How to Use the Blood Type Compatibility & Demographics MCP in LlamaIndex

Ground your hematology RAG in real-time data with LlamaIndex.

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Connect Blood Type Compatibility & Demographics MCP to LlamaIndex

Create your Vinkius account to connect Blood Type Compatibility & Demographics to LlamaIndex — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Blood Type Compatibility & Demographics with LlamaIndex

Ask AI about this MCP

ChatGPT

Claude

Perplexity Vinkius runs on Gemini

Gemini

Grok

Knowledge-Augmented Distribution

Index regional data using `get_population_distribution`. Your RAG app can then answer questions about local blood availability. This MCP helps you build a searchable database of demographics. It keeps your answers grounded in actual facts.

Clinical Reference Indexing

Use `get_rbc_compatibility` to populate your vector store with safety rules. This ensures your agent stays grounded in actual medical standards. This MCP provides the raw data for your knowledge base. You won't have to worry about the agent making up rules.

Searchable Pregnancy Risk

Feed `analyze_pregnancy_risk` results into your index. You can query past risk assessments to find patterns in patient history. This MCP allows for deep retrieval of historical risk data. It makes your RAG application much more useful for clinical review.

Setup guide

Set up Blood Type Compatibility & Demographics MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Blood Type Compatibility & Demographics MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Blood Type Compatibility & Demographics tools.",
)
response = await agent.run("List recent Blood Type Compatibility & Demographics data")

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Common questions about Blood Type Compatibility & Demographics MCP in LlamaIndex

Use the MCP tool to pull data into your vector store. This makes the data searchable for your agent.

Yes, it treats the tool output as searchable content. You can query it just like any other document.

It retrieves the data through a standard tool call. The results then become part of your local index.

The tool follows standard clinical guidelines for blood safety.

LlamaIndex doesn't store the data permanently. It only indexes what you pull into your local session.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

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