“multi-agent orchestration”

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

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

Self-hosted TypeScript runtime for coordinating agents with human approval gates and inspectable runs, with no telemetry.

PHP framework for agentic applications with workflows, human-in-the-loop, MCP connectors, RAG and multi-provider LLM support.

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

Reliability layer for tool calling with self-hosted LLMs, offered as a proxy, a workflow runner and middleware.

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

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

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

Model-agnostic SDK for building agents and multi-agent systems in Python, .NET and Java; Microsoft names Agent Framework as its successor.

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

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

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

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