MCP server

Fitness Tools

io.github.almostjacked/fitness-tools

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

Deterministic fitness calculators — TDEE, adaptive TDEE, body fat, 1RM, macros — with consensus.

Source

At a glance

Type

MCP server

Publisher

Not verified

Status

Working at last check

Tools

10

Token cost

About 3,303 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http fitness-tools https://fitness-tools-mcp.ajwallacemusic.workers.dev/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.fitness-tools]
url = "https://fitness-tools-mcp.ajwallacemusic.workers.dev/mcp"

Gemini CLI

{"mcpServers":{"fitness-tools":{"httpUrl":"https://fitness-tools-mcp.ajwallacemusic.workers.dev/mcp"}}}

Cursor

{"mcpServers":{"fitness-tools":{"url":"https://fitness-tools-mcp.ajwallacemusic.workers.dev/mcp"}}}

VS Code

{"servers":{"fitness-tools":{"type":"http","url":"https://fitness-tools-mcp.ajwallacemusic.workers.dev/mcp"}}}

Antigravity

agy mcp add fitness-tools https://fitness-tools-mcp.ajwallacemusic.workers.dev/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"fitness-tools","server_url":"https://fitness-tools-mcp.ajwallacemusic.workers.dev/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"fitness-tools","server_url":"https://fitness-tools-mcp.ajwallacemusic.workers.dev/mcp"}

Tools

• activity-multiplier ~416 tokens
  Estimate the TDEE activity multiplier via the classic lookup table or a NEAT+EAT model (occupation/steps for non-exercise, training volume for exercise).
• adaptive-tdee ~498 tokens
  Measure actual TDEE from a logged history of daily weight and/or calorie intake. Default method (kalman) is a joint Kalman filter over true weight and TDEE — handles missing days, gates outliers, and reports uncertainty (CI95) alongside denoised true weight; regression/endpoints are simple window-ba
• body-fat ~405 tokens
  Estimate body-fat % via US Navy circumference, Jackson-Pollock 3-site skinfold, and Deurenberg (BMI-based) methods.
• ffmi ~299 tokens
  Compute the Fat-Free Mass Index (FFMI) and its height-adjusted form from weight and body fat (or lean mass), and flag whether it exceeds the ~25 natural ceiling.
• macros ~277 tokens
  Compute protein/fat/carb grams for a calorie target using the g-per-kg-bodyweight method, with goal-based protein defaults.
• muscle-potential ~276 tokens
  Estimate drug-free maximum bodyweight at a target body-fat % via Casey Butt (wrist+ankle), the FFMI~25 natural cap, and Berkhan's max-contest-weight model. Men only in v1.
• one-rep-max ~193 tokens
  Estimate 1RM from a submaximal set via Epley, Brzycki, Lombardi, Wathan, O'Conner, and Mayhew; returns a %1RM load chart.
• powerlifting-attempts ~249 tokens
  Deterministic opener/second/third attempts from an estimated 1RM, plus a warmup ramp and per-side plate loading. Tunable by aggressiveness and available plates.
• rsmi ~321 tokens
  Estimate the appendicular skeletal muscle index (RSMI) from a DXA value (direct) and/or an anthropometric estimate (Wen 2011), and flag low muscle mass against EWGSOP2, AWGS, and Baumgartner sarcopenia cutoffs.
• tdee ~369 tokens
  Estimate BMR and TDEE via Mifflin-St Jeor, Harris-Benedict, Katch-McArdle, and Cunningham. Provide body_fat or lean_mass to unlock the LBM-based methods.

Browse

• GitHub tools
• GitHub and code hosting
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