MCP Server for CapSolver - captcha-solving capabilities for AI agents
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.
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
# 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
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)
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.
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.
| 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
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
MIT
Source-derived launch command. Check the maintainer’s required arguments and credentials before running:
uvx capsolver-mcpMerge this template into ~/Library/Application Support/Claude/claude_desktop_config.json. Keep existing servers. Add any arguments, credentials, and permissions required by the maintainer; this template has not been install-tested.
{
"mcpServers": {
"io-github-capsolver-ai-capsolver-mcp": {
"command": "uvx",
"args": [
"capsolver-mcp"
]
}
}
}Restart Claude Desktop completely for changes to take effect. Confirm the server appears connected in the client’s tool list, then try a read-only example from its documentation.
Claude Desktop setup referencecapsolver-mcppypiio.github.capsolver-ai/capsolver-mcp works with any MCP-compatible client. Copy the config snippet from the Configuration section above and add it to the file shown for your client, then restart the application.
~/Library/Application Support/Claude/claude_desktop_config.jsonRestart Claude Desktop completely for changes to take effect.~/.cursor/mcp.jsonRestart Cursor for changes to take effect..vscode/mcp.jsonReload VS Code window for changes to take effect.~/.codeium/windsurf/mcp_config.jsonRestart Windsurf for changes to take effect..mcp.jsonSave at the project root, then start Claude Code in that project and review the MCP server approval prompt. Keep real credentials out of shared files.