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  1. Home
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  3. HealthChain
HealthChain logo
Health: ActiveRecent health check succeeded.Last checked 9/21/2026, 6:46:50 AM

HealthChain

User RatingsBe the first to rate and review this MCP server!
View Repository226 GitHub StarsTotal stargazers on GitHub for the source repository (226 stars).Visit Website
healthcarefhirclinical-datamcp

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

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to CursorAdd to VS Code
We couldn’t automatically confirm this listing starts correctly

We ran the install command below but it didn't respond within our test window — this can mean a slow first-time install rather than a real problem.

uvx healthchain

No response to 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.

Manual Client & Custom JSON ConfigExpand JSON â–¾

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "healthchainai-healthchain": {
      "command": "uvx",
      "args": [
        "healthchain"
      ]
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing Alternatives🧬 More in Biology & Bioinformatics

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

Capabilities & Tool Schemas

Inspect callable tools, capabilities, and parameters exposed to AI agents by HealthChain.

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

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. The generated application is configured through app.py and healthchain.yaml; the provided material does not specify separate MCP server startup arguments or required environment variables.

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 →

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Adoption & maintenance

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

GitHub stars
226
Stargazers on the source repository.
Last commit
20d ago
Most recent push to the default branch.
Install check
Inconclusive
Didn't respond in our test window — often a slow first install.
Directory activity
1 installs · 1 upvotes
Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet — be the first to share how this listing worked for you.

Frequently Asked Questions about HealthChain

The provided material lists `pip install healthchain[mcp]`. It does not document a separate command for starting the MCP server.

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Technical Specs & Signals

Category🧬Biology & Bioinformatics
PricingFree
More technical detailsExpand â–¾
TransportSTDIO
RuntimePython
AuthNo auth required
LicenseApache-2.0
ClientsClaude Desktop
Last updatedSep 6, 2026
12/12 checks healthy over the last 42d
Views3
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs1
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars226
GitHub Star CountTotal stargazers on GitHub representing community popularity (226 stars).
Last commit20d ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Sep 1, 2026
59Quality signal: Good · 59/100How this signal is calculated ▾
Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools24/30
Adoption & activity9/15
Community engagement1/10

A guidance signal from public completeness & health data — not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 6h ago via OSV.dev · healthchain (PyPI)

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More in 🧬 Biology & Bioinformatics →Alternatives to HealthChain →Install in Claude DesktopInstall in CursorInstall in VS Code