Senechal Mcp

Overview

Senechal MCP Server bridges the gap between an AI assistant and a rich health‑data ecosystem. By exposing the Senechal API through Model Context Protocol, it allows large language models to pull real‑time health metrics, summaries, and analytics directly into their context or invoke them as callable tools. This solves the common problem of data silos: health apps often expose data only through proprietary SDKs or REST endpoints that are cumbersome for LLMs to consume. With a single MCP endpoint, developers can give their assistants instant access to patient demographics, medication lists, daily measurements, and trend analyses without writing custom adapters.

The server provides a clean set of resources that represent static or semi‑static data views, such as for demographic information or for period‑based summaries. These resources can be fetched and embedded in the LLM’s prompt, enabling context‑aware reasoning about a user’s health status. Complementing these are tools like , which let the model call a function to retrieve fresh data on demand. This dual approach gives developers flexibility: embed pre‑computed insights or let the model decide when to pull live data.

Key capabilities include:

• Granular querying: Parameters such as , , and let callers tailor data granularity, from a single day to multi‑year trends.
• Statistical analysis: The resource returns aggregated metrics (mean, median, variance) over a configurable period, enabling advanced health analytics without additional code.
• Cross‑platform integration: The server ships a configuration for Claude Desktop, allowing users to add “Senechal Health” as a tool with a single click.

Typical use cases span clinical decision support, personalized wellness coaching, and health‑tracking chatbots. For instance, a virtual nurse could ask the LLM to “summarize my blood pressure trend over the past month” and receive a concise summary generated by . In research, analysts could embed trend data into prompts that generate hypotheses or visualizations. Because the MCP server handles authentication, rate‑limiting, and data formatting, developers can focus on higher‑level application logic.

What sets Senechal MCP Server apart is its tight coupling with a well‑structured health API and the inclusion of reusable prompt templates. Developers can import these prompts to standardize how data is interpreted, ensuring consistent reasoning across different models and projects. The server’s modular design also means that adding new resources or tools is straightforward, making it a future‑proof foundation for any health‑centric AI workflow.