AI Agents Interoperability
An enterprise ready Agentic AI architecture which is framework and LLM Agnostic.
Architecture
The “What” and “Why”
AI Agent Interoperability: Building Framework-Agnostic Multi-Agent Systems
I have explained the key concepts of agent interoperability and how you can leverage them to build framework-agnostic AI.
Read Time: 6 min
Managing LLM’s asymmetric context windows in multi-interoperable-agentic systems
I have explained importance of context window length in a multi-interoperable-agentic systems.
Read Time: 4 min
Model Context Protocol (MCP) Gateway — a middleware meant to productionize MCP for an enterprise
I have explained how ContextForge MCP Gateway works — a secure, unified middleware for scaling agentic AI integrations in the enterprise.
Read Time: 5 min
The “How to’s”
Developing a Model Context Protocol (MCP) server and client for your agent-tool interoperability
I have explained how to implement a MCP Server and MCP Client for your enterprise
Read Time: 6 min
Deploy a remote Model Context Protocol (MCP) server and access it through Server-Sent Events (SSE) transport protocol
I have explained how to deploy a remote MCP server and access it through Server Sent Events (SSE) transport protocol.
Read Time: 5 min
Building Interoperable AI Agents with Agent Communication Protocol (ACP)
I have explained how to build a Cross-Framework AI Agent Ecosystems.
Read Time: 4 min
GitHub Link
- Repository (10+ ⭐️)
Skills picked up
- Hands-on Large language models (OpenAI, Meta-llama, Mistralai, Claud, AWS Bedrock, HuggingFace, Ollama, LiteLLM, watsonx.ai)
- Develop & Deploy AI Agents
- Govern AI Agents
- Multi-agentic frameworks (LangGraph, CrewAI, Autogen, BeeAI, Strands)
- Agent communication protocol (ACP), Google A2A
- Model context protocol (MCP), MCP Gateway
- Transport protocols: Server sent events (SSE), Stdio
- HTTP/ JSON-RPC
Work in progress! keep a watch!