Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Beschreibung vom Entwickler (englisches Original)
Renders web pages into structured, agent-readable representations using headless Chromium.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"mcpServers": {
"charlotte": {
"command": "npx",
"args": [
"-y",
"@ticktockbent/charlotte"
]
}
}
}Führe das in deinem Terminal aus
claude mcp add charlotte -- npx -y @ticktockbent/charlotteIn .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"charlotte": {
"command": "npx",
"args": [
"-y",
"@ticktockbent/charlotte"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"charlotte": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@ticktockbent/charlotte"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 7. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto ticktockbent bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.1.3) kam vor 9 Monaten in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Node.js auf deinem Computer.
In derselben Kategorie: Spec Driven Development, Remote Desktop Commander, Dialyne
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
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.
Real phone calls in France for AI agents: dial +33 numbers, menus, hold, AI disclosure.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
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":
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