Harnesses & SDKs

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

Rust framework with an agent harness, typed task graphs and streaming indexing and RAG pipelines for LLM applications.

XState library where agent logic is a state machine, so a model can only pick events the machine allows.

Minimal Python graph framework of about 100 lines for LLM agents, workflows, RAG and map-reduce pipelines.

Python framework for durable AI agents built as dataflows that resume after crashes, retry safely and record each step.

Python framework for customer-facing conversational agents that narrows the prompt context each turn using rules, knowledge and tools you define.

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 library for steering language models by constraining output with regex and grammars and mixing control flow with generation.

Typed Python toolkit for composing classic and agentic retrieval-augmented generation pipelines with pluggable LLMs and stores.

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

PyTorch-style Python framework for multi-agent, multi-session workflows, with a durable production runtime in v2.0.0.

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.

Open-source Python framework for text and voice assistants; the open-source edition is in maintenance mode while Rasa moves to its CALM engine.

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

SDK for building durable, responsive services, including agentic AI services, that cluster automatically and deploy to any infrastructure.

Python framework for LLM applications built on Qwen models, with function calling, MCP, a code interpreter and RAG options.

Python runtime for agent apps with tool sandboxing and streaming agent APIs; archived, with features moved to AgentScope 2.0.

SDK for building agents in C#, JavaScript and Python that run on channels such as Microsoft Teams and Microsoft 365 Copilot.

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

Python framework for data labeling agents that learn skills from a ground-truth dataset through iterative feedback.

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

Experimental Python library that teaches agent handoffs on the Chat Completions API; OpenAI now points users to its Agents SDK.