ticktockbent/charlotte repository overview

⁠Charlotte

The Web, Readable.

Charlotte is an MCP server that renders web pages into structured, agent-readable representations using headless Chromium. It exposes the browser's semantic understanding — accessibility tree, layout geometry, interactive elements — to AI agents via Model Context Protocol⁠ tools, enabling navigation, observation, and interaction without vision models or brittle selectors.

⁠Why Charlotte?

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 takes a different approach. It 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 (336 characters for Hacker News) instead of the full element dump (61,000+ characters). When it needs specifics, it asks for them.

⁠Benchmarks

Charlotte v0.2.0 vs Playwright MCP, measured by characters returned per tool call on real websites:

Navigation (first contact with a page):

Charlotte's navigate returns minimal detail by default — landmarks, headings, and interactive element counts grouped by page region. Enough to orient, not enough to overwhelm. On Wikipedia, that's 135x smaller than Playwright's response.

Observation (when the agent needs full detail):

Even at full summary detail, Charlotte's structured format is ~2x smaller than Playwright's raw accessibility dump — while providing typed metadata, form structures, and content summaries that a flat tree doesn't.

The workflow difference: Playwright agents receive 61K+ characters every time they look at Hacker News, whether they're reading headlines or looking for a login button. Charlotte agents get 336 characters on arrival, call find({ type: "link", text: "login" }) to get exactly what they need, and never pay for the rest.

⁠How It Works

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.

⁠Features

Navigation — navigate, back, forward, reload

Observation — observe (3 detail levels), find (spatial + semantic search), screenshot, diff (structural comparison against snapshots)

Interaction — click, type, select, toggle, submit, scroll, hover, key, wait_for (async condition polling)

Session Management — tabs, tab_open, tab_switch, tab_close, viewport (device presets), 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)

⁠Quick Start

⁠Prerequisites

• Node.js >= 22
• npm

⁠Installation

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

# Debian (if you need glibc compatibility)
docker pull ticktockbent/charlotte:debian

# Or from GHCR
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

⁠Run

Charlotte communicates over stdio using the MCP protocol:

# If installed globally
charlotte

# If installed from source
npm start

⁠MCP Client Configuration

Add Charlotte to your MCP client configuration. For Claude Code, create .mcp.json in your project root:

{
  "mcpServers": {
    "charlotte": {
      "type": "stdio",
      "command": "npx",
      "args": ["@ticktockbent/charlotte"],
      "env": {}
    }
  }
}

For Claude Desktop, add to claude_desktop_config.json:

{
  "mcpServers": {
    "charlotte": {
      "command": "npx",
      "args": ["@ticktockbent/charlotte"]
    }
  }
}

See docs/mcp-setup.md⁠ for the full setup guide, including development mode, generic MCP clients, verification steps, and troubleshooting.

⁠Usage Examples

Once connected, an agent can use Charlotte's tools:

⁠Browse a website

navigate({ url: "https://example.com" })
// → 612 chars: landmarks, headings, interactive element counts

find({ type: "link", text: "More information" })
// → just the matching element with its ID

click({ element_id: "lnk-a3f1" })

⁠Fill out a form

navigate({ url: "https://httpbin.org/forms/post" })
find({ type: "text_input" })
type({ element_id: "inp-c7e2", text: "[email protected]" })
select({ element_id: "sel-e8a3", value: "option-2" })
submit({ form_id: "frm-b1d4" })

⁠Local development feedback loop

dev_serve({ path: "./my-site", watch: true })
observe({ detail: "full" })
dev_audit({ checks: ["a11y", "contrast"] })
dev_inject({ css: "body { font-size: 18px; }" })

⁠Page Representation

Charlotte returns structured representations with three detail levels that let agents control how much context they consume:

⁠Minimal (default for navigate)

Landmarks, headings, and interactive element counts grouped by page region. Designed for orientation — "what's on this page?" — without listing every element.

{
  "url": "https://news.ycombinator.com",
  "title": "Hacker News",
  "viewport": { "width": 1280, "height": 720 },
  "structure": {
    "headings": [{ "level": 1, "text": "Hacker News", "id": "h-a1b2" }]
  },
  "interactive_summary": {
    "total": 93,
    "by_landmark": {
      "(page root)": { "link": 91, "text_input": 1, "button": 1 }
    }
  }
}

⁠Summary (default for observe)

Full interactive element list with typed metadata, form structures, and content summaries.

{
  "url": "https://example.com/dashboard",
  "title": "Dashboard",
  "viewport": { "width": 1280, "height": 720 },
  "structure": {
    "landmarks": [
      { "role": "banner", "label": "Site header", "bounds": { "x": 0, "y": 0, "w": 1280, "h": 64 } },
      { "role": "main", "label": "Content", "bounds": { "x": 240, "y": 64, "w": 1040, "h": 656 } }
    ],
    "headings": [{ "level": 1, "text": "Dashboard", "id": "h-1a2b" }],
    "content_summary": "main: 2 headings, 5 links, 1 form"
  },
  "interactive": [
    {
      "id": "btn-a3f1",
      "type": "button",
      "label": "Create Project",
      "bounds": { "x": 960, "y": 80, "w": 160, "h": 40 },
      "state": {}
    }
  ],
  "forms": []
}

⁠Full

Everything in summary, plus all visible text content on the page.

⁠Detail Levels

Navigation tools default to minimal. The observe tool defaults to summary. Both accept an optional detail parameter to override.

⁠Element IDs

Element IDs are stable across minor DOM mutations. They're generated by hashing a composite key of element type, ARIA role, accessible name, and DOM path signature:

btn-a3f1  (button)    inp-c7e2  (text input)
lnk-d4b9  (link)      sel-e8a3  (select)
chk-f1a2  (checkbox)  frm-b1d4  (form)

IDs survive unrelated DOM changes and element reordering within the same container. When an agent navigates at minimal detail (no individual element IDs), it uses find to locate elements by text, type, or spatial proximity — the returned elements include IDs ready for interaction.

⁠Development

# Run in watch mode
npm run dev

# Run all tests
npm test

# Run only unit tests
npm run test:unit

# Run only integration tests
npm run test:integration

# Type check
npx tsc --noEmit

⁠Project Structure

src/
  browser/          # Puppeteer lifecycle, tab management, CDP sessions
  renderer/         # Accessibility tree extraction, layout, content, element IDs
  state/            # Snapshot store, structural differ
  tools/            # MCP tool definitions (navigation, observation, interaction, session, dev-mode)
  dev/              # Static server, file watcher, auditor
  types/            # TypeScript interfaces
  utils/            # Logger, hash, wait utilities
tests/
  unit/             # Fast tests with mocks
  integration/      # Full Puppeteer tests against fixture HTML
  fixtures/pages/   # Test HTML files

⁠Architecture

The Renderer Pipeline is the core — it calls extractors in order and assembles a PageRepresentation:

1. Accessibility tree extraction (CDP Accessibility.getFullAXTree)
2. Layout extraction (CDP DOM.getBoxModel)
3. Landmark, heading, interactive element, and content extraction
4. Element ID generation (hash-based, stable across re-renders)

All tools go through renderActivePage() which handles snapshots, reload events, and response formatting.

⁠Sandbox

Charlotte includes a test website in tests/sandbox/ that exercises all 30 tools without touching the public internet. Serve it locally with:

dev_serve({ path: "tests/sandbox" })

Four pages cover navigation, forms, interactive elements, delayed content, scroll containers, and more. See docs/sandbox.md⁠ for the full page reference and a tool-by-tool exercise checklist.

⁠Known Issues

Tool naming convention — Charlotte uses : as a namespace separator in tool names (e.g., charlotte:navigate, charlotte:observe). MCP SDK v1.26.0+ logs validation warnings for this character, as the emerging SEP standard⁠ restricts tool names to [A-Za-z0-9_.-]. This does not affect functionality — all tools work correctly — but produces stderr warnings on server startup. Will be addressed in a future release to comply with the SEP standard.

Iframe content not captured — Charlotte reads the main frame's accessibility tree only. Content inside iframes (same-origin or cross-origin) is not included in the page representation. See the Roadmap for planned iframe support.

Shadow DOM — Open shadow DOM works transparently. Chromium's accessibility tree pierces open shadow boundaries, so web components (e.g., GitHub's <relative-time>, <tool-tip>) render their content into Charlotte's representation without special handling. Closed shadow roots are opaque to the accessibility tree and will not be captured.

⁠Roadmap

Screenshot Artifacts — Save screenshots as persistent file artifacts rather than only returning inline data, enabling agents to reference and manage captured images across sessions.

Video Recording — Record interactions as video, capturing the full sequence of agent-driven navigation and manipulation for debugging, documentation, and review.

ARM64 Docker Images — Add linux/arm64 platform support to the Docker publish workflow for native performance on Apple Silicon Macs and ARM servers.

Iframe Content Extraction — Traverse child frames via CDP to include iframe content in the page representation. Currently, Charlotte only reads the main frame's accessibility tree; same-origin and cross-origin iframe content is invisible.

⁠Full Specification

See docs/CHARLOTTE_SPEC.md⁠ for the complete specification including all tool parameters, the page representation format, element identity strategy, and architecture details.

⁠License

MIT⁠

⁠Contributing

See CONTRIBUTING.md⁠ for guidelines.