Renders web pages into structured, agent-readable representations using headless Chromium.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
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π‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
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 β 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 β landmarks, headings, interactive elements, forms, content summaries β 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 β 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 β 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 ~10β140x 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 β 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 | β |
| 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:
Agents receive landmarks, headings, interactive elements with typed metadata, bounding boxes, form structures, and content summaries β all derived from what the browser already knows about every page.
Navigation β navigate, back, forward, reload
Observation β 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) β 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 β console (all severity levels, filtering, timestamps), requests (full HTTP history, method/status/resource type filtering)
Session Management β 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 β dev_serve (static server + file watching with auto-reload), dev_inject (CSS/JS injection), dev_audit (a11y, performance, SEO, contrast, broken links)
Utilities β 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%.
Agents can activate more tools mid-session without restarting:
Run Charlotte as a remote MCP server and connect it to claude.ai β one command:
It prints a public connector URL and an operator token. In claude.ai: Settings β Connectors β Add custom connector β 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 β 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:
Docker images are available on Docker Hub and GitHub Container Registry:
Or install from source:
Charlotte communicates over stdio using the MCP protocol:
Create .mcp.json in your project root:
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