Sauce Labs MCP Server

A Model Context Protocol (MCP) server that provides comprehensive integration with the Sauce Labs testing platform. This package includes two complementary MCP servers enabling AI assistants to interact with Sauce Labs' device cloud, manage test jobs, analyze builds, and monitor testing infrastructure through natural language conversations.

Servers

This package provides two separate MCP servers optimized for different use cases:

sauce-api-mcp (Core Server) — Full Sauce Labs API integration for account management, device discovery, job analysis, builds, storage, and tunnels.

sauce-api-mcp-rdc (RDC Server) — Real Device Cloud (RDC) focused server. Dynamically generates MCP tools at startup from the official Sauce Labs OpenAPI spec using FastMCP with an OpenAPIProvider, so the tool set is always up-to-date without code changes. Includes a small set of handwritten tools for endpoints that need special handling (binary payloads, session lifecycle, app installation polling).

Both servers can be configured simultaneously in your LLM client for full Sauce Labs coverage.

Features

🚀 Core Capabilities

• Account Management: View account details, team information, and user permissions
• Device Cloud Access: Browse 300+ real devices (iOS, Android) and virtual machines
• Test Job Management: Retrieve recent jobs, analyze test results, and debug failures
• Build Monitoring: Track build status, view job collections, and analyze test suites
• Storage Management: Manage uploaded apps and test artifacts
• Tunnel Monitoring: Check Sauce Connect tunnel status and configuration

🔧 Advanced Features

• Real-time Device Status: Monitor device availability and usage across data centres
• Cross-platform Testing: Support for both Virtual Device Cloud (VDC) and Real Device Cloud (RDC)
• Test Analytics: Detailed job information including logs, videos, and performance metrics
• Team Collaboration: Multi-team support with proper access controls
• Dynamic RDC API: sauce-api-mcp-rdc auto-discovers the latest RDC v2 endpoints from the OpenAPI spec at startup; the cached spec is used as a fallback when the network is unavailable
• Response shaping: Large API list responses are automatically truncated to keep LLM context budget under control ( configurable via SAUCE_MCP_MAX_RESPONSE_ITEMS)
• File safety: File push/pull operations on devices are restricted to ~/.sauce-mcp/files/ to prevent path traversal

Prerequisites

• Python 3.10+
• pip
• Sauce Labs account with API access
• Claude Desktop, Gemini CLI, Goose, or another MCP-compatible LLM client

Installation

Install the package from PyPI:

pip install sauce-api-mcp

This installs both servers and registers their command-line entry points:

• sauce-api-mcp — core server
• sauce-api-mcp-rdc — RDC OpenAPI server

Verify installation:

which sauce-api-mcp
which sauce-api-mcp-rdc

Configuration for LLM Clients

Claude Desktop (Mac / Linux / Windows)

1. Locate your Claude Desktop config file:

   • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
   • Windows: %APPDATA%\Claude\claude_desktop_config.json
   • Linux: ~/.config/Claude/claude_desktop_config.json

2. Find your Python installation's bin directory:

   python3 -c "import sys; print(sys.prefix + '/bin')"
   

3. Add both servers to your config:

   {
     "mcpServers": {
       "sauce-api-mcp-core": {
         "command": "/path/to/bin/sauce-api-mcp",
         "env": {
           "SAUCE_USERNAME": "your-sauce-username",
           "SAUCE_ACCESS_KEY": "your-sauce-access-key"
         }
       },
       "sauce-api-mcp-rdc": {
         "command": "/path/to/bin/sauce-api-mcp-rdc",
         "env": {
           "SAUCE_USERNAME": "your-sauce-u
   

... View full README on GitHub