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  1. Home
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  4. README

Capsolver MCP README

The full upstream README, mirrored here for reference. Install config, tool schemas, adoption signals, and an original overview live on the Capsolver MCP listing page.

Back to Capsolver MCP View source on GitHub

capsolver-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

Terminal
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:

server.ts
# 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

bash
# 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

Code
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

server.ts
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: host and port are constructor parameters on create_server() (forwarded to FastMCP), matching the MCP Python SDK 1.x API.

Configure in Claude Desktop

Add to your claude_desktop_config.json:

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

ToolBrowser?Description
solve_captchaNoSolve a captcha by type + site params (token mode)
detect_captchasYesScan a page URL and list present captcha types
solve_on_pageYesDetect + solve + autofill all captchas on a page
get_balanceNoCheck account balance and packages
get_supported_captchasNoList all supported captcha types and handlers

Browser-based tools (detect_captchas, solve_on_page) require the browser extra:

Terminal
pip install capsolver-mcp[browser]
playwright install chromium

Development

bash
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