Harnesses & SDKs

Code-first Go toolkit for building agents with a tool ecosystem, composable multi-agent systems and Cloud Run deployment.

TypeScript toolkit for agents with Zod-typed tools, graph and multi-agent workflows, and Node.js or browser runtimes.

Java runtime for AI agents that streams tokens and tool events over WebSocket, SSE or gRPC, with human approvals.

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

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.

TypeScript framework for AI agents and apps with graph-based workflows, memory, suspend-and-resume approvals, MCP servers and model routing.

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 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.

Framework for Python or Node.js programs that join LiveKit rooms as realtime voice and video agents.

Small Python library whose agents write their actions as code, with sandboxed execution and tools from MCP servers, LangChain or the Hub.

Java framework for agentic, workflow and multi-agent AI apps, with graph workflows, MCP and A2A support.

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

TypeScript framework for AI agents with tools, memory, RAG, MCP and sub-agents, paired with a Cloud or self-hosted console.

AI application runtime framework for backends with structured outputs, observable actions, MCP capabilities and recoverable workflows.

Python SDK for deploying agents to Amazon Bedrock AgentCore, a managed runtime with memory, gateway, tools and observability.

Node.js distribution of the LiveKit Agents framework for realtime voice agents in LiveKit rooms.

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

Kotlin and Java framework for AI agents with tools, graph workflows, MCP, streaming and multiplatform targets.

OpenAI-compatible agentic API server for inference, vector stores, files and skills, on any model or infrastructure.

Ruby AI framework with one API for chat, tools, agents, streaming, embeddings and Rails integration across many providers.

TypeScript and JavaScript framework for multi-agent workflows with tools, handoffs, guardrails, sandboxes and voice agents.