About substrate-browser
substrate-browser is an MCP server for AI agents that controls a headless Chromium browser. It returns a compact semantic graph with element IDs and coordinates, then supports page interaction without CSS selectors or XPath.
Key features
- 01Compact semantic page graph
- 02Element IDs and pixel coordinates
- 03Click, type, and select controls
- 04Scrolling and keyboard input
- 05Screenshots and browser history
Use cases
- 01Inspecting web pages with less HTML noise
- 02Filling forms and choosing dropdowns
- 03Navigating pages through element IDs
MCP support
Exposes browser navigation and interaction as MCP tools, including page extraction, clicking, typing, selection, scrolling, screenshots, and history controls.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
npx -y substrate-browserSUBSTRATE_PROXYOptional egress proxy URL (http/socks) to route all Chromium traffic through, mitigating SSRF and DNS rebinding risks.SUBSTRATE_VIEWPORT_WIDTHBrowser viewport width in pixels (Default: 1280)SUBSTRATE_VIEWPORT_HEIGHTBrowser viewport height in pixels (Default: 800)Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMESubstrate
Stop wasting 48K tokens to read a webpage. Substrate compresses a typical content page into roughly 1–4K tokens your LLM can actually use — vs. ~48K of raw HTML.
Substrate is an MCP server that gives your AI agent eyes and hands on the web. It extracts a compressed semantic graph of any webpage — buttons, inputs, links, dropdowns, checkboxes — with precise pixel coordinates, and handles clicking, typing, and selection via spatial coordinates. No CSS selectors. No xpaths. No hallucination.
Why It Matters
Every other browser automation approach burns tokens on noise:
| Approach | Tokens | Extraction | What Your LLM Gets |
|---|---|---|---|
Raw HTML (page.content()) | ~48,000 | 5ms | Full DOM tree — scripts, styles, hidden elements, ad markup. LLM drowns in noise and hallucinates clicks on invisible elements. |
| Vision (screenshot + OCR) | ~8,000 | ~800ms | A pixel blob. LLM can "see" the page but can't target anything precisely. Clicks land 20px off. Forms fail. |
| Substrate | ~1,000–4,000 | ~10–30ms | Structured JSON: what each element is, where it is, what state it's in. LLM clicks the right thing on the first try. |
The math: a ~110-element content page (say, Wikipedia) compresses to roughly ~2,300 tokens — about 1.8% of a typical 128K context window. You can fit roughly ~55 page extractions before the LLM runs out of room. With raw HTML, you get 2.
Token figures are order-of-magnitude, measured live on representative pages (example.com ~84 tok, Wikipedia ~3.5K, Hacker News front page ~4.4K, extraction 8–58ms). They scale with page density; the extractor caps output at MAX_ELEMENTS=400, so very dense pages are truncated rather than emitted in full. The math is arithmetic: on a ~2.3K-token page, ⌊128K/2.3K⌋ ≈ 55 extractions.
The real win — shorter action loops:
Without Substrate: With Substrate:
navigate → screenshot navigate
→ "I see a button" → click (wrong) → {btn id=3 "Submit" [640,400]}
→ screenshot → "ah, more right" → click(3) → done.
→ click → "not that either"
→ screenshot → ... 2 tool calls. Task complete.
8-12 tool calls. Task complete.
That's not a marginal improvement. That's 5-6x fewer API calls, 5-6x less latency, and 5-6x lower cost per web task.
How It Works
Substrate runs as a headless Chromium browser via the Model Context Protocol (MCP). Your LLM agent talks to it through 10 simple tools:
| Tool | What It Does |
|---|---|
navigate | Load a URL, get back the page graph (capped at 400 elements) |
click | Click any element by its numeric ID |
type_text | Type into an input field (auto-clears first) |
select_option | Pick a dropdown option by value |
press_key | Press a keyboard key (Escape, Enter, Tab, arrows, modifiers) |
scroll | Scroll up/down by 80% of viewport |
screenshot | Get a visual snapshot + the graph together |
go_back / go_forward | Browser history navigation |
get_current_url | Check where you are |
Every navigation and interaction tool returns the same compressed graph (get_current_url returns just the URL; screenshot returns the image plus the graph). Your LLM reads the graph, picks an element ID, and calls the next tool. No image interpretation. No HTML parsing. Just IDs and coordinates.
Installation & Setup
Substrate is a standalone Model Context Protocol (MCP) server. You do not need to write code to use it — you just plug it into your AI assistant.
Option 1: Claude Desktop (Recommended)
- Open your Claude Desktop configuration file:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json
- macOS:
- Add the
substrate-browserserver to themcpServersblock:
{
"mcpServers": {
"substrate-browser": {
"command": "npx",
"args": ["-y", "substrate-browser"]
}
}
}
- Restart Claude Desktop. You will now see the 10 browser tools available (a small hammer icon) and you can ask Claude to "Go to example.com and tell me what you see".
(Note: Playwright will automatically download the Chromium binary on the very first run. This requires Node.js 20+ installed on your system).
Option 2: Running from Source (For Developers)
If you want to modify the extraction logic or add your own tools:
git clone https://github.com/manuelinuxkr/substrate-b.git
cd substrate-b
npm install
npx playwright install chromium
npm run build
npm start
License
MIT
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.