Hermes Search (Azure Cognitive Search)
Hermes Search MCP Server is an open - source service based on the Model Context Protocol, providing full - text and semantic search functions integrated with Azure Cognitive Search, and supporting multiple AI client tools.
rating : 2.5 points
downloads : 15
What is Hermes Search MCP Server?
Hermes Search is an intelligent search server based on the Model Context Protocol (MCP), which enables AI systems (such as Claude, Cursor, etc.) to seamlessly connect to the Azure Cognitive Search service, achieving efficient document search and management functions.How to use Hermes Search MCP Server?
Simply configure your AI client (Cline, Cursor, or Claude Desktop) and provide the credentials for the Azure search service to start using the powerful search function.Use cases
Suitable for scenarios where AI assistants need to access enterprise knowledge bases, technical documents, or personal document collections, supporting fast retrieval of relevant information.Main features
Full-text searchSupports full-text retrieval of structured/unstructured data
Semantic searchUnderstands search intent based on AI, not just keyword matching
Document managementSupports operations such as indexing, updating, and deleting documents
Multi-client compatibilityCompatible with multiple AI clients such as Cline, Cursor, and Claude Desktop
Advantages and limitations
Advantages
Ready to use, start with one - click via npx
Deeply integrated with Azure Cognitive Search
Supports multiple popular AI clients
Provides a type - safe TypeScript interface
Limitations
Requires an existing Azure Cognitive Search service
Currently mainly supports English content search
Advanced functions require certain configuration knowledge
How to use
Install the service
Run directly via npx or install using the Smithery tool
Configure the client
Configure accordingly based on the AI client you are using (Cline, Cursor, or Claude Desktop)
Provide Azure credentials
Set your Azure Cognitive Search service endpoint, API key, and index name in the configuration file
Restart the client
After completing the configuration, restart your AI client to load the search function
Usage examples
Technical document searchQuickly find relevant solutions in a large technical document library
Knowledge base expansionAdd new knowledge to the enterprise knowledge base
Research material retrievalFind relevant research in a collection of research papers
Frequently Asked Questions
Why doesn't my search return any results?
How do I know if the service is running normally?
Which file formats are supported for indexing?
What are the limitations of indexing a large number of documents?
Related resources
Azure Cognitive Search documentation
Microsoft's official documentation for the Azure search service
Model Context Protocol specification
Official specification of the MCP protocol
GitHub repository
Project source code and issue tracking
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