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HealthChain

by healthchainai

Provides typed, validated FHIR tools for agents to create, inspect, code, and check healthcare resources.

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Install HealthChain

Pick your client, then add it in one click or paste the config.

STDIOPython
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "healthchainai-healthchain": {
      "command": "uvx",
      "args": [
        "healthchain"
      ]
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

We couldn’t confirm it starts correctly

The install command installed and started the server, which then stopped for configuration (such as an API key) that our sandbox does not have — expected for servers that connect to your account.

uvx healthchain

Process exited before answering initialize.

This is an experimental automated check and can have false negatives — missing environment variables, a slow cold install, etc. It doesn’t necessarily mean something’s wrong. Last checked Today.

Overview

healthchainai/HealthChain MCP server exposes typed and validated FHIR capabilities for healthcare AI agents. It supports building, reading, validating, and coding FHIR resources from patient bundles, along with terminology lookup and machine-readable validation reports. The underlying Python project can connect to live FHIR APIs and serve its toolkit to Claude over MCP. Reach for it when an agent needs to work with clinical data while preserving FHIR structure and validation.

Use cases

  • Build FHIR resources from agent-generated clinical data
  • Validate patient records before downstream processing
  • Look up terminology codes during healthcare workflows
  • Read patient bundles for grounded agent responses

Key features

  • Typed FHIR resource tools
  • Machine-readable validation reports
  • FHIR terminology lookup
  • Patient bundle reading and coding
  • Claude access over MCP
  • Live FHIR API connectivity

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked Today

Recent health check succeeded.

27/27 checks healthy over the last 92d

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 5d ago via OSV.dev · healthchain (PyPI)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars231Stargazers on the source repository.
Last commit5d agoMost recent push to the default branch.
Install checkRunsOur sandbox started it; it then asked for an API key or config.
Directory activity1 installs · 1 upvotesConfig copies, upvotes, and views on AllMCPs.

How HealthChain works

What healthchainai/HealthChain MCP server does

healthchainai/HealthChain MCP server provides healthcare-focused tools around the Fast Healthcare Interoperability Resources (FHIR) standard. Its stated MCP capabilities cover creating and reading FHIR resources, validating resource content, coding resources from patient bundles, and looking up terminology. The server is intended for agents that need to handle structured clinical information rather than produce unconstrained text.

Validation is a central part of the workflow. The project describes typed FHIR resources and machine-readable validation reports designed to support a fix-and-retry loop. This gives an agent structured feedback when generated data does not satisfy the expected FHIR model or contains invalid clinical codes.

How it works

The HealthChain Python toolkit supplies the FHIR functionality, and its agent tools can be served to Claude through the Model Context Protocol. The project also supports FHIR-grounded question answering from a live clinical record and connections to live FHIR APIs, including multi-EHR scenarios described in the repository. These capabilities make it suitable for workflows where an agent needs to inspect patient data, produce a FHIR representation, and check that representation before it is used downstream.

The validation approach is designed to avoid silently filling in clinical details. The project states that its helpers do not add claims that were not supplied, such as guessed statuses or automatically generated timestamps. That behavior is relevant when an application needs a clear boundary between model output and data written into a clinical record.

Setup and configuration

Install the Python package with the MCP extra:

Terminal
pip install healthchain[mcp]

The repository also documents the base package installation as pip install healthchain. For the broader SDK, a project can be scaffolded with healthchain new my-app -t fhir-gateway, entered with cd my-app, and started locally with healthchain serve.

Tools and capabilities

The documented capabilities include:

  • Creating typed FHIR resources.
  • Reading FHIR data from patient bundles.
  • Validating resources and returning machine-readable reports.
  • Looking up healthcare terminology and codes.
  • Coding FHIR resources from available patient information.
  • Serving FHIR tools to Claude over MCP.
  • Connecting applications to live FHIR APIs, including multiple EHR sources.

healthchainai/HealthChain MCP server fits agent workflows that need structured clinical inputs and outputs, validation before writes, or terminology-aware resource construction. The repository also identifies integrations with FastAPI and LangChain, although those are broader SDK integrations rather than MCP client requirements.

Read the full README View source on GitHub

Reviews

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Frequently Asked Questions about HealthChain

It does not document a separate command for starting the MCP server.

It supports building, reading, validating, and coding FHIR resources from patient bundles, plus terminology lookup and machine-readable validation reports.

Yes. The repository states that its typed FHIR tools can be served to Claude over MCP.

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