Capsolver MCP server

capsolver-mcp

<!-- mcp-name: io.github.capsolver-ai/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

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: 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 claudedesktopconfig.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

Browser-based tools (detectcaptchas, solveon_page) require the browser extra:

pip install capsolver-mcp[browser]
playwright install chromium

Development

Shortened. The full README is on GitHub.