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awesome-agent-collaborate-tools

A curated list of tools for AI agent-to-agent communication, coordination, and collaboration
https://github.com/masstensor/awesome-agent-collaborate-tools

Last synced: 5 days ago
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  • Communication Protocols

    • A2A (Agent-to-Agent Protocol) - Open protocol by Google (donated to Linux Foundation, June 2025) for peer-to-peer agent coordination. 150+ supporting organizations. Peer-to-peer agent communication and task delegation via Agent Cards.
    • ACP (Agent Communication Protocol) - RESTful agent interoperability protocol originated by IBM/BeeAI, donated to Linux Foundation. Enables agents built with different frameworks (LangChain, CrewAI, AutoGen, etc.) to communicate via a standardized API.
    • ANP (Agent Network Protocol) - Decentralized protocol for open agent networks, built on W3C DID standards. Enables agents to discover and interact without centralized coordination.
    • UTCP (Universal Tool Calling Protocol) - Exposes tools to models using the tool's native endpoint rather than requiring an MCP wrapper. Contributed to Linux Foundation alongside ACP.
    • OpenAI Agents SDK — Handoffs - First-class agent-to-agent handoff primitives in OpenAI's Agents SDK. Allows agents to delegate tasks with full context transfer.
    • ACP (Agent Communication Protocol) - RESTful agent interoperability protocol originated by IBM/BeeAI, donated to Linux Foundation. Enables agents built with different frameworks (LangChain, CrewAI, AutoGen, etc.) to communicate via a standardized API.
    • ANP (Agent Network Protocol) - Decentralized protocol for open agent networks, built on W3C DID standards. Enables agents to discover and interact without centralized coordination.

  • Contributing

  • Developer Tools & SDKs

    • BeeAI Framework - IBM's open-source agent framework powering the ACP protocol. Production-ready with tool use, memory, and structured output.
    • FastMCP - The fastest way to build MCP servers in Python. Decorator-based API similar to FastAPI. Used by tens of thousands of MCP server authors. Now part of the official MCP Python SDK.
    • Composio - Managed tool integration platform for AI agents. 250+ pre-built integrations (GitHub, Slack, Notion, etc.) with auth management. Works with LangChain, CrewAI, AutoGen, and any agent framework.
    • Portkey AI Gateway - Open-source AI gateway with fallbacks, retries, load balancing, and request routing across 200+ LLMs. Essential for multi-agent deployments that use multiple model providers.
    • LiteLLM - Unified API for 100+ LLMs. Use the same code to call OpenAI, Anthropic, Gemini, Groq, Ollama. Simplifies multi-agent systems where different agents use different models.
    • instructor - Structured output extraction from LLMs using Pydantic. Critical for agent-to-agent communication with typed message schemas — ensures agents receive parseable, validated data.
    • im-for-agents-python - Python SDK for IM for Agents. Send and receive messages between agents with minimal boilerplate.
    • multi-agent-starter - Starter template for building multi-agent applications with MCP, A2A, and IM for Agents integration out of the box.

  • Examples & Demos

    • Google A2A Samples - Official Google samples for A2A protocol. Best starting point for understanding Agent Cards and task lifecycle.
    • LangGraph Multi-Agent Examples - Official LangGraph examples covering supervisor, hierarchical, and collaborative multi-agent patterns with state management.
    • CrewAI Examples - Official CrewAI examples including trip planner, stock analysis, and game builder crews. Best starting point for role-based multi-agent systems.
    • IM for Agents — 3 curl demo - Minimal demo of agent-to-agent messaging with 3 HTTP calls — no SDK, no framework. Shows the baseline for any cross-framework agent coordination.
    • a2a-examples - Practical examples of A2A protocol agent communication. Covers agent discovery, task delegation, and streaming responses.
    • multi-agent-demo - End-to-end demo of multiple agents collaborating via IM for Agents and MCP. Shows orchestrator + specialist agent pattern.
    • multi-agent-patterns - Common patterns for building multi-agent systems with code examples. Covers pipeline, fan-out, consensus, and critic patterns.
    • AutoGen Examples - Microsoft's reference examples for AutoGen agent patterns including group chat and code execution.

  • Identity & Trust

    • A2A Agent Cards - A2A protocol standard for agent self-description. Agents publish capabilities, authentication requirements, and endpoints in a standardized JSON format. Enables dynamic agent discovery.
    • WIMSE (Workload Identity and Minimal Secrets) - IETF working group standard for workload/agent identity in cloud environments. Combines SPIFFE, OAuth 2.0, and token exchange for agent delegation. First draft published 2025, actively developed 2026.
    • OAuth 2.0 for AI Agents - Using OAuth 2.0 / DPoP for agent-to-agent authorization. Best practice for agents calling APIs or other agents on behalf of users. IETF draft (draft-klrc-aiagent-auth-00) published March 2026.
    • DID (Decentralized Identifiers) - W3C standard for cryptographic agent identity without central authority. Used as the foundation for ANP and decentralized agent networks.

  • Learning Resources

  • Messaging & Notification

    • IM for Agents - Agent-to-agent messaging without MCP. Three HTTP calls and your agents are talking — no SDK, no protocol implementation, no infrastructure setup. Cross-framework: Claude, GPT, Gemini, and local LLMs can all join the same room via REST API. Free tier available.
    • Redis Pub/Sub + Streams - Battle-tested message patterns. Redis Streams provide persistent, consumer-group-based messaging ideal for agent pipelines where replay and backpressure matter.
    • XMTP - Decentralized, end-to-end encrypted messaging protocol. Used for agent-to-agent messaging with cryptographic identity, especially in Web3 agent contexts.
    • IM for Agents - Agent-to-agent messaging without MCP. Three HTTP calls and your agents are talking — no SDK, no protocol implementation, no infrastructure setup. Cross-framework: Claude, GPT, Gemini, and local LLMs can all join the same room via REST API. Free tier available.
    • IM for Agents - Agent-to-agent messaging without MCP. Three HTTP calls and your agents are talking — no SDK, no protocol implementation, no infrastructure setup. Cross-framework: Claude, GPT, Gemini, and local LLMs can all join the same room via REST API. Free tier available.
    • im-agents-mcp - MCP server for IM for Agents. Allows any MCP-compatible agent to send and receive messages from other agents via IM for Agents.
    • Agent Notify Action - GitHub Action for sending notifications from automated agents to humans or other systems. Supports Telegram, Slack, and webhooks.
    • NATS - High-performance, cloud-native messaging system. Subjects and consumer groups make it excellent for agent event streaming and task routing. Supports request-reply patterns common in agent architectures.
    • Redis Pub/Sub + Streams - Battle-tested message patterns. Redis Streams provide persistent, consumer-group-based messaging ideal for agent pipelines where replay and backpressure matter.

  • Multi-Agent Orchestration

    • CrewAI - Role-based multi-agent framework. Agents have roles, goals, and backstories. Simple API, production-ready, 30K+ GitHub stars.
    • LangGraph - Graph-based agent orchestration by LangChain. Fine-grained control over agent state machines. Best for complex branching and human-in-the-loop flows.
    • AutoGen - Microsoft's framework for conversational multi-agent workflows. Strong support for human-in-the-loop, code generation, and group chat patterns.
    • Google ADK (Agent Development Kit) - Google's official SDK for building agents that work with Gemini and A2A protocol. Includes built-in support for multi-agent delegation.
    • Anthropic Agent SDK - Official Anthropic toolkit for building Claude-powered agents with tool use, multi-turn conversations, and agent handoffs.
    • Semantic Kernel - Microsoft's open-source SDK for building AI agents and copilots. Supports agent-to-agent patterns via the Process Framework.
    • Swarms - Production-grade swarm orchestration. Supports hierarchical, sequential, concurrent, and mixture-of-agents patterns. Battle-tested for enterprise deployments.
    • Mastra - TypeScript-first agent framework with memory, tool-calling, workflows, and RAG. Designed for building production AI applications with multi-agent capabilities.
    • smolagents - Hugging Face's minimal, code-centric agent framework. Agents write and execute Python code to achieve goals. Simple integration into multi-agent pipelines.
    • open-multi-agent - Production-grade multi-agent orchestration. Model-agnostic, supports team collaboration, task scheduling, and inter-agent communication with shared memory.
    • PydanticAI - Production-grade agent framework from the Pydantic team. Type-safe tool calling, dependency injection, and structured output. Supports multi-agent orchestration via agent handoff primitives.
    • LlamaIndex Workflows - Event-driven, async multi-agent orchestration built into LlamaIndex. Define agents as workflow steps with typed events — clean model for complex agent DAGs.
    • Dify - Open-source LLM app platform with visual agent builder. Supports multi-agent workflows, tool integration, and knowledge retrieval. 60K+ GitHub stars.
    • Anthropic Agent SDK - Official Anthropic toolkit for building Claude-powered agents with tool use, multi-turn conversations, and agent handoffs.
    • LlamaIndex Workflows - Event-driven, async multi-agent orchestration built into LlamaIndex. Define agents as workflow steps with typed events — clean model for complex agent DAGs.

  • Observability & Debugging

    • Langfuse - Open-source LLM observability (MIT license). Acquired by ClickHouse. 19 Fortune 50 clients. Full-featured: tracing, evaluations, prompt management, datasets.
    • Arize Phoenix - Open-source LLM observability. Trace agent runs, visualize spans, and evaluate outputs locally or in the cloud. Built on OpenTelemetry.
    • AgentOps - Agent-specific observability and testing. Session replays, cost tracking, failure analysis, and compliance monitoring. Native integrations with CrewAI, AutoGen, LangChain.
    • Weights & Biases Weave - W&B's LLM observability platform. Trace, evaluate, and monitor agent runs with rich visualization.
    • Traceloop / OpenLLMetry - OpenTelemetry-based LLM observability. Automatic instrumentation for LangChain, CrewAI, AutoGen, and 20+ frameworks. Sends traces to any OTel-compatible backend (Datadog, Grafana, etc.).
    • Helicone - Open-source LLM observability and caching proxy. Drop-in for OpenAI/Anthropic/Gemini. Per-request latency, cost, and error tracking with user-level attribution.
    • Weights & Biases Weave - W&B's LLM observability platform. Trace, evaluate, and monitor agent runs with rich visualization.
    • Honeyhive - Agent evaluation and monitoring platform. Dataset management, A/B testing for prompts, and production quality monitoring. Focus on multi-step agent workflows.

  • State & Memory

    • Mem0 - Adaptive memory layer for AI agents. Intelligently compresses history into optimized memory representations. Claims up to 80% prompt token reduction. Lowest integration friction for standalone memory.
    • Zep - Long-term memory store with temporal knowledge graph. Tracks how facts change over time. Integrates structured business data with conversational history. Best for temporal-aware production pipelines.
    • Letta (formerly MemGPT) - Agents with OS-style virtual memory management. Self-editing memory architecture with in-context vs archival storage. Includes REST API and development environment.
    • Cognee - Knowledge-graph-first memory for agents. Builds structured knowledge graphs from unstructured data for rich semantic retrieval.
    • LangMem - LangChain's memory abstraction layer. Multiple memory types (episodic, semantic, procedural) with a unified API.
    • Supermemory - Universal memory API for AI agents. Import from anywhere, query with semantic search. Designed as a "memory backbone" across multiple agents.
    • Redis (State Management) - Fast in-memory store for short-term agent state, session data, and distributed locks. Essential for stateful multi-agent systems requiring sub-millisecond access.
    • Chroma - Open-source embedding database. The most popular vector store for agent memory. Simple API, runs locally or in the cloud. pip install chromadb.
    • Qdrant - High-performance vector database written in Rust. Excellent for production agent long-term memory with filtering, payload indexing, and sparse vector support.
    • Weaviate - Open-source vector database with built-in vectorization. Modules for text, images, and multi-modal memory. Native GraphQL API.
    • Haystack DocumentStore - Pluggable document store interface for Haystack agents. Supports Elasticsearch, OpenSearch, Weaviate, Pinecone, and more. Uniform API across backends.
Programming Languages
Python 18 TypeScript 6 Jupyter Notebook 2 Rust 2 C# 1 Go 1
Categories
Multi-Agent Orchestration 15 State & Memory 11 Learning Resources 9 Messaging & Notification 9 Examples & Demos 8 Observability & Debugging 8 Developer Tools & SDKs 8 Communication Protocols 7 Identity & Trust 4 Contributing 1
Sub Categories
Keywords
llm 16 ai 14 openai 11 agents 9 llmops 8 langchain 8 python 7 ai-agents 7 open-source 5 prompt-engineering 5 llms 4 anthropic 4 chatgpt 4 rag 4 generative-ai 3 vector-database 3 typescript 3 artificial-intelligence 3 evals 3 autogen 3 monitoring 3 llama-index 3 mcp 3 genai 3 llm-evaluation 3 agent 3 machine-learning 2 llm-agent 2 framework 2 workflows 2 nextjs 2 analytics 2 chatbots 2 evaluation 2 gpt-4 2 large-language-models 2 gpt 2 llm-observability 2 help-wanted 2 gemini 2 good-first-issue 2 observability 2 playground 2 prompt-management 2 ycombinator 2 hnsw 2 pydantic 2 image-search 2 mlops 2 nearest-neighbor-search 2