“building AI agents”

TypeScript toolkit for AI apps and agents with a unified provider API, streaming, UI hooks and a wrapper for running established agent harnesses.

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

Opinionated agent harness on LangGraph with sub-agents, filesystem access, context management, persistent memory and approval of tool calls.

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

Open-source toolkit for building, evaluating and deploying agents in Python, TypeScript, Go, Java and Kotlin, tuned for Gemini but model-agnostic.

Open-source agent harness for stateful agents whose memory persists and improves with use, with a terminal UI, app server and TypeScript SDK.

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

Framework for AI agents and multi-agent networks where a router picks which agent runs, with tools and MCP support.

JavaScript and TypeScript framework of interoperable components for building LLM apps and agents, with LangGraph.js and Deep Agents above it.

SDK for building Microsoft Teams apps and AI agents in TypeScript, C# and Python, with a CLI that scaffolds new agents.

Workflow SDK: Build durable, reliable, and observable apps and AI Agents in TypeScript

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