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searxng-mcp
A Model Context Protocol (MCP) server that enables AI assistants to perform web searches using SearXNG, a privacy-respecting metasearch engine.
3 years
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SearXNG MCP Server
A Model Context Protocol (MCP) server that enables AI assistants to perform web searches using SearXNG, a privacy-respecting metasearch engine. Works out-of-the-box with zero additional deployment by automatically selecting a random instance from SearX.space, while also supporting private instances with basic authentication.
Features
- Zero-configuration setup: Works immediately by using a random public instance from SearX.space
- Private instance support: Connect to your own SearXNG instance with optional basic authentication
- Perform web searches with customizable parameters
- Support for multiple search engines
- Privacy-focused search results
- Markdown-formatted search results
- Sensible default values for all parameters
CAVEAT - Public Instances might be unavailabe for this purpose and return "Request failed with status code 429"
Installation
Prerequisites
- Node.js (v16 or higher)
- npm (v7 or higher)
- Access to a SearXNG instance (self-hosted or public)
Install from source
# Clone the repository
git clone https://github.com/tisDDM/searxng-mcp.git
cd searxng-mcp
# Install dependencies
npm install
# Build the project
npm run build
Configuration
The SearXNG MCP server can be configured with the following environment variables:
-
SEARXNG_URL
(optional): The URL of your SearXNG instance (e.g.,https://searx.example.com
). If not provided, a random public instance from SearX.space will be automatically selected, making the server usable with zero additional deployment. -
USE_RANDOM_INSTANCE
(optional): Set to "false" to disable random instance selection when no URL is provided. Default is "true". -
SEARXNG_USERNAME
(optional): Username for basic authentication when connecting to a private instance -
SEARXNG_PASSWORD
(optional): Password for basic authentication when connecting to a private instance
You can set these environment variables in a .env
file in the root directory of the project:
SEARXNG_URL=https://searx.example.com
SEARXNG_USERNAME=your_username
SEARXNG_PASSWORD=your_password
Usage
Running the server
# If installed globally
searxngmcp
# If installed from source
node build/index.js
Integrating with Claude Desktop
- Open Claude Desktop
- Go to Settings > MCP Servers
- Add a new MCP server with the following configuration:
{ "mcpServers": { "searxngmcp": { "command": "searxngmcp", "env": { // Optional: If not provided, a random public instance will be used "SEARXNG_URL": "https://searx.example.com", // Optional: Only needed for private instances with authentication "SEARXNG_USERNAME": "your_username", "SEARXNG_PASSWORD": "your_password" }, "disabled": false, "autoApprove": [] } } }
Integrating with Claude in VSCode
- Open VSCode
- Go to Settings > Extensions > Claude > MCP Settings
- Add a new MCP server with the following configuration:
{ "mcpServers": { "searxngmcp": { "command": "node", "args": ["/path/to/searxng-mcp/build/index.js"], "env": { // Optional: If not provided, a random public instance will be used "SEARXNG_URL": "https://searx.example.com", // Optional: Only needed for private instances with authentication "SEARXNG_USERNAME": "your_username", "SEARXNG_PASSWORD": "your_password" }, "disabled": false, "autoApprove": [] } } }
Usage with Smolagents
SearXNG MCP can be easily integrated with Smolagents, a lightweight framework for building AI agents. This allows you to create powerful research agents that can search the web and process the results:
from smolagents import CodeAgent, LiteLLMModel, ToolCollection
from mcp import StdioServerParameters
# Configure the SearXNG MCP server
server_parameters = StdioServerParameters(
command="node",
args=["path/to/searxng-mcp/build/index.js"],
env={
"SEARXNG_URL": "https://your-searxng-instance.com",
"SEARXNG_USERNAME": "your_username", # Optional
"SEARXNG_PASSWORD": "your_password" # Optional
}
)
# Create a tool collection from the MCP server
with ToolCollection.from_mcp(server_parameters) as tool_collection:
# Initialize your LLM model
model = LiteLLMModel(
model_id="your-model-id",
api_key="your-api-key",
temperature=0.7
)
# Create an agent with the search tools
search_agent = CodeAgent(
name="search_agent",
tools=tool_collection.tools,
model=model
)
# Run the agent with a search prompt
result = search_agent.run(
"Perform a search about: 'climate change solutions' and summarize the top 5 results."
)
print(result)
Available Tools
searxngsearch
Perform web searches using SearXNG, a privacy-respecting metasearch engine. Returns relevant web content with customizable parameters.
Parameters
Parameter | Type | Description | Default | Required |
---|---|---|---|---|
query | string | Search query | - | Yes |
language | string | Language code for search results (e.g., 'en', 'de', 'fr') | 'en' | No |
time_range | string | Time range for search results. Options: 'day', 'week', 'month', 'year' | null | No |
categories | array of strings | Categories to search in (e.g., 'general', 'images', 'news') | null | No |
engines | array of strings | Specific search engines to use | null | No |
safesearch | number | Safe search level: 0 (off), 1 (moderate), 2 (strict) | 1 | No |
pageno | number | Page number for results. Must be minimum 1 | 1 | No |
max_results | number | Maximum number of search results to return. Range: 1-50 | 10 | No |
Example
// Example request
const result = await client.callTool('searxngsearch', {
query: 'climate change solutions',
language: 'en',
time_range: 'year',
categories: ['general', 'news'],
safesearch: 1,
max_results: 5
});
Development
Setup
# Clone the repository
git clone https://github.com/tisDDM/searxng-mcp.git
cd searxng-mcp
# Install dependencies
npm install
Build
npm run build
Watch mode (for development)
npm run watch
Testing with MCP Inspector
npm run inspector
License
MIT
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