Pictmcp
PictMCP is an MCP server that provides reliable and algorithmically correct pairwise test generation for software developers using AI assistants to design test cases. It runs Microsoft's PICT algorithm locally using WebAssembly, separating the AI's thinking from combinatorial mathematics calculations to ensure the determinacy and correctness of test generation.
rating : 2 points
downloads : 4.4K
What is PictMCP?
PictMCP is a Model Context Protocol (MCP) server specifically designed for AI assistants. It solves a key problem when AI generates test cases: AI is good at thinking about test scenarios but not good at complex combinatorial mathematics calculations. PictMCP separates the two - letting the AI handle the thinking process of test design, while Microsoft's PICT algorithm (compiled to WebAssembly) ensures the mathematical correctness and determinacy of pairwise combination testing.How to use PictMCP?
Using PictMCP is very simple: First, configure and install the PictMCP server through the MCP client. Then, you can directly describe test parameters (such as browser type, operating system, language, etc.) to your AI assistant. The AI assistant will automatically call PictMCP's `generate - test - cases` tool to generate the minimum set of test cases that cover all parameter - pair combinations. You don't need to understand complex combinatorial mathematics or manually write test matrices.Applicable scenarios
PictMCP is most suitable for the following scenarios: 1) Software testers need to design test cases for multi - parameter systems; 2) Development teams use AI assistants for test planning; 3) Need to ensure that tests cover all parameter combinations but want to minimize the number of test cases; 4) There are dependencies or constraints between test parameters (e.g., some browsers only support specific operating systems).Main features
Local processing
All test generation is completed locally without connecting to an external server, ensuring data privacy and fast response
Powered by WebAssembly
Uses Microsoft's PICT algorithm compiled to WebAssembly to provide fast and reliable pairwise combination calculations
Constraint support
Supports defining constraint relationships between parameters (e.g., Safari only supports macOS) and automatically filters out invalid combinations
Structured output
Returns results in JSON format, making it easy for AI assistants to parse and display as clear tables
Natural language interaction
Users can describe parameters and constraints in natural language, and the AI assistant automatically converts them into PICT syntax
Advantages
Separate concerns: The AI is responsible for creative thinking, and the algorithm ensures mathematical correctness
Significantly reduce the number of test cases: Pairwise testing usually covers more than 80% of defects, and the number of test cases is much less than full combinations
No need to install complex tools: Based on WebAssembly, no need to install the PICT CLI separately
Seamless integration with AI assistants: Perfectly cooperate with AI tools such as Claude and Cursor through the standard MCP protocol
Support complex constraints: Can handle various dependencies and exclusion relationships between parameters
Limitations
Only generates test case designs: Does not execute actual tests and needs to be used with a test framework
Pairwise testing does not provide 100% coverage: Although it can find most defects, it cannot guarantee to find all defects caused by multi - parameter interactions
Requires MCP client support: Users need to configure an AI assistant that supports MCP
There is a limit on the number of parameters: Although the PICT algorithm is efficient, it may still generate a large number of test cases when there are too many parameters and values
How to use
Install Node.js
Ensure that Node.js v22 or a higher version is installed on the system
Configure the MCP client
Add the PictMCP server configuration to the MCP configuration of the AI assistant (the specific configuration method varies depending on the client)
Describe test requirements
Describe your test parameters to the AI assistant, including parameter names and possible values
Add constraints (optional)
If there are constraints between parameters, describe them in natural language
Get results
The AI assistant will call PictMCP to generate test cases and display the results in a table
Usage examples
Login form testing
Design test cases for multi - platform login forms to ensure coverage of all combinations of browsers, operating systems, and languages
E - commerce checkout process testing
Test the checkout process of an e - commerce website, considering combinations of payment methods, delivery options, and user levels
Mobile app compatibility testing
Test the compatibility of mobile apps on different devices and operating system versions
Frequently Asked Questions
Does PictMCP send data to external servers?
I already have the PICT command - line tool. Do I still need PictMCP?
What is Pairwise Testing?
Do I need to learn the PICT constraint syntax?
Can pairwise testing guarantee to find all defects?
What is the relationship between PictMCP and Microsoft?
Related resources
PictMCP GitHub repository
The source code and latest version of PictMCP
PictRider GUI tool
If you prefer a graphical interface rather than an AI assistant, you can try PictRider
PICT official documentation
The complete documentation and constraint syntax of Microsoft's PICT algorithm
Model Context Protocol
The official specification of the MCP protocol
Article on pairwise testing
Understand the principle and value of pairwise testing in depth

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