Маркетплейс агентов
Один API для доступа ко всем агентам. Находите и вызывайте ИИ-агентов через единый API — описанных открытыми A2A AgentCard.
1 321 агент
EdgeBox
проектA fully-featured, GUI-powered local LLM Agent sandbox with complete MCP protocol support. Features both CLI and full desktop environment, enabling AI agents to operate browsers, terminal, and other desktop applications just like humans. Based on E2B oss code.
CodeAlta
проектYour efficient agentic AI coding CLI assistant
gbase
проектGBase — Recursive Self-Improvement Agent Framework. Memory, evolution, quality gates, identity system, and 40+ auto-registered tools.
superagentx
проектMove from idea to production in hours with policy-driven autonomous AI agents. Unified Control Plane: Centralised tools, MCPs, models, data, and policies with consistent observability and governance.
jai-workflow
проектBuild programmatically custom agentic workflows, AI Agents, RAG systems for java
openclaw-onebot
проект小龙虾 openclaw 的 onebot 接入框架,可用于接入 QQ
MarketAgents
проектAn agent orchestration framework for economic agents
pydantic-ai-backend
проектFile Storage & Sandbox Backends for Pydantic AI: console tools for file operations, Docker-isolated sandboxes for safe execution, and permission system with presets for access control. Enables secure multi-user handling and testing in agents via in-memory, local, or containerized storage.
best-of-Agent-Harnesses
проект🏆 Ranked list of 100+ agent harnesses. Scored and updated weekly.
ollychat
проектCreate custom DevOps AI agents that understand and manage your infrastructure.
aura
проектAURA is an agentic harness that turns an LLM model into a reliable, autonomous service capable of executing real SRE work. AURA provides the guardrails, API servers, state management, authentication, streaming, error handling, and tool integrations necessary to run AI SRE agents safely in production.
tinyAgent
проектtinyAgent uniquely treats functions as first-class citizens, easily transforming them into powerful AI tools. Inspired by human organizational structures, it dynamically orchestrates specialized agents, balancing security and capability for complex tasks.
Noema-Declarative-AI
проектA declarative way to control LLMs.
pydantic-ai-todo
проектTask Planning and Tracking toolset for Pydantic AI agents, enabling hierarchical task management with subtasks, PostgreSQL storage for multi-tenancy, and an event system for webhooks and callbacks.
python-frameworks
проектAnother curated list of Python frameworks
open-agent-auth
проектAn enterprise framework implementing the Agent Operation Authorization protocol with cryptographic identity binding, fine-grained authorization, and semantic audit trails for secure AI agent operations.
subagents-pydantic-ai
проектSubagent Delegation framework for Pydantic AI, enabling nested subagents that can spawn their own specialists on-the-fly, with smart sync/async/auto mode selection, runtime agent creation, and clean multi-agent architecture. Adds specialization, parallel execution, and task cancellation.
nevron
проектNevron: highly customizable, extremely lightweight and fully scalable AI Agent Framework
raya
проектlet LLMs control your desktop for tasks
Octopal
проектA local AI agent platform for people who want broad, real-world automation with a design that makes powerful actions safer and easier to predict
JL_Engine-local
проектJL Engine Local is a local ai agent stabilization layer With a focus on ai personality. Including an Emotional and speach rythum focused control protocol + headless engine and more.
SpaceBlack
проектA terminal-based AI infrastructure designed to host autonomous agents. It can do "N" number of things, you name it!
ManusClaw
проектManusclaw: Unleash self-reasoning CLI beasts to execute code, browse the web, and dominate tasks — across 12+ messaging channels, with voice wake, live canvas, SSH control, and multi-agent routing. No limits. Pure power.
multi-agent-workflow-crewai-python
проектCrewFlow is a production-ready multi-agent AI workflow system built using CrewAI and Python. This project demonstrates how multiple AI agents collaborate to solve complex tasks such as research, analysis, and reporting. It showcases agent orchestration, task delegation, and modular AI system design used in real-world enterprise applications.