows and multi-agent patterns.

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.

Python framework for generative AI agents, pipelines and parallel workflows, with RAG engines, tools, memory and swappable drivers.

All-in-one Python AI framework for embeddings-based semantic search, LLM pipelines, workflows and agents.

Kubernetes-native framework and runtime for building and running AI agents as Kubernetes custom resources.

Lightweight Python framework for composing AI agents and tools as small, typed pieces built on Instructor and Pydantic.

Python framework for structured LLM outputs and agentic workflows built from tasks, agents and threads.

Python framework for orchestrating multiple LLM agents in sequential, concurrent, hierarchical and graph-based workflows.