Browser Use
Lets AI do web tasks for you, such as filling forms, searching and extracting data, in the maker’s cloud browsers or on your computer.
Description from the maker (original English)
Renders web pages into structured, agent-readable representations using headless Chromium.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
You need
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"charlotte": {
"command": "npx",
"args": [
"-y",
"@ticktockbent/charlotte"
]
}
}
}Run this in your terminal
claude mcp add charlotte -- npx -y @ticktockbent/charlottePaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"charlotte": {
"command": "npx",
"args": [
"-y",
"@ticktockbent/charlotte"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"charlotte": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@ticktockbent/charlotte"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
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These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026
The registry name was verified with the GitHub account ticktockbent, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.1.3) reached the registry 9 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
In the same category: Browser Use, Chrome DevTools MCP, MCP Server Browser
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Lets AI do web tasks for you, such as filling forms, searching and extracting data, in the maker’s cloud browsers or on your computer.
Lets AI use Chrome’s developer tools to inspect pages, find what makes them slow and spot errors. Made by the Chrome DevTools team.
MCP server for browser use access
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
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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