Analytics

fitnessxdash.com

Returns a summary of a personal health dashboard including available data sources and metrics, with full data requiring API key authentication.

WebMCP1 endpoint1 known toolsFirst detected September 17, 2026Last detected September 17, 2026

ENDPOINT 1

https://fitnessxdash.com/login

No auth detected

MCP server metadata

Name: WebMCP

Capabilities

imperative

Known tools 1

get_health_summary

Returns a summary of this personal health dashboard including available data sources and metrics. Full data requires API key authentication via x-api-key header on /api/dashboard.

Inferred read-only

CONNECT WITH APPROVAL

Client installation

Review this server and its permissions before adding it. Secret placeholders must be set locally.

Codex

~/.codex/config.toml

[mcp_servers.webmcp]
url = "https://fitnessxdash.com/login"
enabled = true

Claude Code

.mcp.json

{
  "mcpServers": {
    "webmcp": {
      "type": "http",
      "url": "https://fitnessxdash.com/login"
    }
  }
}

Claude Desktop

Settings → Connectors → Add custom connector

Name: webmcp
Remote MCP URL: https://fitnessxdash.com/login

Add this remote URL as a custom connector in Claude Desktop. Availability depends on the user plan and workspace policy.

Cursor

.cursor/mcp.json

{
  "mcpServers": {
    "webmcp": {
      "url": "https://fitnessxdash.com/login"
    }
  }
}

Visual Studio Code

.vscode/mcp.json

Add to Visual Studio Code

{
  "servers": {
    "webmcp": {
      "type": "http",
      "url": "https://fitnessxdash.com/login"
    }
  }
}

Generic MCP

Client-specific MCP configuration

{
  "name": "webmcp",
  "transport": "streamable-http",
  "url": "https://fitnessxdash.com/login"
}

MCP Inspector

Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.

TRUST AND VERIFICATION EVIDENCE

Loading Trust v2 evidence…

Checking the associated registrable domain. The BuiltWith key remains server-side.

Indexed

Evidence is source-attributed and does not guarantee that a third-party server is safe. Risk labels are conservative metadata heuristics.