"Combine A2A and MCP to create advanced, distributed agentic systems!"

A2A-Go is a framework for building scalable, distributed agentic AI systems. It promotes a microservice architecture where agents and tools operate as independent services, deployable locally or across a network. The framework implements the Agent-to-Agent (A2A) protocol and utilizes the Model Context Protocol (MCP) for standardized tool interaction and data exchange.

a2a‑go is a reference Go implementation of the Agent‑to‑Agent (A2A) protocol by Google, including the proposed interoperability with the Model Context Protocol (MCP).

🚧 Work in progress 🚧 Consider this project a proof of concept at best, and subject to sudden changes.

• Agent‑to‑Agent (A2A) protocol implementation

  • Send Task to send a new task to an agent
  • Get Task to retrieve a task by ID
  • Cancel Task to cancel a task
  • Stream Task to stream the task results
  • Set Push Notification to configure push notifications for a task
  • Get Push Notification to retrieve the push notification configuration for a task
  • Structured Outputs to return structured data from an agent
  • Fine‑tuning to fine‑tune an agent on a dataset
  • Image Generation to generate images with an agent
  • Audio Transcription to transcribe audio
  • Text‑to‑Speech to convert text to speech

• Model Context Protocol (MCP) interoperability

  • Tool Calling to call tools and receive the results
  • List Prompts to retrieve a list of prompts from an agent
  • Get Prompt to retrieve a prompt by ID
  • Set Prompt to create or update a prompt
  • Delete Prompt to delete a prompt by ID
  • List Resources to retrieve a list of resources from an agent
  • Get Resource to retrieve a resource by ID
  • Set Resource to create or update a resource
  • Delete Resource to delete a resource by ID
  • Sampling to sample a task from an agent
  • Roots to get the root task for a task

• Built‑in tools

  • Browser to browse the web
  • Docker to run Docker commands
  • GitHub to search GitHub
  • Memory to store and retrieve memories
  • Qdrant to store and retrieve vectors
  • Neo4j to store and retrieve graph data

Use the Makefile to run a full containerized distributed system, demonstrating A2A and MCP interoperability.

make server
make client