mcpField
F
fitness-influencer

fitness-influencer

Local
github.com/MarceauSolutionsMedia & Design
Repository

About fitness-influencer

AI-powered fitness content creator tools: video editing, image generation, workout plans, analytics

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
  "mcpServers": {
    "wmarceau-fitness-influencer": {
      "command": "uvx",
      "args": [
        "fitness-influencer-mcp"
      ],
      "env": {
        "XAI_API_KEY": "<XAI_API_KEY>",
        "GOOGLE_CREDENTIALS_PATH": "<GOOGLE_CREDENTIALS_PATH>"
      }
    }
  }
}
Run commanduvx fitness-influencer-mcp
Environment variables to set
XAI_API_KEYSecretxAI/Grok API key for image generation ($0.07/image)
GOOGLE_CREDENTIALS_PATHSecretPath to Google OAuth credentials for Sheets analytics

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
pypifitness-influencer-mcp1.3.0

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

The maintainer has not added details yet. Check the README in the repository.

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.