PictMCP

Local MCP server that generates pairwise test cases using the PICT algorithm with WebAssembly support, returning structured JSON results.

javascript

0

GitHub Stars

javascript

Language

2 months ago

First Indexed

3 weeks ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

{
  "mcpServers": {
    "takeyaqa-pictmcp": {
      "command": "npx",
      "args": [
        "pictmcp"
      ]
    }
  }
}

PictMCP is a local MCP server that provides pairwise combinatorial testing capabilities to AI assistants. It offloads complex combinatorial logic from the AI, enabling you to generate efficient test case sets while keeping all processing on your machine for privacy and speed.

How to use

You integrate PictMCP with your MCP client to perform pairwise testing. Start the local server, then configure your MCP client to point to it. Use the client’s workflow to trigger test case generation through PictMCP, and retrieve structured JSON results that you can feed back into your AI testing or test design pipelines.

How to install

Prerequisites you need before installing: a modern Node.js environment (Node.js v24 or higher). Install Node.js from the official website or your preferred package manager if you have not already installed it.

Install and run the MCP server using the following steps. Copy and paste each command into your terminal one by one.

Additional sections

Configuration and usage details help you tailor PictMCP to your testing needs. You can run the server locally with a simple command, configure your MCP client to connect to it, and use the provided tools to generate tests with pairwise coverage. The server runs without requiring any external network calls, and it returns well-structured JSON results for easy integration.

If you want practical examples, you can create prompts that define parameter sets for your testing scenarios and rely on PictMCP to produce an optimized, pairwise set of test cases. You can also apply PICT constraint syntax to exclude invalid parameter combinations when you have constraints like "Safari only works on macOS" or similar rules.

Available tools

generate-test-cases

Generates an optimized set of test cases using pairwise combinatorial testing based on the provided parameters and constraints.