fhir-mcp-server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| search_patientsB | Busca pacientes por apellido en el servidor FHIR. |
| get_observationsA | Trae las observaciones clínicas de un paciente por su ID FHIR. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| resumen_clinico | Plantilla para pedir un resumen clínico de un paciente. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: one searches for patients by last name, the other retrieves clinical observations for a specific patient ID. There is no meaningful overlap or ambiguity between them.
Both tool names follow the same verb_noun snake_case pattern: search_patients and get_observations. The naming is consistent, predictable, and easy for an agent to navigate.
With only two tools, the server feels thin for a FHIR implementation, which typically supports a much broader range of resources and operations. However, the count is not egregiously low and could be acceptable for a narrowly scoped use case.
The server covers only patient search and observation retrieval, missing foundational FHIR operations like getting a patient by ID, creating or updating resources, and searching observations by clinical criteria. Agents would likely encounter dead ends when trying to perform common FHIR workflows.