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Medplum MCP

Welcome to the official documentation for the Medplum MCP integration. This guide provides an in-depth look at how to set up and use the integration, detailing the available tools and providing practical examples to help you get started.

Medplum is the open-source healthcare developer platform. Our MCP integration allows AI models to securely access, analyze, and interact with healthcare data (e.g., patient records, appointments, lab results) stored on a Medplum server, all powered by the FHIR standard.

Getting Started​

To begin using the Medplum MCP integration, follow these steps:

  1. Open Claude.ai: You will need a paid plan to add integrations.
  2. Navigate to Settings: Click on the settings icon in the bottom left, then navigate to "Organization Integrations."
  3. Add Integration: Click "Add Integration" and enter the following details:
  4. Connect: Back on the Organization integrations page, click the "Connect" button. You will be redirected to Medplum to authenticate.
  5. Confirm Access: Once redirected back to Claude, you can create a new chat and confirm the integration is working by asking: "Can you please confirm you have access to the 'fhir-request' MCP tool?"

Note: LLMs can sometimes cache sessions. If you experience issues, try disconnecting and reconnecting the integration in a new chat.

Core Functionality and Tools​

The Medplum MCP integration exposes several powerful tools for interacting with FHIR data. Here are the tools available in your MCP server:

fhir-request​

  • Title: Perform a FHIR API Request
  • Description: This is a powerful, low-level tool that performs a direct FHIR API request. It can be used to create, read, update, or delete FHIR resources, providing full CRUD (Create, Read, Update, Delete) functionality.
  • Annotations: This tool can modify data.
  • Schema:
{
  "type": "object",
  "properties": {
    "method": {
      "type": "string",
      "enum": ["GET", "POST", "PUT", "PATCH", "DELETE"],
      "description": "The HTTP method for the request."
    },
    "url": {
      "type": "string",
      "description": "The full FHIR API URL path (e.g., '/fhir/Patient')."
    },
    "body": {
      "type": "object",
      "description": "The JSON body of the FHIR resource to be created or updated."
    }
  },
  "required": ["method", "url"]
}

Example Use Cases​

Here are three examples demonstrating the core capabilities of the Medplum MCP integration. These examples will be visible to users in the Anthropic Directory listing.

Example 1: Finding High Blood Pressure Patients (Using search)

  • Prompt: "What are the names of all patients who have a blood pressure observation with a systolic value greater than 140 in the last year?"
  • Tool Call: The AI will use the search tool with the resourceType set to "Patient" and searchParams filtering for patients linked to specific observations.
  • Outcome: The Medplum server responds with a list of patient names and IDs that match the criteria, which the AI can then summarize for the user.

Example 2: Scheduling a New Appointment (Using fhir-request)

  • Prompt: "Create a new appointment for patient 'Jane Doe' with Dr. Smith for a routine check-up next Tuesday at 10 AM."
  • Tool Call: The AI will use the fhir-request tool with the method set to "POST", the url set to /fhir/Appointment, and a body containing the details of the new appointment.
  • Outcome: The Medplum server creates the appointment and returns a success message, which the AI can confirm with the user.

Example 3: Fetching Specific Lab Results (Using fetch)

  • Prompt: "What were the results of patient 'John Doe's most recent lab work for cholesterol?"
  • Tool Call: The AI will first use the search tool to find the ID for John Doe, and then the fetch tool to retrieve the specific Observation resources for his latest cholesterol lab work.
  • Outcome: The Medplum server returns the detailed observation data, including values and units, which the AI can present to the user in an easy-to-understand format.

Authentication and Security​

Medplum uses OAuth 2.0 with the 6/18 auth spec to securely authenticate users. When you first connect the integration, you will be redirected to the Medplum server to log in and authorize Claude.ai to access your data. Medplum's platform ensures all data access is secure and compliant with relevant healthcare regulations. Our full privacy policy can be found here: https://www.medplum.com/privacy

Support and Community​

For questions, feedback, or technical support, please contact us through one of our community channels. We recommend our Discord for real-time conversation and GitHub for bug reports.