Lets AI agents browse the web as short, numbered text instead of screenshots.

It works with Claude Code, Codex, Cursor or your own agent as an MCP server. Install in two commands.

npx -y -p mantis-browser mantis install
claude mcp add mantis -- npx -y -p mantis-browser mantis-mcp
npx -y -p mantis-browser mantis read https://example.com   # try it without an agent

Windows, Linux servers and other agents: SETUP.

Side-by-side replay of the same task with Mantis and Playwright MCP: Mantis finishes in 11 calls and about 238k input tokens, Playwright MCP in 25 calls and about 887k

One real task (Luna, each tool’s median run of 5 by input tokens, replayed): about half the time, over 3.5x fewer input tokens, less than half the calls. Across all 5 runs: 3-5x fewer tokens, about half the time, 11-12 calls vs 21-29. This is a selected example from 16 long tasks; medians across all 16 are in Results. Full video.

Security and threat model: SECURITY.md.

How it works

Agent sends open/click to Mantis; Mantis reads the page in Chromium, numbers each control and returns only what changed; CAPTCHA, 2FA and payment go to you

What the agent sees

A shop page with a cookie popup becomes 8 numbered lines; after click #3 only the changes come back

Results

Mantis vs the accessibility tree (Playwright MCP) on public sites, gpt-6-luna and claude-haiku-5-5. Every cell is a per-run median; time is end-to-end wall time per run:

0.1.13: headline numbers are 0.1.9's; later builds checked on Dickens (Luna, Haiku), the capability-v1 local set and the visual-live-v1 real-site set.

Long tasks (correct: 14 keyed tasks, 42 runs per cell; medians: all 16 tasks, 48 runs per cell; both approaches run in the same session):

	Luna Mantis	Luna tree	Haiku Mantis	Haiku tree
Correct	35/42	34/42	40/42	40/42
Input tokens (median)	244k	345k	268k	506k
Tool calls (median)	17	24	19	30
Time (median)	42s	66s	54s	85s

Short tasks (30 tasks, 90 runs per cell; tree and screenshot columns are the earlier 20261026 run):

	Luna Mantis	Luna tree	Luna screenshot	Haiku Mantis	Haiku tree	Haiku screenshot
Correct	88/90	86/90	90/90	90/90	88/90	88/90
Input tokens (median)	64k	99k	104k	38k	88k	33k
Tool calls (median)	3	4	7	3	5	6
Time (median)	16s	31s	35s	19s	30s	23s

Versus the accessibility tree:

Long tasks: accuracy within one run, 29-47% fewer input tokens, 29-37% fewer calls, about a third less time.
Short tasks: accuracy equal or better, 35-57% fewer input tokens.

Versus screenshots:

Luna: screenshots score 2 runs higher but use more tokens and time.
Haiku: screenshots use fewer tokens.

Caveats:

Short-task times compare a newer Mantis build with the earlier tree and screenshot run, so treat that time gap as indicative.
Scores come from deterministic answer keys on the final page state. Two long iframe/tab tasks can't be keyed and are left out of the long-task counts.
Method and full caveats: bench/RESULTS.md.

Use your own Chrome

Optional. Mantis can drive your real Chrome (your tabs, your sign-ins) instead of launching a fresh browser:

Run npx -y -p mantis-browser mantis chrome. It starts Chrome on 127.0.0.1:9222 with a dedicated profile.
Add MANTIS_CDP_URL=http://127.0.0.1:9222 to the env of the Mantis MCP config.
Sign in to your sites once in that profile; sign-ins persist there.
Mantis then acts on your real tabs, so act carefully. Without the variable nothing changes.

Limitations

No canvas input: canvas, WebGL, maps and drawing apps are described only as canvas, with no coordinate click or draw tool.
Login and bot walls need ask_human, which needs a display.
Benchmarked only on read, navigate and form-fill tasks on public sites, with two models. The screenshot baseline is this project's own tool, and a few tasks were swapped after results (disclosed).
Page content is untrusted data; see SECURITY.md.
Small v0.1.x beta.

Learn more

How it works in detail
Claude skill: teaches Claude how to read Mantis output
Install, configuration and tool reference
Re-running the benchmarks

License

MIT