Hermes Search (Azure Cognitive Search)

Hermes Search (Azure Cognitive Search)

cognitive-stack

Provides integration with Azure Cognitive Search for full-text and semantic search operations. Allows you to query, index documents, and manage search indexes from AI assistants.

Provides a bridge to Azure Cognitive Search for executing search queries, indexing documents, and managing search indexes with filtering options

3326 views3Local (stdio)

What it does

  • Execute full-text and semantic searches
  • Index and manage documents
  • Create and configure search indexes
  • Apply filters and search parameters
  • Perform type-safe search operations

Best for

Developers building search-enabled applicationsData analysts querying document collectionsTeams managing knowledge bases in Azure
Compatible with multiple MCP clientsOne-click Smithery installationTypeScript type safety

About Hermes Search (Azure Cognitive Search)

Hermes Search (Azure Cognitive Search) is a community-built MCP server published by cognitive-stack that provides AI assistants with tools and capabilities via the Model Context Protocol. Bridge to Azure AI Search for enterprise asset management. Execute queries, index docs, and manage with powerful filteri It is categorized under databases, analytics data.

How to install

You can install Hermes Search (Azure Cognitive Search) in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

License

Hermes Search (Azure Cognitive Search) is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

Hermes Search MCP Server 🔍

🔌 Compatible with Cline, Cursor, Claude Desktop, and any other MCP Clients!

The Model Context Protocol (MCP) is an open standard that enables AI systems to interact seamlessly with various data sources and tools, facilitating secure, two-way connections.

The Hermes Search MCP server provides:

  • Full-text and semantic search capabilities over structured/unstructured data
  • Document indexing and management in Azure Cognitive Search
  • Efficient search operations with customizable parameters
  • Type-safe operations with TypeScript

Prerequisites 🔧

Before you begin, ensure you have:

  • Azure Cognitive Search service and credentials
  • Claude Desktop or Cursor
  • Node.js (v20 or higher)
  • Git installed (only needed if using Git installation method)

Hermes Search MCP server installation ⚡

Running with NPX

npx -y hermes-search-mcp@latest

Installing via Smithery

To install Hermes Search MCP Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @hermes-search/mcp --client claude

Configuring MCP Clients ⚙️

Configuring Cline 🤖

The easiest way to set up the Hermes Search MCP server in Cline is through the marketplace with a single click:

  1. Open Cline in VS Code
  2. Click on the Cline icon in the sidebar
  3. Navigate to the "MCP Servers" tab (4 squares)
  4. Search "Hermes Search" and click "install"
  5. When prompted, enter your Azure Cognitive Search credentials

Alternatively, you can manually set up the Hermes Search MCP server in Cline:

  1. Open the Cline MCP settings file:
# For macOS:
code ~/Library/Application\ Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json

# For Windows:
code %APPDATA%\Code\User\globalStorage\saoudrizwan.claude-dev\settings\cline_mcp_settings.json
  1. Add the Hermes Search server configuration to the file:
{
  "mcpServers": {
    "hermes-search-mcp": {
      "command": "npx",
      "args": ["-y", "hermes-search-mcp@latest"],
      "env": {
        "AZURE_SEARCH_ENDPOINT": "your-search-endpoint",
        "AZURE_SEARCH_API_KEY": "your-api-key",
        "AZURE_SEARCH_INDEX_NAME": "your-index-name"
      },
      "disabled": false,
      "autoApprove": []
    }
  }
}
  1. Save the file and restart Cline if it's already running.

Configuring Cursor 🖥️

Note: Requires Cursor version 0.45.6 or higher

To set up the Hermes Search MCP server in Cursor:

  1. Open Cursor Settings
  2. Navigate to Features > MCP Servers
  3. Click on the "+ Add New MCP Server" button
  4. Fill out the following information:
    • Name: Enter a nickname for the server (e.g., "hermes-search-mcp")
    • Type: Select "command" as the type
    • Command: Enter the command to run the server:
    env AZURE_SEARCH_ENDPOINT=your-search-endpoint AZURE_SEARCH_API_KEY=your-api-key AZURE_SEARCH_INDEX_NAME=your-index-name npx -y hermes-search-mcp@latest
    

    Important: Replace the environment variables with your Azure Cognitive Search credentials

Configuring the Claude Desktop app 🖥️

For macOS:

# Create the config file if it doesn't exist
touch "$HOME/Library/Application Support/Claude/claude_desktop_config.json"

# Opens the config file in TextEdit
open -e "$HOME/Library/Application Support/Claude/claude_desktop_config.json"

For Windows:

code %APPDATA%\Claude\claude_desktop_config.json

Add the Hermes Search server configuration:

{
  "mcpServers": {
    "hermes-search-mcp": {
      "command": "npx",
      "args": ["-y", "hermes-search-mcp@latest"],
      "env": {
        "AZURE_SEARCH_ENDPOINT": "your-search-endpoint",
        "AZURE_SEARCH_API_KEY": "your-api-key",
        "AZURE_SEARCH_INDEX_NAME": "your-index-name"
      }
    }
  }
}

Usage in Claude Desktop App 🎯

Once the installation is complete, and the Claude desktop app is configured, you must completely close and re-open the Claude desktop app to see the hermes-search-mcp server. You should see a search icon in the bottom left of the app, indicating available MCP tools.

Hermes Search Examples

  1. Search Documents:
Search for documents containing "machine learning" in the Azure Cognitive Search index, returning the top 10 results.
  1. Index Content:
Index the following documents into Azure Cognitive Search: [{"id": "1", "title": "AI Overview", "content": "Artificial Intelligence is..."}]
  1. Delete Index:
Delete the current Azure Cognitive Search index.

Troubleshooting 🛠️

Common Issues

  1. Server Not Found

    • Verify the npm installation by running npm --version
    • Check Claude Desktop configuration syntax
    • Ensure Node.js is properly installed by running node --version
  2. Azure Search Credentials Issues

    • Confirm your Azure Cognitive Search credentials are valid
    • Check the credentials are correctly set in the config
    • Verify no spaces or quotes around the credentials
  3. Index Access Issues

    • Verify the index exists in your Azure Cognitive Search service
    • Check the index permissions
    • Ensure the API key has appropriate access rights

Acknowledgments ✨

  • Model Context Protocol for the MCP specification
  • Anthropic for Claude Desktop
  • Microsoft Azure for Cognitive Search

Alternatives

Related Skills

Browse all skills
literature-review

Conduct comprehensive, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.). This skill should be used when conducting systematic literature reviews, meta-analyses, research synthesis, or comprehensive literature searches across biomedical, scientific, and technical domains. Creates professionally formatted markdown documents and PDFs with verified citations in multiple citation styles (APA, Nature, Vancouver, etc.).

377
content-trend-researcher

Advanced content and topic research skill that analyzes trends across Google Analytics, Google Trends, Substack, Medium, Reddit, LinkedIn, X, blogs, podcasts, and YouTube to generate data-driven article outlines based on user intent analysis

23
notion

Notion workspace integration. Use when user wants to read/write Notion pages, search databases, create tasks, or sync content with Notion.

10
biomni

Autonomous biomedical AI agent framework for executing complex research tasks across genomics, drug discovery, molecular biology, and clinical analysis. Use this skill when conducting multi-step biomedical research including CRISPR screening design, single-cell RNA-seq analysis, ADMET prediction, GWAS interpretation, rare disease diagnosis, or lab protocol optimization. Leverages LLM reasoning with code execution and integrated biomedical databases.

9
rag-implementation

Build Retrieval-Augmented Generation (RAG) systems for LLM applications with vector databases and semantic search. Use when implementing knowledge-grounded AI, building document Q&A systems, or integrating LLMs with external knowledge bases.

6
smithery-ai-cli

Find, connect, and use MCP tools and skills via the Smithery CLI. Use when the user searches for new tools or skills, wants to discover integrations, connect to an MCP, install a skill, or wants to interact with an external service (email, Slack, Discord, GitHub, Jira, Notion, databases, cloud APIs, monitoring, etc.).

6