mcpbeat Sign in

Fitness Influencer MCP Server

local only

Fitness Influencer runs on your own machine — the client starts it, so there is no endpoint to ping. 106 installs a week from pypi.

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

The linked repository no longer exists on GitHub — it was deleted or made private.

Installs per day peak 314 · avg 27 · +36% w/w
a month agotoday
106
Installs / week
pypi · fitness-influencer-mcp
—
Stars
on GitHub
—
Last commit
from GitHub
—
License
language unknown

This one has been quiet for a while

Quiet is not dead — but it is worth knowing when it wakes up, or when someone else takes it over. We watch the repository and tell you either way.

Three servers free · no card

Connect this server

This server runs on your own machine — install it with the package manager and the client starts it for you. Package name taken from the official registry entry.

run in your terminal
claude mcp add fitness-influencer -- uvx fitness-influencer-mcp
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "fitness-influencer": {
      "command": "uvx",
      "args": [
        "fitness-influencer-mcp"
      ]
    }
  }
}
~/.codex/config.toml
[mcp_servers.fitness-influencer]
command = "uvx"
args = ["fitness-influencer-mcp"]
.cursor/mcp.json
{
  "mcpServers": {
    "fitness-influencer": {
      "command": "uvx",
      "args": [
        "fitness-influencer-mcp"
      ]
    }
  }
}
.vscode/mcp.json
{
  "servers": {
    "fitness-influencer": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "fitness-influencer-mcp"
      ]
    }
  }
}

Optional settings from the registry entry, left out of the block above: XAI_API_KEY (xAI/Grok API key for image generation ($0.07/image)), GOOGLE_CREDENTIALS_PATH (Path to Google OAuth credentials for Sheets analytics).

Alternatives to Fitness Influencer

same job, measured the same way
Blogburst MCP Server
by shensi8312

AI social media agent — generate content, auto-pilot posting, analytics for 9+ platforms.

72 installs/wk local only
Transition MCP
by nftechie

AI-powered multisport coaching — workouts, training plans, and performance analytics.

local only
Writio
by alexlarcheveque

LinkedIn-native AI content creation, scheduling & analytics via MCP.

46 installs/wk local only
11agents Cloud MCP
by 11agents

Cloud MCP for project data, analytics, research, content planning, media generation, and growth.

answering
Cloudflare Tools
by craft-agent

Cloudflare tools for coding agents: zones, DNS, analytics, Workers, Pages, storage and tunnels.

local only
Toffu
by toffu

AI marketing platform your agent runs end to end: ads, analytics, content, and reports.

answering
SocialHive
by socialhive

Social media management, multi-platform publishing, AI generation, and cross-channel analytics.

24 tools answering
Tiktok Creator
by wmarceau

TikTok automation: post videos, get analytics, manage comments

80 installs/wk local only

Fitness Influencer — questions

Answers built from our own checks of this server.

Why is there no uptime for Fitness Influencer?
Fitness Influencer runs on your own machine over stdio — there is no network address to reach, so uptime cannot be measured for it by anyone. What can be measured is adoption: the pypi package fitness-influencer-mcp was installed 106 times last week.
Is Fitness Influencer still maintained?
The linked repository no longer exists on GitHub — it was deleted or made private. We show this because it changes what you can expect: an unmaintained server may keep answering for months and then stop without warning.
How do I connect Fitness Influencer?
Copy the ready config from this page. We generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each in the form that client actually reads. It runs locally, so the command pulls fitness-influencer-mcp straight from pypi; nothing to host, nothing to sign up for.
How many people use Fitness Influencer?
The pypi package fitness-influencer-mcp was installed 106 times in the last week. Week over week that is +36%. We show installs rather than GitHub stars on purpose: a star is a bookmark, an install is someone actually running it.