Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Descripción del creador (original en inglés)
MCP server for managing workouts, routines, and exercise data through the Hevy API
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
HEVY_API_KEYLos valores marcados como secretos son llaves de tu cuenta. Nunca los compartas ni los pegues en un chat.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"hevy": {
"command": "npx",
"args": [
"-y",
"hevy-mcp"
],
"env": {
"HEVY_API_KEY": "your-value"
}
}
}
}Ejecuta esto en tu terminal
claude mcp add hevy --env HEVY_API_KEY=your-value -- npx -y hevy-mcpCompleta los valores vacíos antes de ejecutarlo.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"hevy": {
"command": "npx",
"args": [
"-y",
"hevy-mcp"
],
"env": {
"HEVY_API_KEY": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"hevy": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"hevy-mcp"
],
"env": {
"HEVY_API_KEY": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 7 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub chrisdoc, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
Debes completar: HEVY_API_KEY
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (3.2.1) llegó al registro hace 4 meses.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Node.js en tu computadora.
En la misma categoría: Spec Driven Development, Remote Desktop Commander, Draugr
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Security scanning for AI agents: SAST, SCA, secrets, IaC, DAST, ranked by real risk.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
Talk to your Hevy workout data from Claude, Cursor, Codex, and other MCP clients.
Connect to the hosted MCP · Use the Hevy CLI · Watch the 18-second demo · Explore all 23 tools · Documentation
Prefer the terminal? The separate @chrisdoc/hevy-cli package reads workouts, routines, exercises, and body measurements directly from the Hevy API, and can create or update those resources with explicit confirmation. Deletion is not supported.
npm install -g @chrisdoc/hevy-cli
export HEVY_API_KEY=your-hevy-api-key
hevy workouts list --page-size 10 hevy summary --weeks 4
Add --json to any command for scripts and pipelines. The CLI is a standalone Hevy API client, not an MCP wrapper. See packages/cli/README.md for the full command reference, pagination behavior, and exit codes.
hevy-mcp is an open-source Model Context Protocol (MCP) server for the Hevy fitness and workout tracking app. It lets AI assistants read, analyze, create, and update your Hevy workouts, routines, exercise templates, and body measurements through authenticated Hevy API requests.
The Node stdio/HTTP adapter and Cloudflare Worker share the same MCP tools. See deployment modes to choose a transport, or architecture for workspace ownership, runtime scopes, and supported embedding APIs.
A Hevy API key, available with Hevy PRO, is required.
Click the preview to play the full-quality 18-second demo.
In the demo, the assistant retrieves real Hevy data and answers a multi-part training question with evidence from the user's workout history.
npx, bunx, or the official Docker image.Try asking:
Analyze my training over the last six weeks. Show workouts per week, my most
frequently trained exercises, any obvious gaps or inconsistencies, and cite the
workout evidence you used.
Find my push-day routine and show its exercises and sets.
Compare my recent body measurements with my training consistency.
Create a completed workout from my saved routine. Ask me for any missing set
results before writing it to Hevy.
The repository includes a Claude plugin that connects to the hosted OAuth-enabled MCP endpoint without embedding a user's Hevy API key.
In Claude, open Settings → Connectors → Add custom connector and enter:
https://mcp.hevy-mcp.dev/mcp
Complete the OAuth flow and enter the Hevy API key when prompted. The same remote endpoint can be used by Claude Desktop and other clients that support remote MCP connectors.
The Claude plugin is defined by .claude-plugin/plugin.json and .mcp.json. Install it from this public repository or from the Claude Plugin Directory after publication. It adds the hosted Hevy MCP connector and the Hevy workout skill.
See the privacy policy for the hosted service's data handling details.
Create an API key in Hevy's API settings, then keep it somewhere secure. API access currently requires a Hevy PRO subscription.
hevy-mcp to your clientThe hosted Cloudflare endpoint is the fastest way to start. It runs remotely, so your client does not need Node.js, Bun, Docker, or a local server process.
Production URL:
https://mcp.hevy-mcp.dev/mcp
The endpoint uses Streamable HTTP. Send your Hevy API key as a bearer token on every request.
Codex CLI, the Codex desktop app, and the IDE extension share the same MCP configuration. Make your Hevy API key available in the environment that starts Codex, then add the hosted server:
export HEVY_API_KEY=your-hevy-api-key
codex mcp add hevy \ --url https://mcp.hevy-mcp.dev/mcp \ --bearer-token-env-var HEVY_API_KEY
Codex stores the environment variable name, not the key itself, in its MCP configuration. Restart Codex or begin a new session, then run codex mcp list to verify the server is configured.
Clients that accept a remote MCP URL and fixed headers commonly use this shape:
{
"mcpServers": { "hevy": { "url": "https://mcp.hevy-mcp.dev/mcp", "headers": { "Authorization": "Bearer your-hevy-api-key" } } } }
Exact configuration keys vary by client. The hosted server requires support for Streamable HTTP and a fixed Authorization header.
[!IMPORTANT]
Treat the bearer value like a password. The Worker validates it with Hevy for
each request, does not store it, and forwards it to Hevy only as the required
api-keyheader.
Choose local stdio if you prefer to run the server on your own machine or your client cannot attach a fixed authorization header to remote MCP requests.
codex mcp add hevy \
--env HEVY_API_KEY=your-hevy-api-key \ -- npx -y hevy-mcp
Add this mcpServers entry to your client configuration:
{
"mcpServers": { "hevy": { "command": "npx", "args": ["-y", "hevy-mcp"], "env": { "HEVY_API_KEY": "your-hevy-api-key" } } } }
There are two ways to configure the Hevy MCP server for Google Antigravity (agy):
This utilizes the built-in plugin system:
The plugin reads the repository-root mcp_config.json to start the local stdio server. That configuration intentionally contains no API key; the server inherits HEVY_API_KEY from the host environment as described below. This is separate from the manual, user-global configuration described below and from the repository's .mcp.json, which configures hosted HTTP/OAuth.
agy plugin install https://github.com/chrisdoc/hevy-mcp
HEVY_API_KEY in your host shell environment so the CLI child process can inherit it:HEVY_API_KEY in your system/shell configurations:~/.zshrc or ~/.bashrc): bash export HEVY_API_KEY="your-actual-api-key" powershell [Environment]::SetEnvironmentVariable("HEVY_API_KEY", "your-actual-api-key", "User") agy: bash export HEVY_API_KEY="your-actual-api-key" If you prefer configuring it statically via the global configuration file:
~/.gemini/config/mcp_config.jsonhevy configuration block under the mcpServers key. Make sure to merge this entry with any existing servers you have configured rather than replacing the entire file contents: {
"mcpServers": { "hevy": { "command": "npx", "args": ["-y", "hevy-mcp"], "env": { "HEVY_API_KEY": "your-actual-api-key" } } } }
Common local configuration locations:
~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.json~/.cursor/mcp.jsonRestart or reconnect the client after saving the file.
Configure your client to launch this command with HEVY_API_KEY in the child process environment:
npx -y hevy-mcp
npx requires Node.js 20 or newer. Restart or reconnect your client after saving its configuration.
Use bunx instead
Requires Bun:
{
"mcpServers": { "hevy": { "command": "bunx", "args": ["hevy-mcp@latest"], "env": { "HEVY_API_KEY": "your-hevy-api-key" } } } }
Use Docker instead
Official images support linux/amd64 and linux/arm64. Keep stdin open with -i because the container runs the stdio MCP server:
export HEVY_API_KEY=your-hevy-api-key
docker run -i --rm -e HEVY_API_KEY ghcr.io/chrisdoc/hevy-mcp:latest
For an MCP client, store the key in a protected environment file and configure the client to launch Docker:
{
"mcpServers": { "hevy": { "command": "docker", "args": [ "run", "-i", "--rm", "--env-file", "/absolute/path/to/hevy-mcp.env", "ghcr.io/chrisdoc/hevy-mcp:latest" ] } } }
Pin an exact image tag such as ghcr.io/chrisdoc/hevy-mcp:X.Y.Z when you need reproducible upgrades.
You can also add the npm server to supported clients with add-mcp:
npx add-mcp hevy-mcp --env "HEVY_API_KEY=your-hevy-api-key"
Try one of these after restarting or reconnecting your MCP client:
Solo se muestra el principio; lee el resto en el repo