PictMCP
io.github.takeyaqa由 GitHub 帳號 takeyaqa 發布v0.6.0更新於 Oct 24, 2026
Provides pairwise combinatorial testing capabilities to AI assistants.
概覽
一個本機 MCP 伺服器,使用編譯為 WebAssembly 的 Microsoft PICT 演算法,為 AI 助理產生成對組合測試案例。
- 可以做什麼
- 透過 generate-test-cases 工具,依參數與其值產生最佳化的成對測試案例,並以結構化 JSON 回傳,方便整合進測試設計流程。
- 適用情境
- 適合在與 AI 助理一同設計測試案例時使用,希望取得確定且演算法正確的成對涵蓋,而非依賴模型的組合數學能力,也適用於需要以限制條件排除無效組合的情境。
- 執行需求
- 透過 npx(npm 套件 pictmcp)以 stdio 在本機執行;需要 Node.js v22 或以上版本。無需帳號、API 金鑰或網路存取。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 PictMCP,將其新增到工作區。
- 為需要使用其工具的對話啟用該服務。
Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。
其他 MCP 客戶端
參照 儲存庫 中的啟動說明。
README
PictMCP
[!CAUTION] This package has been archived and will no longer be maintained. Please consider using takeyaqa/tester-skills.
Pairwise testing for your AI assistant
PictMCP is an MCP server for software developers who design test cases with AI assistants, providing reliable, algorithm-correct pairwise test generation.
Why use this?
- AI is great at test design, but not at combinatorial math.
- Pairwise generation must be deterministic and correct.
- PictMCP separates thinking (AI) from calculation (PICT).
Prefer a GUI? Check out PictRider.
Features
- 🔒 Local Processing - All processing runs locally with no external network calls
- ⚡ WebAssembly Powered - Fast execution using Microsoft's PICT algorithm compiled to WebAssembly
- 🔗 Constraint Support - Define constraints to filter out invalid parameter combinations
- 📊 Structured Output - Returns well-structured JSON results for easy integration
Installation
Prerequisites
- Node.js (v22 or higher)
MCP Client Configuration
Add the following configuration to your MCP client. This is an example configuration; the exact format may vary depending on your client. Please refer to your MCP client's documentation for details.
Quick Start
Once installed, you can ask your AI assistant to generate test cases using pairwise combinatorial testing.
Example Prompt
Generate test cases for a login form with the following parameters:
- Browser: Chrome, Firefox, Safari
- OS: Windows, macOS, Linux
- Language: English, Japanese, Spanish
The AI assistant will use the generate-test-cases tool to create an optimized set of test cases that covers all pairwise combinations.
Example Result
AI assistants typically format the results as a table:
Example with Constraints
Generate test cases for:
- Browser: Chrome, Firefox, Safari
- OS: Windows, macOS, Linux
- Language: English, Japanese, Spanish
With constraint: Safari only works on macOS
You can describe constraints in plain language — the AI assistant will convert them into PICT constraint syntax automatically.
FAQ
Does this communicate with external servers?
No. All processing runs locally with no external network calls.
I already use the pict CLI. Do I need this?
If your AI agent can execute CLI commands directly, you may not need this tool. However, PictMCP provides:
- A standardized MCP interface for AI assistants
- No need to install PICT separately (WebAssembly-based)
- Structured JSON output instead of TSV
What is pairwise testing?
Pairwise testing (also known as all-pairs testing) is a combinatorial testing method that generates test cases covering all possible pairs of input parameters. This significantly reduces the number of test cases while maintaining high defect detection rates.
What constraint syntax is supported?
You don't need to write PICT syntax directly. Simply describe constraints in natural language and your AI assistant will handle the conversion. PictMCP supports the full PICT constraint syntax. See the PICT documentation for details.
License
This project is licensed under the MIT License—see the LICENSE file for details.
Disclaimer
PictMCP is provided "as is", without warranty of any kind. The authors are not liable for any damages arising from its use.
Generated test cases do not guarantee complete coverage or the absence of defects. Please supplement pairwise testing with other strategies as appropriate.
PictMCP is an independent project and is not affiliated with Microsoft Corporation.
If you find PictMCP useful, please consider starring the repository.
來源:README.md,提交 4d2dc38
工具
0版本歷史
1- v0.6.0最新Sep 16, 2026
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