A Low-Code MCP Framework for Building Complex and Innovative RAG Pipelines

🦖 Serverless AI Agent Framework with Geo-distributed Edge AI Infra.

Build autonomous AI agents in Python.

A Python library for building AI agents that leverage the full power of Google Antigravity.

The Context Layer for unstructured data: typed, versioned datasets over S3, GCS, Azure

Toward Skill-Native LLMs: Skill Entropy for Benchmarking and Training Long-Horizon Reasoning

Open source version of Claude Managed Agents. Fastest way to build and deploy reliable AI agents, MCP tools and agent-to-agent.

AG2 (formerly AutoGen): The Open-Source AgentOS.Join us at: https://discord.gg/sNGSwQME3x

This package implements Agent Skills (https://agentskills.io) support with progressive disclosure for Pydantic AI. Supports filesystem and programmatic skills.

Universal memory runtime for AI agents

The Enterprise-Grade Multi-Agent Orchestration Framework. Website: https://swarms.ai

Code, Build and Evaluate agents - excellent Model and Skills/MCP/ACP/A2A Support

Open-World Self-Evolution for LLM Agents — agents that build both their skills and their own verification signals from scratch, with no target-task supervision. (Code coming soon.)

Transparent and Efficient Financial Analysis

A bio-inspired cognitive memory engine — a new paradigm for Graph RAG.

🌐Web Agent Protocol (WAP) - Record and replay user interactions in the browser with MCP support

Connect AI agents across any network — zero config, encrypted, skill-based routing

Open-source AI assistant ecosystem with MCP integrations, multimodal workflows, IoT support, and cross-platform voice interaction.

One portable memory layer for every AI agent: local-first, Markdown-native, user-owned, and self-evolving across apps, tools, and workflows.

Open Brain — The infrastructure layer for your thinking. One database, one AI gateway, one chat channel — any AI plugs in. No middleware, no SaaS.

A selective learning and memory substrate for agentic systems — typed, revisable, decayable memory with competence learning and trust-aware retrieval.

🕷️ An adaptive Web Scraping framework that handles everything from a single request to a full-scale crawl!

A modular Python framework implementing the Model Context Protocol (MCP). It features a standardized client-server architecture over StdIO, integrating LLMs with external tools, real-time weather data fetching, and an advanced RAG (Retrieval-Augmented Generation) system.

Next-gen AI memory layer with importance scoring, temporal decay, hierarchical memory, and YMYL prioritization