Ai Agents Interoperability
What is Ai Agents Interoperability
ai-agents-interoperability refers to the frameworks and guidelines that facilitate communication between different AI agents using the Model Context Protocol (MCP) and the Agent Communication Protocol (ACP).
Use cases
Use cases include collaborative robotics where multiple robots need to work together, virtual customer service agents that communicate seamlessly, and AI systems in smart homes that interact with each other.
How to use
To use ai-agents-interoperability, developers should follow the provided guides to implement MCP and ACP in their AI systems, ensuring that agents can effectively communicate and share context.
Key features
Key features include standardized communication protocols, enhanced interoperability between AI agents, and guidelines for implementing context-aware interactions.
Where to use
ai-agents-interoperability can be used in various fields such as robotics, virtual assistants, and any domain where multiple AI agents need to collaborate and share information.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Ai Agents Interoperability
ai-agents-interoperability refers to the frameworks and guidelines that facilitate communication between different AI agents using the Model Context Protocol (MCP) and the Agent Communication Protocol (ACP).
Use cases
Use cases include collaborative robotics where multiple robots need to work together, virtual customer service agents that communicate seamlessly, and AI systems in smart homes that interact with each other.
How to use
To use ai-agents-interoperability, developers should follow the provided guides to implement MCP and ACP in their AI systems, ensuring that agents can effectively communicate and share context.
Key features
Key features include standardized communication protocols, enhanced interoperability between AI agents, and guidelines for implementing context-aware interactions.
Where to use
ai-agents-interoperability can be used in various fields such as robotics, virtual assistants, and any domain where multiple AI agents need to collaborate and share information.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
AI Agents Interoperability Series
Learn how to architect Agentic AI solutions which are framework agnostic, LLM Agnostic. Refer to the Blog series below to learn more.
Reference Architecture
Medium articles
Read more about AI Agents Interoperability here: Medium.com
Pre-requirements
- I have used Tavily search for the web search tool implementation, create a Tavily API Key here: https://www.tavily.com
- I have used Google SERP APIs for the flight search tool implementation, create a SERP API key here: https://serpapi.com/manage-api-key
Setup codebase
-
Clone the repo.
git clone https://github.com/manojjahgirdar/ai-agents-interoperability.gitNote: UV Package manager is recommended.
-
Install the uv package manager.
pip install pipx pipx install uv -
Once the uv package manager is installed, create a virtual environment and activate it.
uv venv source .venv/bin/activate -
Install the python dependencies.
uv sync -
Export env variables
cp env.example .envFill the env values
-
Launch the mcp/acp servers.
- To launch the mcp server run:
cd src/mcp/mcp-server uv run mcp_server.py - To launch the acp server, in another terminal run:
cd src/acp/acp-server export REMOTE_MCP_URL=http://127.0.0.1:8000/sse uv run acp_server.py
- To launch the mcp server run:
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.
