“Agent memory”

Go framework for AI agents with memory, tool execution, MCP, agent skills, multi-agent patterns and evaluation.

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.

Rust multi-agent framework with typed tool calling, sliding-window memory, pluggable LLM backends and OpenTelemetry tracing.

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

Typed Python SDK for building agents with swappable model providers, plus optional capabilities for memory, sub-agents, planning and durable execution.

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

Lightweight Python agent framework for long-running tasks, with skills, sub-agents, A2A and ACP servers, and CLI, TUI and web front ends.

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

Open-source framework that routes each user query to one of several AI agents, with Python, TypeScript and Swift runtimes.

Java framework for distributed, long-running agents with typed event streams, permission gating, middleware and subagents.

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

AI application runtime framework for backends with structured outputs, observable actions, MCP capabilities and recoverable workflows.

Python interface for running and evaluating agents from several frameworks, with OpenTelemetry traces; now in soft deprecation.

Java runtime for AI agents that streams tokens and tool events over WebSocket, SSE or gRPC, with human approvals.

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

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

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

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

Python framework and runtime for building agents, serving them over a REST API and MCP server, and managing them from a web control plane.

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

Python framework for generative AI agents, pipelines and parallel workflows, with RAG engines, tools, memory and swappable drivers.

Python framework for agents that discover MCP tools by themselves, with optional memory, guardrails, cache and tracing.

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