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capsolver-mcp

capsolver-mcp

Local
capsolver.comBrowser Automation3Updated 6w ago

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

  1. 01Solve captchas by type and site parameters
  2. 02Detect captchas on a page
  3. 03Solve and autofill page captchas
  4. 04Check balance and packages
  5. 05List supported captcha types

Use cases

  1. 01Let an AI agent solve a captcha from site parameters
  2. 02Inspect a page for captcha types
  3. 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.

mcp.json · Universal config
{
"mcpServers": {
"capsolver-ai-capsolver": {
"command": "uvx",
"args": [
"capsolver-mcp"
],
"env": {
"CAPSOLVER_API_KEY": "<CAPSOLVER_API_KEY>"
}
}
}
}
Run commanduvx capsolver-mcp
Environment variables to set
CAPSOLVER_API_KEYSecretYour CapSolver API key

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
pypicapsolver-mcp0.1.3

Tools

5

Saved tool list · updated 2w ago

ParameterTypeRequiredDescription
cdataanyNo
proxyanyNo
s_tokenanyNo
timeoutanyNo
versionanyNo
invisibleanyNo
min_scoreanyNo
enterpriseanyNo
user_agentanyNo
page_actionanyNo
website_keystringYes
website_urlstringYes
captcha_typestringYes
polling_intervalanyNo

Details

From the project README

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 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

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:

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

Markdown supported

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.