captcha-mcp-test
MCP server for solving captchas via CapMonster Cloud. It
is the solve brain: it lists supported captcha types, serves CapMonster's docs,
and creates/polls solve tasks against the CapMonster Cloud REST API. It has no
browser of its own — pair it with a browser-driving MCP (e.g.
mcp-patchright-mainworld)
that does the page work (navigation, interaction, reading the live DOM/network, and
injecting the solved token back into the page).
Quick start
{
"mcpServers": {
"capmonster": {
"command": "uvx",
"args": ["captcha-mcp-test"],
"env": { "CM_API_KEY": "YOUR_API_KEY" }
}
}
}
uvx runs the published PyPI package with no local clone needed. See
mcp.json for a full example that also wires up the patchright
companion browser MCP.
Configuration
This server only runs over stdio (the transport MCP clients use to launch it as a
subprocess), so there are no HTTP headers to carry a per-request key — set
CM_API_KEY in the client's env block (see mcp.json) and every tool
call in that session uses it.
Tools
get_supported_tasks— list captcha task types CapMonster supports (from the live OpenAPI spec).get_task_parameters(task_type)— required/optional fields, variant notes, and the solution schema for a task type.get_docs(url, offset, limit, section)— fetch a CapMonster doc page (docs.capmonster.cloud/api.capmonster.cloudonly), with section-jump and pagination.create_task(task)— submit a captcha task, returns ataskId.get_task_result(task_id)— poll a task once.get_task_result_wait(task_id, timeout_seconds, poll_interval_seconds)— poll a task to completion (preferred over driving the loop yourself).get_actual_user_agent()— fetch a current Windows User-Agent to use as one consistent fingerprint across the browser and the solve task.get_balance()— CapMonster account balance.
Workflow
capmonster_agent/SKILL.md is the step-by-step
procedure for analyzing a captcha-protected page and solving it with this server
paired with a patchright (or any stateful browser-automation) MCP.
capmonster_agent/PROMPT.md is a copy-paste prompt
that sets an agent up with both servers and points it at the skill.
Development
python -m venv .venv
.venv\Scripts\activate # or source .venv/bin/activate on Linux/macOS
pip install -e ".[dev]"
pytest
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