mcp-searxng MCP Server

What does “mcp-searxng” MCP Server do?

The mcp-searxng MCP Server is an example server designed to enable AI agents to perform real-time web searches using SearXNG, an open-source meta-search engine. By connecting with external information sources, this server allows AI assistants to retrieve up-to-date and diverse search results from various search engines, enhancing their ability to provide accurate and current answers. The integration with SearXNG means that the AI agent can utilize privacy-focused and multi-source search capabilities, making it suitable for research, fact-checking, and expanding knowledge beyond static datasets. This server is ideal for developer workflows that require access to fresh data, real-time web content, or broad internet search capabilities within their AI-driven applications.

List of Prompts

No information available in the repository regarding prompt templates.

Ready to grow your business?

Start your free trial today and see results within days.

Request demo Log in

List of Resources

No information found in the repository about exposed MCP resources.

List of Tools

Based on the available repository files, especially server.py, there are no explicit tool definitions listed. The repository focuses on providing web search capabilities via SearXNG, which may be exposed as a single tool for querying search results, but no detailed description is provided.

Join our newsletter

Get latest tips, trends, and deals for free.

Email address

Subscribe

Use Cases of this MCP Server

• Real-time Web Search
  Developers can equip their AI agents with up-to-date internet search capabilities for answering user queries, conducting research, or fact-checking information in real time.
• Privacy-focused Search Integration
  Integrate privacy-respecting search results from engines like DuckDuckGo, Brave, or Ecosia, enhancing trust and compliance for end-users.
• Enhanced Research for AI Agents
  AI agents can access a wide range of search engines through SearXNG, gaining broader perspectives and more comprehensive information for complex queries.
• Augmenting LLM Capabilities
  Bridge the gap between static LLM knowledge and dynamic web data, providing more relevant and situationally aware responses.
• Meta-search for Application Development
  Power applications that require multi-source search results, such as market analysis tools, news aggregators, or research assistants.

How to set it up

Windsurf

1. Prerequisites: Ensure Node.js and Windsurf are installed.
2. Locate Configuration: Open your Windsurf configuration file.
3. Add mcp-searxng MCP Server: Insert the following JSON snippet into the mcpServers section.
4. Save & Restart: Save changes and restart Windsurf.
5. Verify: Check the server logs or Windsurf UI to confirm successful integration.

{
  "mcpServers": [
    {
      "name": "mcp-searxng",
      "command": "npx",
      "args": ["@mcp-searxng/mcp-server@latest"]
    }
  ]
}

Securing API Keys

To secure API keys or sensitive credentials, use environment variables:

{
  "mcpServers": [
    {
      "name": "mcp-searxng",
      "command": "npx",
      "args": ["@mcp-searxng/mcp-server@latest"],
      "env": {
        "SEARXNG_API_KEY": "${SEARXNG_API_KEY}"
      },
      "inputs": {
        "api_key": "${SEARXNG_API_KEY}"
      }
    }
  ]
}

Claude

1. Prerequisites: Install Claude’s CLI or integration platform.
2. Locate Configuration: Find the Claude MCP configuration file.
3. Add Server: Insert the following under MCP servers.
4. Save & Restart: Apply changes and restart Claude.
5. Verify: Confirm server registration in Claude’s interface.

{
  "mcpServers": [
    {
      "name": "mcp-searxng",
      "command": "npx",
      "args": ["@mcp-searxng/mcp-server@latest"]
    }
  ]
}

Cursor

1. Prerequisites: Make sure Cursor and Node.js are set up.
2. Open Configuration: Edit the Cursor configuration file.
3. Configure MCP Server: Add the mcp-searxng server details.
4. Restart Cursor: Restart the application.
5. Verify: Test the integration from Cursor’s tool catalog.

{
  "mcpServers": [
    {
      "name": "mcp-searxng",
      "command": "npx",
      "args": ["@mcp-searxng/mcp-server@latest"]
    }
  ]
}

Cline

1. Prerequisites: Ensure Cline and Node.js are installed.
2. Edit Configuration: Open the Cline MCP configuration file.
3. Add Server: Insert the server configuration JSON.
4. Save & Restart: Save and restart Cline.
5. Verify: Check server status in Cline.

{
  "mcpServers": [
    {
      "name": "mcp-searxng",
      "command": "npx",
      "args": ["@mcp-searxng/mcp-server@latest"]
    }
  ]
}

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "mcp-searxng": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “mcp-searxng” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

My opinion: mcp-searxng provides a clear overview and real-world use cases but lacks implementation details for prompts, resources, and tools, limiting its immediate utility for developers seeking a robust, multi-tool MCP server. Its main contribution is enabling web search through SearXNG, but documentation and modularity could be improved.

MCP Score

Rating:
Based on the above tables, I would rate this MCP server a 3/10. While it is open source and has a clear purpose, the lack of detailed tool/resource implementations and prompt templates limits its utility and completeness as an MCP server.