Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Descripción del creador (original en inglés)
Renders web pages into structured, agent-readable representations using headless Chromium.
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": {
"charlotte": {
"command": "npx",
"args": [
"-y",
"@ticktockbent/charlotte"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add charlotte -- npx -y @ticktockbent/charlottePégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"charlotte": {
"command": "npx",
"args": [
"-y",
"@ticktockbent/charlotte"
]
}
}
}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": {
"charlotte": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@ticktockbent/charlotte"
]
}
}
}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 ticktockbent, 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 (0.1.3) llegó al registro hace 9 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, Signoff
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.
Five gates that make an agent's 'done' provable: run them, read the verdict, audit the record.
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.
The Web, Readable.
Your AI agent burns ~50,000 characters of accessibility tree just to look at the Hacker News front page. Charlotte does it in 364.
Charlotte is an MCP server that gives AI agents structured, token-efficient access to the web. Instead of dumping the full accessibility tree on every call, Charlotte returns only what the agent needs: a compact page summary on arrival, targeted queries for specific elements, and full detail only when explicitly requested. On content-heavy pages that orientation is up to ~140x smaller than a full accessibility-tree snapshot from Playwright MCP; on trivially small pages the two are roughly the same size.
Most browser MCP servers dump the entire accessibility tree on every call — a flat text blob that can exceed a million characters on content-heavy pages. Agents pay for all of it whether they need it or not.
Charlotte decomposes each page into a typed, structured representation — landmarks, headings, interactive elements, forms, content summaries — and lets agents control how much they receive with three detail levels. When an agent navigates to a new page, it gets a compact orientation (364 characters for Hacker News) instead of the full element dump (~50,000 characters). When it needs specifics, it asks for them.
Measured on Charlotte v0.8.0 against Playwright MCP v0.0.79, by characters returned per tool call on real websites (npx tsx benchmarks/run-benchmarks.ts --suite comparison), 2026-08-08. This section is a summary — the canonical benchmarks page (including per-task cost and release drift) is charlotte.mintlify.site/benchmarks; methodology, instruments, and raw results: benchmarks/.
Orientation cost (what an agent pays to "see" a page on arrival):
A Charlotte navigate returns a usable orientation by default — landmarks, headings, and interactive element counts grouped by page region. To get the equivalent with Playwright MCP, an agent calls browser_snapshot, which returns the full accessibility tree. (Playwright's browser_navigate alone returns only a short confirmation, not the page content, so it isn't a like-for-like comparison.)
| Site | Charlotte navigate | Playwright browser_snapshot | Smaller by |
|---|---|---|---|
| example.com | 415 | 465 | 1.1x |
| httpbin form | 619 | 1,847 | 3.0x |
| GitHub repo | 3,778 | 38,983 | 10x |
| Wikipedia (AI article) | 22,134 | 1,137,928 | 51x |
| Hacker News | 364 | 50,706 | 139x |
The advantage scales with page complexity: on content-heavy pages the structured orientation is ~10–140x smaller than the full snapshot, while on a trivially small page like example.com the two are within ~20% of each other (and on a page that small, the structured representation can be the larger of the two — there is simply nothing to summarize away). Charlotte's value shows up precisely where Playwright's flat dump hurts most. When an agent needs more than the orientation, it calls observe or find for exactly the part it wants instead of paying for the whole tree up front.
Tool definition overhead (invisible cost per API call):
| Profile | Tools | Def. tokens/call | Savings vs full |
|---|---|---|---|
| full | 43 | 8,500 | — |
| browse (default) | 23 | 4,372 | ~49% |
| core | 7 | 2,186 | ~75% |
Tool definitions are sent on every API round-trip. With the default browse profile, Charlotte carries ~49% less definition overhead than loading all 43 tools; the minimal core profile cuts it by ~75%. See the profile benchmark report for full results.
The workflow difference: A Playwright agent that reads the full snapshot receives ~50,000 characters every time it looks at Hacker News, whether it's reading headlines or hunting for a login button. A Charlotte agent gets 364 characters on arrival, calls find({ type: "link", text: "login" }) to get exactly what it needs, and never pays for the rest.
Charlotte maintains a persistent headless Chromium session and acts as a translation layer between the visual web and the agent's text-native reasoning. Every page is decomposed into a structured representation:
┌─────────────┐ MCP Protocol ┌──────────────────┐
│ AI Agent │<────────────────────>│ Charlotte │ └─────────────┘ │ │ │ ┌────────────┐ │ │ │ Renderer │ │ │ │ Pipeline │ │ │ └─────┬──────┘ │ │ │ │ │ ┌─────▼──────┐ │ │ │ Headless │ │ │ │ Chromium │ │ │ └────────────┘ │ └──────────────────┘
Agents receive landmarks, headings, interactive elements with typed metadata, bounding boxes, form structures, and content summaries — all derived from what the browser already knows about every page.
Navigation — navigate, back, forward, reload
Observation — observe (3 detail levels, structural tree view), find (spatial + semantic search, CSS selector mode, output_file for large result sets), screenshot (with persistent artifact management), screenshots, screenshot_get, screenshot_delete, diff (structural comparison against snapshots)
Interaction (iframe-aware) — click, click_at (coordinate-based), type (with slow typing support), select, toggle, submit, scroll, hover, drag, key (single/sequence with element targeting), wait_for (async condition polling), upload (file input), fill_form (batch form fill), dialog (accept/dismiss JS dialogs)
Monitoring — console (all severity levels, filtering, timestamps), requests (full HTTP history, method/status/resource type filtering)
Session Management — tabs, tab_open, tab_switch, tab_close, viewport (generic presets or named devices such as "iPhone 15" with DPR, touch, and user agent emulation), network (throttling, URL blocking), set_cookies, get_cookies, clear_cookies, set_headers, configure
Development Mode — dev_serve (static server + file watching with auto-reload), dev_inject (CSS/JS injection), dev_audit (a11y, performance, SEO, contrast, broken links)
Utilities — evaluate (arbitrary JS execution in page context)
Charlotte ships 43 tools (42 registered + the charlotte_tools meta-tool), but most workflows only need a subset. Startup profiles control which tools load into the agent's context, reducing definition overhead by up to ~75%.
charlotte --profile browse # 23 tools (default) — navigate, observe, interact, tabs
charlotte --profile core # 7 tools — navigate, observe, find, click, type, submit charlotte --profile full # 43 tools — everything charlotte --profile interact # 31 tools — full interaction + dialog + evaluate charlotte --profile develop # 34 tools — interact + dev_serve, dev_inject, dev_audit charlotte --profile audit # 14 tools — navigation + observation + dev_audit + viewport
Agents can activate more tools mid-session without restarting:
charlotte_tools enable dev_mode → activates dev_serve, dev_audit, dev_inject
charlotte_tools disable dev_mode → deactivates them charlotte_tools list → see what's loaded
Run Charlotte as a remote MCP server and connect it to claude.ai — one command:
docker run --cap-add SYS_ADMIN --shm-size 2g -p 3737:3737 ghcr.io/ticktockbent/charlotte
It prints a public connector URL and an operator token. In claude.ai: Settings → Connectors → Add custom connector — paste the URL, leave the OAuth Client ID/Secret fields blank, and enter the token on Charlotte's consent page when it appears. That's it; you're browsing.
The demo URL and token are ephemeral (both rotate on restart). Running it for real — stable domain, your own tunnel or reverse proxy, docker compose: Self-Hosting. Trust model and network guards: Security. Container and sandbox internals: Docker.
Charlotte is listed on the MCP Registry as io.github.TickTockBent/charlotte and published on npm as @ticktockbent/charlotte:
npm install -g @ticktockbent/charlotte
Docker images are available on Docker Hub and GitHub Container Registry:
# Alpine (default, smaller)
docker pull ticktockbent/charlotte:alpine
docker pull ticktockbent/charlotte:debian
docker pull ghcr.io/ticktockbent/charlotte:latest
Or install from source:
git clone https://github.com/ticktockbent/charlotte.git
cd charlotte npm install npm run build
Charlotte communicates over stdio using the MCP protocol:
# If installed globally (default browse profile)
charlotte
charlotte --profile core
npm start
Create .mcp.json in your project root:
{
"mcpServers": { "charlotte": { "type": "stdio", "command": "npx", "args": ["@ticktockbent/charlotte"], "env": {} } } }
Add to claude_desktop_config.json:
{
"mcpServers": { "charlotte": { "command": "npx", "args": ["@ticktockbent/charlotte"] } } }
Add to .cursor/mcp.json:
{
"mcpServers": { "charlotte": { "command": "npx", "args": ["@ticktockbent/charlotte"] } } }
Add to ~/.codeium/windsurf/mcp_config.json:
{
"mcpServers": { "charlotte": { "command": "npx", "args": ["@ticktockbent/charlotte"] } } }
Add to .vscode/mcp.json:
{
"servers": { "charlotte": { "type": "stdio", "command": "npx", "args": ["@ticktockbent/charlotte"] } } }
Add to Cline MCP settings (via the Cline sidebar > MCP Servers > Configure):
{
"mcpServers": { "charlotte": { "command": "npx", "args": ["@ticktockbent/charlotte"] } } }
Add to ~/.amp/settings.json:
{
"mcpServers": { "charlotte": { "command": "npx", "args": ["@ticktockbent/charlotte"] } } }
See docs-internal/mcp-setup.md for the full setup guide, including development mode, generic MCP clients, verification steps, and troubleshooting.
Charlotte resolves settings from four sources, highest precedence first: CLI arguments → environment variables → config file → built-in defaults. See docs/configuration.md for the complete reference.
Pass a JSON config file with --config, or drop a charlotte.config.json in the working directory and Charlotte loads it automatically:
charlotte --config charlotte.config.json
{
"browser": { "headless": true, "noSandbox": false }, "tools": { "profile": "browse" }, "rendering": { "includeIframes":
Solo se muestra el principio; lee el resto en el repo