Agent-Native Calendar
Agent-Native Google Calendar - manage events, sync, and public booking
Descripción del creador (original en inglés)
What fills your agent's context window before a session starts: skill descriptions, memory files.
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.
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": {
"whats-loaded": {
"command": "npx",
"args": [
"-y",
"whats-loaded-mcp"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add whats-loaded -- npx -y whats-loaded-mcpPégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"whats-loaded": {
"command": "npx",
"args": [
"-y",
"whats-loaded-mcp"
]
}
}
}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": {
"whats-loaded": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"whats-loaded-mcp"
]
}
}
}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 9 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub stcmain, 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.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
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 (0.2.5) llegó al registro hace 3 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: Agent-Native Calendar, Excel MCP Server, MCP Server for Excel
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:↓ Descargas por semanai★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
Agent-Native Google Calendar - manage events, sync, and public booking
Create and edit Excel files with AI: charts, PivotTables, formulas. No Excel needed.
Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.
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.
Your context window is already half spent before you type. An MCP server that shows what is consuming it — every skill description, every memory file and its hidden @imports, every configured MCP server — ranked by cost, with duplicates called out.
Skills are cheap to install and permanently expensive to keep. A skill's name and description go into the system prompt of every session, forever — only the body is loaded on demand. Install a few hundred and you've quietly mortgaged half your window before the first message.
Nothing surfaces this. You notice it as sessions that compact sooner than they used to, and you have no idea which of the things you installed six months ago is responsible.
On the machine this was written on:
# Context budget — cost before you type a single character
~95,316 estimated tokens always loaded. For scale: ~47.7% of a 200K window, ~9.5% of a 1M window.
| Source | Count | Est. tokens |
|---|---|---|
| Skill descriptions | 1,767 | 92,884 |
| Memory files (CLAUDE.md/AGENTS.md + imports) | 3 | 2,432 |
| MCP servers configured | 10 | not measured |
| Total measurable | 95,316 |
79 duplicate skill names are costing ~9,435 tokens.
79 names were installed more than once — the same skill picked up from several sources, like agent-browser appearing three times from three authors. But a shared name does not always mean a redundant copy: on that install only 34 groups were byte-identical (~1,523 tokens genuinely recoverable), while 45 shared a name and differed in content — different work wearing the same label, where deleting a copy loses something. duplicate_skills compares content hashes and reports those two groups separately, so the cleanup advice is safe to act on rather than merely impressive.
| Tool | What it answers |
|---|---|
context_budget | The headline: how much is loaded before you type, split by source. Start here |
skill_costs | Skills ranked by token cost, so you trim where it actually pays |
duplicate_skills | The same skill installed more than once — usually pure waste |
memory_files | CLAUDE.md/AGENTS.md sizes and what their @import lines silently pull in |
mcp_servers | Every MCP server configured across your clients, and which config declares it |
Claude Desktop (one-click, no terminal): download the latest whats-loaded-mcp- .dxt from Releases and open it with Claude Desktop (double-click, or Settings → Extensions → Install Extension…). The server and its dependencies ship inside the bundle — no npm, no Node install.
Register with Claude Code (available in every session):
claude mcp add --scope user whats-loaded -- npx -y whats-loaded-mcp
Or in any MCP client config:
{
"mcpServers": { "whats-loaded": { "command": "npx", "args": ["-y", "whats-loaded-mcp"] } } }
From source
git clone https://github.com/stcmain/whats-loaded-mcp.git
cd whats-loaded-mcp npm install && npm run build
Published as whats-loaded-mcp on npm and as io.github.stcmain/whats-loaded-mcp in the MCP Registry.
One optional setting, and it takes no credentials.
| Variable | Default | Meaning |
|---|---|---|
WL_PROJECT_ROOT | the server's working directory | Directory treated as "the project" for project-scoped skills, memory files and .mcp.json. |
Personal and plugin scopes are read from ~/.claude either way. Setting this is worth it when a desktop client launches the server: the process inherits *that client's* working directory, which is rarely the project you are asking about.
{
"mcpServers": { "whats-loaded": { "command": "npx", "args": ["-y", "whats-loaded-mcp"], "env": { "WL_PROJECT_ROOT": "/path/to/the/project" } } } }
Getting this wrong in the flattering direction would be easy, so the accounting is deliberately conservative:
name + description is what loads at startup. The body of a SKILL.md is fetched on demand and is not counted, even though it is 100× larger.config.toml) are not parsed.~/.claude). The MCP inventory reads Claude Desktop, Cursor, Windsurf and VS Code configs too, but skill accounting is Claude Code's model.This server's output goes straight into a model's context, so the interesting risk is not what it does to your machine — it is what it hands to the model.
exec, no shell, and no outbound connection anywhere in the codebase.homedir() or cwd(). The only model-controlled parameters are a clamped integer and a substring matched in memory against names already collected. Path traversal is not possible because there is no path construction to traverse.CLAUDE.md routinely contains private operational detail. This server reports size and the import graph, never a line of content.Built by Shift The Culture — we run a one-person company on AI agents and ship the tooling we needed ourselves. This server is free and MIT-licensed, no strings.
It has three siblings, all also free and MIT:
The rest of that tooling is paid:
The server above stays free and MIT either way — it has no upsell in it, no telemetry, and no dependency on the paid kits.
This server is MIT and stays MIT. There is no pro edition, no telemetry, and nothing held back from the free build. Sponsorship is how the maintenance gets paid for without any of that changing.
No sponsors yet — the first slot is open. Company sponsors get their name or logo in this section, in the two sibling servers, and on the sponsor page. Tiers, exactly what the placement is, and what it explicitly does not buy: https://shifttheculture.media/sponsor
Individuals: https://paypal.me/ShiftTheCultureLLC — any amount, no perks, no tier.
MIT © Zachary Pampu