Harnesses & SDKs

Open-source agent harness from LangChain for building agents with code, with LangSmith for testing and monitoring.

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

Open-source Python framework from deepset for modular pipelines and agent workflows covering retrieval, tool use and generation.

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

TypeScript platform to build and deploy long-running AI agents and workflows with retries, queues and human approval steps.

Browser DOCX editor and document engine built on OOXML, with a Document API that agents reach through SDKs, a CLI and an MCP server.

Java library with one API over LLM providers and vector stores, plus tools, RAG and integrations for Quarkus and Spring Boot.

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.

Rails framework for building AI agents as controllers, with provider gems for OpenAI, Anthropic, Ollama and more.

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

Browser infrastructure for AI agents: local and cloud Playwright-based browser sessions, scraping and deployable browser functions.

Java application framework from the Spring project with portable chat and embedding APIs, tool calling and vector stores.

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.

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

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

Python SDK for TimeGPT, a time series foundation model for forecasting and anomaly detection.

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

Python SDK for tracing agents and scoring their traces with prompt-based judges, to find failures in production.

JVM framework for agentic flows that plan toward goals, mixing LLM calls with code and domain models, usable from Kotlin or Java.

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