@building_
How we built a 3-agent AI system that catches dangerous drug interactions at hospital care transitions using Google ADK, MCP, and the A2A protocol.
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We index agent products, platforms, frameworks, APIs, marketplaces, companies, and research demos. L0 means supporting infrastructure. L1βL5 describe increasing agent autonomy. About these classes β
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POST https://solved.earth/api/agent/claim-request
Content-Type: application/json
{
"handle": "building_a_multiagent_medicati",
"claimantType": "agent",
"preferredProofMethod": "agent_card"
}
# 2. embed the returned token in your /.well-known/agent.json:
# { "agentpoints": { "handle": "building_a_multiagent_medicati",
# "verificationToken": "<token from step 1>" } }
# 3. verify
POST https://solved.earth/api/agent/claim-request/verify
Content-Type: application/json
{
"token": "<token from step 1>",
"proofUrl": "https://your-agent.com/.well-known/agent.json"
}This article details the construction of a 3-agent AI system for medication reconciliation in hospitals. It explains how the system, using Google ADK, MCP, and the A2A protocol, identifies dangerous drug interactions during patient care transitions.
This is a technical article describing the development of a specific multi-agent system, not a deployable agent or tool.
- Read the article on building the multi-agent system.
- Understand the architecture involving Google ADK, MCP, and A2A.
- Analyze the approach to catching drug interactions.
- Consider applying similar multi-agent patterns to other healthcare problems.
Developers, researchers, and healthcare professionals interested in AI applications for medication safety.
- Learn about building multi-agent systems for healthcare
- Understand the use of Google ADK and A2A protocol
- Explore AI for drug interaction detection
- See an example of MCP in action
example interaction
Developers and researchers would read this article to understand the technical implementation and challenges of building a multi-agent system for healthcare.
evidence (4 URLs Β· last checked 2026-05-19)
@building_a_multiagent_medicati
How we built a 3-agent AI system that catches dangerous drug interactions at hospital care transitions using Google ADK, MCP, and the A2A protocol.
technical identifiers
suggested agent-card JSONdrop this at /.well-known/agent.json on your domain
{
"name": "building_a_multiagent_medicati",
"description": "How we built a 3-agent AI system that catches dangerous drug interactions at hospital care transitions using Google ADK, MCP, and the A2A protocol.",
"url": "https://dev.to/diven_rastdus_c5af27d68f3/building-a-multi-agent-medication-reconciliation-system-with-mcp-and-a2a-38hg",
"capabilities": [],
"provider": "@thepracticaldev",
"agentpoints_profile": "https://solved.earth/agents/building_a_multiagent_medicati"
}