Wellness Pulse

With asingle integration, your AI gets access to:

- 📊CDC PLACES public benchmarks— trusted mental health data for any ZIP code or county in the US
- 🏢Institutional wellness signals— live trends, snapshots, and alert checks from your organization's Wellness Pulse data
- 🗣️Plain-English explanations— AI-ready summaries returned alongside structured JSON

Built for fast"ask → answer"workflows in copilots, automations, and AI dashboards — no human analysis needed in the loop.

Fetches CDC PLACESFrequent Mental Distress (FMD)data for a given ZIP code or county FIPS.

At least one ofziporcounty_fipsis required.

Returns:scope,values,national_percentile_rank(optional),marketing_copy

Example use case:"What's the CDC mental distress benchmark for ZIP 94597?"

Returnsdefault alert thresholdsbased on organization size and location type — no institution ID needed.

Example use case:"What alert thresholds should we use for a mid-size suburban institution?"

These tools require a valid institution identifier (institution_id) from your Wellness Pulse account.

Apoint-in-time snapshotof wellness data for your institution over a given window.

Returns:response_count,avg_wellness_score,last_response_at

Fetches adaily time-seriesof wellness scores and response counts.

Returns:Array of{ day, avg_wellness, responses }objects

Example use case:"What's our wellness trend for the last 90 days?"

Compares last 7 days vs prior 7 daysand flags significant drops.

Returns:drop_pct,alert(boolean flag)

Example use case:"Did we drop week-over-week? Should we be concerned?"

Sector-level aggregated wellness data across institutions.

Returns:institutions_with_responses,total_responses,avg_wellness_score

Claude Desktop (claude_desktop_config.json)

{ "mcpServers": { "Wellness Pulse": { "url": "https://wpulse.org/mcp/", "transport": "http-stream" } } }

{ "mcpServers": { "Wellness Pulse": { "url": "https://wpulse.org/mcp/", "transport": "http-stream" } } }

Step 2 — Initialize a Session (via cURL)

curl -s https://wpulse.org/mcp/ \ -H "Content-Type: application/json" \ -H "Accept: application/json, text/event-stream" \ -d '{ "jsonrpc": "2.0", "id": 1, "method": "initialize", "params": { "protocolVersion": "2025-03-26", "capabilities": {}, "clientInfo": { "name": "my-app", "version": "1.0.0" } } }'

📌 Capture themcp-session-idfrom the response headers — you'll need it for all subsequent calls.

curl -s https://wpulse.org/mcp/ \ -H "Content-Type: application/json" \ -H "Accept: application/json, text/event-stream" \ -H "mcp-session-id: <YOUR_SESSION_ID>" \ -d '{ "jsonrpc": "2.0", "id": 2, "method": "tools/list", "params": {} }'

Example: Fetch CDC benchmark for a ZIP code

curl -s https://wpulse.org/mcp/ \ -H "Content-Type: application/json" \ -H "Accept: application/json, text/event-stream" \ -H "mcp-session-id: <YOUR_SESSION_ID>" \ -d '{ "jsonrpc": "2.0", "id": 3, "method": "tools/call", "params": { "name": "get_mental_health_benchmark", "arguments": { "zip": "94597" } } }'

curl -s https://wpulse.org/mcp/ \ -H "Content-Type: application/json" \ -H "Accept: application/json, text/event-stream" \ -H "mcp-session-id: <YOUR_SESSION_ID>" \ -d '{ "jsonrpc": "2.0", "id": 4, "method": "tools/call", "params": { "name": "get_institution_alert_check", "arguments": { "institution_id": "inst_abc123" } } }'

Once Wellness Pulse MCP is connected, try asking your AI:

"What's our wellness trend for the last 90 days?" "Did we drop week-over-week? Why might that matter?" "What's the CDC mental distress benchmark for ZIP 94597?" "Write a short exec update with our wellness numbers and CDC context." "Are we above or below the national average for mental distress?" "Flag any alert conditions in our institution data this week." "Summarize the sector snapshot and highlight any outliers."

Content-Type: application/json Accept: application/json, text/event-stream

Wellness Pulse MCP is built with aprivacy-first architecture:

- ✅ No user tracking or behavioral logging
- ✅ No personally identifiable information (PII) stored or transmitted
- ✅ Institution data is scoped and access-controlled per account
- ✅ All transport over HTTPS
- ✅ Designed for compliance-conscious environments (healthcare, education, HR)

🏥 Healthcare & Employee Wellness Teams

Use daily trend monitoring and week-over-week alert checks to detect emerging burnout or distress signals before they escalate — and give clinical or HR leadership an AI-generated executive summary on demand.

🎓 Universities & Educational Institutions

Combine CDC county benchmarks with your student wellness survey data to contextualize scores relative to regional norms — ideal for accreditation reports and student affairs presentations.

Embed Wellness Pulse MCP into your existing copilot or dashboard product to instantly add benchmarked mental health context and trend narration — without building your own data pipeline.

Pull CDC PLACES FMD data by ZIP or county to generate marketing copy, grant narratives, and community health reports grounded in authoritative public data.

Wire Wellness Pulse MCP into multi-step agents that periodically check for alert conditions, draft stakeholder updates, and route escalations — all without human-in-the-loop analysis.

Built with care by theWellness Pulseteam.
Helping organizations understand and act on wellbeing data — intelligently.

Monitor team productivity, usage, and spending for AI assistants using the Cursor Admin API.

Provides structured access to ActivityWatch time tracking data for AI assistants.

Access fathom ai api endpoints via mcp server and llm.

Multi-Agent Monitoring LangFuse MCP Server

A Model Context Protocol (MCP) server for comprehensive monitoring and observability of multi-agent systems using Langfuse.

Predict and track AI ROI using Monte Carlo simulations, real-time industry benchmarks, and ML-powered insights.

Stubble learns how you work and organizes your day automatically. Export timesheets, surface insights, and supercharge your AI tools.

Paid remote MCP for AI agent run monitoring, failure detection, tool-call incident replay, SLA receipts, and client status exports.

Behavioral trust layer for the AI agent economy. Check MCP server reliability scores, report interactions, detect anomalies, and discover the most trusted servers. 8 tools, free, real-time.

Behavioral trust scoring for MCP servers and AI agents. Live registry tracking 4,500+ servers with trust scores based on interaction history, success rates, and latency.