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Hypersequent/qasphere-mcp

by Various

MCP Server for QA Sphere TMS

H

MCP

Hypersequent/qasphere-mcp

Added 1 June 2026

#mcp #mcp-server #qasphere #test-management #test-management-tool

Overview

This is an MCP server that connects AI assistants to the QA Sphere test management system. It implements the Model Context Protocol to expose QA Sphere operations as tools for AI agents, enabling natural language interaction with test cases, suites, and runs.

Best for

Best for
QA engineers who want to manage test management tasks through an AI assistant without leaving their chat interface.

Use cases

  • Create and update test cases via chat commands
  • Retrieve test run status and results through an AI assistant
  • Automate test management workflows by embedding the server in MCP-compatible clients

Notes

This is an MCP server that connects AI assistants to the QA Sphere test management system. It implements the Model Context Protocol to expose QA Sphere operations as tools for AI agents, enabling natural language interaction with test cases, suites, and runs.

22 stars on GitHub. Last updated 2026-05-19. Licensed MIT.

Use cases

  • Create and update test cases via chat commands
  • Retrieve test run status and results through an AI assistant
  • Automate test management workflows by embedding the server in MCP-compatible clients

Pros

  • Straightforward integration with any MCP client (e.g., Claude, Copilot)
  • Leverages the existing QA Sphere API without custom glue code
  • Written in TypeScript, making it easy to extend or contribute

Cons

  • Low community adoption (22 stars) means limited support and documentation
  • Requires a running QA Sphere instance and appropriate API credentials
  • Dependent on the MCP ecosystem which may still be evolving

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Straightforward integration with any MCP client (e.g., Claude, Copilot)
  • Leverages the existing QA Sphere API without custom glue code
  • Written in TypeScript, making it easy to extend or contribute

Cons

  • Low community adoption (22 stars) means limited support and documentation
  • Requires a running QA Sphere instance and appropriate API credentials
  • Dependent on the MCP ecosystem which may still be evolving