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Query patient, device, and consent data from a FHIR R4 endpoint.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "fhir-patient-consent-mcp-server" yet — see the docs or source repo.
Check whether the patient has consented to share their health data and return a summary of the related consent records.
Returns the patient's data-sharing consent status and a summary of related consent information from the FHIR R4 endpoint.
Retrieve the patient's insulin pump or other device information and describe the device records currently available.
Returns a real-time summary of device records linked to the patient, such as an insulin pump or other devices.
Summarize the patient's relevant information, device usage, and whether sharing this data is allowed using natural language.
Outputs an integrated natural-language summary covering the patient, device, and data-sharing consent based on real-time query results.
Researchers or data analysts can query patient, device, and consent information in natural language without manually inspecting individual FHIR resources. It is useful when a quick overview of current records is needed.
Developers can connect this MCP tool to AI workflows so models can answer patient- and device-related questions in real time from a FHIR R4 endpoint. It fits healthcare Q&A or assistant experiences.
When users need to confirm whether a patient allows data sharing, they can ask directly for consent status and get real-time results. This reduces the need to switch across systems to verify authorization.
It is an MCP tool that supports natural-language queries about a patient, their insulin pump or other devices, and consent to share data. Answers are retrieved in real time from a FHIR R4 endpoint.
The known prerequisite is access to a FHIR R4 endpoint, since the tool retrieves answers from it in real time. Other installation or authentication requirements are not specified in the provided material; see the source repository.
The description indicates it supports natural-language questions and returns results in real time from a FHIR R4 endpoint, rather than relying only on static preloaded content. The provided material does not specify more advanced capabilities.
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