Hermes Search (Azure Cognitive Search)▌
by cognitive-stack
Bridge to Azure AI Search for enterprise asset management. Execute queries, index docs, and manage with powerful filteri
Provides a bridge to Azure Cognitive Search for executing search queries, indexing documents, and managing search indexes with filtering options
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Developers building search-enabled applications
- / Data analysts querying document collections
- / Teams managing knowledge bases in Azure
capabilities
- / 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
what it does
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.
about
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
MIT
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.
readme
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:
- Open Cline in VS Code
- Click on the Cline icon in the sidebar
- Navigate to the "MCP Servers" tab (4 squares)
- Search "Hermes Search" and click "install"
- When prompted, enter your Azure Cognitive Search credentials
Alternatively, you can manually set up the Hermes Search MCP server in Cline:
- 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
- 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": []
}
}
}
- 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:
- Open Cursor Settings
- Navigate to Features > MCP Servers
- Click on the "+ Add New MCP Server" button
- 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@latestImportant: 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
- Search Documents:
Search for documents containing "machine learning" in the Azure Cognitive Search index, returning the top 10 results.
- Index Content:
Index the following documents into Azure Cognitive Search: [{"id": "1", "title": "AI Overview", "content": "Artificial Intelligence is..."}]
- Delete Index:
Delete the current Azure Cognitive Search index.
Troubleshooting 🛠️
Common Issues
-
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
- Verify the npm installation by running
-
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
-
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
FAQ
- What is the Hermes Search (Azure Cognitive Search) MCP server?
- Hermes Search (Azure Cognitive Search) is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Hermes Search (Azure Cognitive Search)?
- This profile displays 53 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.7 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Direct Database Queries from AI
Enable Claude to query your database directly using natural language
Example
Ask 'Show me top 10 customers by revenue this month' and get SQL results instantly
Eliminate manual SQL writing for ad-hoc queries, get insights 10x faster
Data Analysis & Reporting
Generate complex reports and analytics without leaving conversation
Example
Analyze sales trends, cohort retention, user behavior patterns conversationally
Democratize data access—non-technical team members can query databases
Schema Exploration
Understand database structure, relationships, and data models
Example
'Explain the user_orders table schema and its relationships'
Onboard engineers faster, explore unfamiliar databases efficiently
Data Validation & Quality Checks
Run data quality queries to catch anomalies and inconsistencies
Example
Find duplicate records, missing values, orphaned foreign keys automatically
Maintain data integrity with less manual SQL work
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor with MCP support
- ›Database credentials (read-only recommended for safety)
- ›Network access from Claude client to database
- ›Understanding of database security and access control
Time Estimate
15-30 minutes including configuration and testing
Installation Steps
- 1.Install MCP server: npm install -g @modelcontextprotocol/server-[name]
- 2.Configure database connection in Claude Desktop config (~/.claude/mcp.json)
- 3.Provide connection string: host, port, database, username, password
- 4.Restart Claude Desktop to load MCP server
- 5.Test connection: 'List all tables in database'
- 6.Run simple query: 'Show me 5 rows from users table'
- 7.Verify results and permissions are correct
- 8.Document query patterns for team use
Troubleshooting
- ⚠Connection refused: Check database is running and network accessible
- ⚠Authentication failed: Verify credentials, check user permissions
- ⚠Claude can't see tables: Grant appropriate read permissions to database user
- ⚠Slow queries: Add indexes, limit result set size, use read replicas
- ⚠MCP server not loading: Check config syntax, restart Claude Desktop
Best Practices▌
✓ Do
- +Use read-only database credentials to prevent accidental writes
- +Connect to read replica, not production primary database
- +Set query timeout limits to prevent long-running queries
- +Document database schema and common queries for AI context
- +Monitor query performance and optimize slow queries
- +Use connection pooling for better performance
- +Test with non-production data first
✗ Don't
- −Don't use production write credentials—risk of data corruption
- −Don't query production database during peak traffic hours
- −Don't expose sensitive PII without proper access controls
- −Don't skip query result validation—AI can misinterpret schema
- −Don't allow unlimited result set sizes—set LIMIT clauses
- −Don't share database credentials in plain text config files
💡 Pro Tips
- ★Create database views for common queries to simplify AI access
- ★Add schema comments/descriptions so AI understands column meanings
- ★Use semantic table/column names ('customer_lifetime_value' not 'clv')
- ★Set up query logging to audit what Claude is querying
- ★Create saved query templates for recurring analysis
- ★Combine with data visualization tools for better insights
Technical Details▌
Architecture
MCP server acts as bridge between Claude and database, translating natural language to SQL queries and returning results in structured format.
Protocols
- Model Context Protocol (MCP)
- Database-specific protocols (PostgreSQL, MySQL, MongoDB)
Compatibility
- PostgreSQL
- MySQL
- SQLite
- MongoDB
- Redis
When to Use This▌
✓ Use When
Use for ad-hoc data queries, exploratory analysis, report generation, schema exploration, and democratizing data access. Best for read-heavy analytics workloads.
✗ Avoid When
Avoid for production write operations, mission-critical transactions, real-time OLTP workloads, or when database contains sensitive PII without proper access controls. Use read replicas, not primary.
Integration▌
- →Read replica connection for analytics queries
- →Database view layer to abstract complex joins
- →Query result caching for repeated questions
- →Audit logging of all AI-generated queries
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.7★★★★★53 reviews- ★★★★★Pratham Ware· Dec 24, 2024
Hermes Search (Azure Cognitive Search) is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Diego Reddy· Dec 24, 2024
According to our notes, Hermes Search (Azure Cognitive Search) benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Mia Gonzalez· Dec 24, 2024
Hermes Search (Azure Cognitive Search) is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Ava Reddy· Dec 8, 2024
I recommend Hermes Search (Azure Cognitive Search) for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Arya Rao· Nov 27, 2024
Hermes Search (Azure Cognitive Search) is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Diego Torres· Nov 15, 2024
Hermes Search (Azure Cognitive Search) has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Diego Malhotra· Nov 15, 2024
I recommend Hermes Search (Azure Cognitive Search) for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Soo Li· Nov 3, 2024
Strong directory entry: Hermes Search (Azure Cognitive Search) surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Zaid Mensah· Oct 22, 2024
Hermes Search (Azure Cognitive Search) is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Arjun Verma· Oct 18, 2024
Useful MCP listing: Hermes Search (Azure Cognitive Search) is the kind of server we cite when onboarding engineers to host + tool permissions.
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