About capsolver-mcp
capsolver-mcp is an MCP server that gives AI agents access to CapSolver captcha-solving functions. It provides token-based solving, browser page detection and solving, and account and captcha information tools.
Key features
- 01Solve captchas by type and site parameters
- 02Detect captchas on a page
- 03Solve and autofill page captchas
- 04Check balance and packages
- 05List supported captcha types
Use cases
- 01Let an AI agent solve a captcha from site parameters
- 02Inspect a page for captcha types
- 03Solve and autofill captchas in a browser page
MCP support
The server exposes captcha-solving and account tools to MCP clients. It supports stdio, SSE, and Streamable HTTP transports.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
5Saved tool list · updated 2w ago
| Parameter | Type | Required | Description |
|---|---|---|---|
| cdata | any | No | |
| proxy | any | No | |
| s_token | any | No | |
| timeout | any | No | |
| version | any | No | |
| invisible | any | No | |
| min_score | any | No | |
| enterprise | any | No | |
| user_agent | any | No | |
| page_action | any | No | |
| website_key | string | Yes | |
| website_url | string | Yes | |
| captcha_type | string | Yes | |
| polling_interval | any | No |
Details
From the project READMEcapsolver-mcp
MCP Server for CapSolver — expose captcha-solving capabilities to AI agents via the Model Context Protocol.
Published on PyPI as capsolver-mcp and listed in the official MCP Registry as io.github.capsolver-ai/capsolver-mcp.
See the capsolver-ai-hub repo for integration examples and the full documentation.
For detailed MCP client setup (Claude Desktop, Claude Code, Cursor, Windsurf, Cline, and more), see docs/mcp-integration.md.
Install
pip install capsolver-mcp
pip install capsolver-mcp[browser] # with Playwright support (for detect/solve_on_page)
All tools read the API key from the environment:
# bash / zsh
export CAPSOLVER_API_KEY="your-capsolver-api-key"
# PowerShell
$env:CAPSOLVER_API_KEY = "your-capsolver-api-key"
# cmd
set CAPSOLVER_API_KEY=your-capsolver-api-key
Usage
CLI
# stdio (default — for local MCP clients like Claude Desktop)
capsolver-mcp
# SSE (for remote / HTTP access)
capsolver-mcp --transport sse --host 0.0.0.0 --port 8000
# Streamable HTTP (MCP 2025-03-26 spec)
capsolver-mcp --transport streamable-http --host 0.0.0.0 --port 8000
CLI options
capsolver-mcp [OPTIONS]
--transport {stdio,sse,streamable-http}
Transport protocol (default: stdio)
--host HOST Bind host for SSE/HTTP transports (default: 127.0.0.1)
--port PORT Bind port for SSE/HTTP transports (default: 8000)
--api-key KEY API key (fallback: CAPSOLVER_API_KEY env)
--name NAME Server name (default: capsolver)
Programmatic
from capsolver_mcp.server import create_server
server = create_server(
api_key="your-key", # or set CAPSOLVER_API_KEY env var
server_name="capsolver", # name advertised to MCP clients
host="127.0.0.1", # bind host for SSE / HTTP transports
port=8000, # bind port for SSE / HTTP transports
)
server.run(transport="sse") # or "stdio" or "streamable-http"
Note:
hostandportare constructor parameters oncreate_server()(forwarded toFastMCP), matching the MCP Python SDK 1.x API.
Configure in Claude Desktop
Add to your claude_desktop_config.json:
{
"mcpServers": {
"capsolver": {
"command": "capsolver-mcp",
"env": {
"CAPSOLVER_API_KEY": "your-key"
}
}
}
}
To run without installing it globally, use "command": "uvx" with
"args": ["capsolver-mcp"] — this is what MCP clients generate from the
registry entry. See docs/mcp-integration.md for
per-client examples.
Available tools
| Tool | Browser? | Description |
|---|---|---|
solve_captcha | No | Solve a captcha by type + site params (token mode) |
detect_captchas | Yes | Scan a page URL and list present captcha types |
solve_on_page | Yes | Detect + solve + autofill all captchas on a page |
get_balance | No | Check account balance and packages |
get_supported_captchas | No | List all supported captcha types and handlers |
Browser-based tools (detect_captchas, solve_on_page) require the browser extra:
pip install capsolver-mcp[browser]
playwright install chromium
Development
git clone https://github.com/capsolver-ai/capsolver-mcp.git
cd capsolver-mcp
uv sync --all-extras # or: pip install -r requirements-dev.txt
uv run pytest # run tests
uv run ruff check src tests # lint
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.