Everything in the catalog

Quarkus extensions that connect LangChain4j to Quarkus apps, with declarative AI services and LLM, tool and embedding support.

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

TypeScript agent framework on a Rust runtime, where runs are checkpointed, replayed with zero LLM calls and resumed after a crash.

Official Python implementation of the Universal Tool Calling Protocol, calling HTTP, CLI, MCP and text-file tools through plugins.

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.

C# framework on .NET for building multi-agent AI bots with plugins, RAG, MCP integration and a built-in admin UI.

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.

Python framework for backtesting and running trading strategies written as Python rules or AI agents, across brokers.

Modular Python agent framework with a tool-calling loop, context management, retrieval, persistent memory and MCP tools.

Visualization language and MCP server that lets AI agents create charts from editable chart specs.

Python and TypeScript toolkit for calling any frontier LLM through one interface, with tools, structured output and tracing.

Python library and CLI for building agents that run on IBM watsonx Orchestrate, with a local Developer Edition for testing.

Java library for stateful, multi-agent LLM applications built as cyclical graphs, designed to work with langchain4j and Spring AI.

Python and TypeScript SDK and REST Agent Server for building agents that work with code in local or containerized workspaces.

Go framework for multi-agent systems with graph workflows, tools, session memory, MCP, A2A, AG-UI and OpenTelemetry.

Python framework for LLM agents that run as durable Dapr workflows, with retries, Kubernetes deployment and human-in-the-loop hooks.

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.

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

Open-source LLM function calling framework for AI agents, with serverless LLM tools and geo-distributed infrastructure.