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@@ -1088,6 +1088,7 @@ A growing set of community-developed and maintained servers demonstrates various
 - **[py-mcp-qdrant-rag](https://github.com/amornpan/py-mcp-qdrant-rag)** (by amornpan) - A Model Context Protocol server implementation that provides RAG capabilities through Qdrant vector database integration, enabling AI agents to perform semantic search and document retrieval with local or cloud-based embedding generation support across Mac, Linux, and Windows platforms.
 - **[pydantic/pydantic-ai/mcp-run-python](https://github.com/pydantic/pydantic-ai/tree/main/mcp-run-python)** - Run Python code in a secure sandbox via MCP tool calls, powered by Deno and Pyodide
 - **[Python CLI MCP](https://github.com/ofek/pycli-mcp)** - Interact with local Python command line applications.
+- **[qa-use](https://github.com/desplega-ai/qa-use)** - Browser automation and QA testing capabilities. This server integrates with [desplega.ai](https://desplega.ai) to offer automated testing, session monitoring, batch test execution, and intelligent test guidance using the AAA framework.
 - **[QGIS](https://github.com/jjsantos01/qgis_mcp)** - connects QGIS to Claude AI through the MCP. This integration enables prompt-assisted project creation, layer loading, code execution, and more.
 - **[Qiniu MCP Server](https://github.com/qiniu/qiniu-mcp-server)** - The Model Context Protocol (MCP) Server built on Qiniu Cloud products supports users in accessing Qiniu Cloud Storage, intelligent multimedia services, and more through this MCP Server within the context of AI large model clients.
 - **[QuantConnect](https://github.com/taylorwilsdon/quantconnect-mcp)** - QuantConnect Algorithmic Trading Platform Orchestration MCP - Agentic LLM Driven Trading Strategy Design, Research & Implementation.