Setting up a Protocol for AI Agents Exchange Between Different Vendors
Different AI agents use different formats, protocols, and interfaces. Claude Code, Devin, SWE-Agent, AutoGen agents — each speaks its own "language". To build multi-vendor AI team, unified inter-agent protocol is needed.
Standards and Protocols
MCP (Model Context Protocol, Anthropic): Open protocol for connecting AI assistants to tools and data. Unified interface: server provides tools, resources, prompts — client (Claude, Cursor, etc.) connects per standard. Allows agents from different ecosystems to use same tools.
A2A (Agent-to-Agent Protocol, Google): Protocol for direct interaction between agents from different vendors. Defines: how agent publishes capabilities, how another agent discovers them, how tasks and results are transmitted.
OpenAI Function Calling / Tool Use: De-facto standard for tool description. Most agents support this format — used as lingua franca in integration.
Multi-vendor pipeline Architecture
Task Router (Paperclip / LangGraph)
↓
[Claude Code Agent] [Devin Agent] [SWE-Agent] [Custom Agent]
↑___________MCP Tools Server___________________↑
↑
[GitHub] [Jira] [Slack] [Internal APIs]
MCP Tools Server — unified tool server accessible to all agents via standard protocol.
Development Pipeline
Weeks 1–3: Audit of used agents. Protocol selection (MCP / A2A). Tool server design.
Weeks 4–8: Development of MCP/A2A server. Adapters for each agent. Testing cross-vendor interaction.
Weeks 9–12: Production deployment. Monitoring. Observability for multi-agent trace.
Challenges
Protocol versioning changes rapidly (MCP actively developing in 2025). A2A — still in early adoption stage. Real compatibility requires adaptation for each agent pair.