“agent memory”

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

Lightweight Python framework for LLM agents built as PyTorch-style layers, with agent memory kept as session state.

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

Python agent framework for OpenAI-compatible agents with tools, memory, MCP connections, multi-agent collaboration and workflows.

Open-source Python and TypeScript SDK for model-driven agents, with tools, MCP, multi-agent patterns and streaming.

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

Multi-interface agent framework with tools, memory and MCP, serving agents through Telegram, Discord, Twitter, Farcaster and a REST API.

Low-code Python framework for YAML-defined agents and multi-agent Cogs, with personas, prompt templates and memory nodes.

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

Open-source Python framework for multi-agent systems: agent societies, memory, RAG, code interpreters, synthetic data and large-scale simulation.

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.

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

CLI-first Python agent framework and coding agent with MCP, A2A and Agent Skills support, live streaming and human input.

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

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

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

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.

Python framework for real-time voice and vision agents that process video with pluggable models and processors over WebRTC.

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

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

Open-source framework that builds, evaluates and self-improves multi-agent LLM workflows from a goal.

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