SearXNG MCP Server
Provides privacy-focused web search capabilities through SearXNG metasearch engine, enabling web, image, video, and news searches without tracking. Includes comprehensive research tools that aggregate and analyze results from multiple search engines.
README
🔍 SearXNG MCP Server
A privacy-focused Model Context Protocol (MCP) server that provides Claude with web search capabilities through SearXNG metasearch engine.
✨ Features
- 🔒 Privacy-first - No tracking, no data collection via SearXNG
- 🌐 Multi-engine - Aggregates results from Google, Bing, DuckDuckGo, Brave, and more
- 🎯 Specialized search - Web, images, videos, and news search
- ⚡ Fast - Optimized with minimal tool set (4 tools)
- 🐳 Docker included - SearXNG instance setup included
- 🛠️ Easy setup - Python-based with UV package manager
📦 Installation
Prerequisites
- Python 3.10 or higher
- Docker and Docker Compose
- Git
Quick Install
1. Clone repository:
git clone https://github.com/netixc/SearxngMCP.git
cd SearxngMCP
2. Configure SearXNG:
Edit the following files with your settings:
docker-compose.yml- ReplaceYOUR_IPwith your server's IP addressdocker-compose.yml- ReplaceCHANGE_THIS_SECRET_KEYwith a secret keysearxng/settings.yml- ReplaceCHANGE_THIS_TO_YOUR_OWN_SECRET_KEYwith the same secret keysearxng-config/config.json- ReplaceYOUR_IPwith your server's IP address
Generate a secret key:
openssl rand -hex 32
3. Start SearXNG instance:
docker compose up -d
SearXNG will be available at http://YOUR_IP:8080
4. Install MCP server (using UV - recommended):
# Create venv and install
uv venv
source .venv/bin/activate # Linux/macOS
uv pip install -e ".[dev]"
5. Verify installation:
# Check SearXNG is running
curl http://YOUR_IP:8080
⚙️ Configuration
MCP Client Setup
Add to your MCP settings (e.g., Claude Desktop config):
{
"mcpServers": {
"searxng": {
"command": "/absolute/path/to/SearxngMCP/run-server.sh"
}
}
}
SearXNG Configuration
The SearXNG instance is configured via searxng/settings.yml:
- Default engines: Google, Bing, DuckDuckGo, Brave, Wikipedia, YouTube
- JSON API enabled for MCP access
- Privacy features enabled (no tracking)
- Accessible on your LAN at YOUR_IP:8080
IMPORTANT: Before starting Docker, replace the following in your config files:
docker-compose.yml: ReplaceYOUR_IPandCHANGE_THIS_SECRET_KEYsearxng/settings.yml: ReplaceCHANGE_THIS_TO_YOUR_OWN_SECRET_KEYsearxng-config/config.json: ReplaceYOUR_IP
Generate secret key: openssl rand -hex 32
MCP Server Configuration
Edit searxng-config/config.json (replace YOUR_IP with your server's IP):
{
"searxng": {
"url": "http://YOUR_IP:8080",
"timeout": 10
},
"logging": {
"level": "INFO",
"format": "%(asctime)s - %(name)s - %(levelname)s - %(message)s",
"file": null
}
}
🔧 Available Tools
The server provides 3 optimized tools designed for efficient research:
1. search - Quick Web/News Search
Quick single search for web or news content.
Use when:
- Need quick information or simple lookup
- User asks for a basic web search
- Looking for news on a topic
Parameters:
query*- What to search forcategory- "general" (default) or "news"engines- Optional: Specific engines (e.g., "google,bing")max_results- Number of results (default: 10, max: 50)
Example:
User: What's the latest Python release?
Claude: [Calls search("latest Python release", category="general")]
2. search_media - Images & Videos
Search for images or videos.
Use when:
- User wants to find images or photos
- Looking for video content
- "show me pictures of..." or "find videos about..."
Parameters:
query*- What to findmedia_type- "images" (default) or "videos"engines- Optional: Specific enginesmax_results- Number of results (default: 10, max: 50)
Example:
User: Show me pictures of Northern Lights
Claude: [Calls search_media("Northern Lights", media_type="images")]
3. research_topic - Deep Research ⭐
Multi-search research with automatic analysis and synthesis.
Use when:
- User wants comprehensive research or briefing
- Need to validate information across multiple sources
- User asks to "research", "investigate", or "analyze"
- Creating detailed reports with cross-referenced sources
What it does:
- Runs 2-6 searches automatically using different strategies
- Searches multiple engines (Google, Bing, DuckDuckGo, Brave, Wikipedia)
- Combines general web + news sources
- Deduplicates results across all searches
- Returns 15-50 UNIQUE sources
- Instructs Claude to analyze and synthesize (not just list sources)
Critical behavior: After gathering sources, Claude is instructed to:
- Read and analyze ALL sources
- Cross-reference claims across sources
- Identify high-confidence facts (confirmed by many sources)
- Note contradictions or single-source claims
- Create comprehensive briefing with executive summary
- Assess source quality and credibility
Parameters:
query*- Research topic or questiondepth- Research thoroughness:"quick"- 2 searches, ~15 unique sources"standard"- 4 searches, ~30 unique sources (recommended)"deep"- 6 searches, ~50 unique sources
Example:
User: Research the latest AI developments and give me a briefing
Claude: [Calls research_topic("latest AI developments 2025", depth="standard")]
Claude receives 32 unique sources, then synthesizes:
"# AI Developments Briefing (2025)
## Executive Summary
Based on analysis of 32 sources from Google, Bing, DuckDuckGo, and Wikipedia...
## Key Findings
✓ Major development 1 (HIGH CONFIDENCE - confirmed by 12 sources)
✓ Emerging trend 2 (MEDIUM - reported by 5 sources)
⚠ Claim 3 (LOW - single source, needs verification)
## Contradictions
Source A says X, but Sources B, C, D report Y...
## Source Quality
Most reliable: Google News (8 sources), Wikipedia (3 sources)
..."
💡 Usage Examples
General search:
User: What is the latest news about AI?
Claude: [Calls search("latest AI news")]
Image search:
User: Show me pictures of Northern Lights
Claude: [Calls search_images("Northern Lights")]
Video search:
User: Find Python tutorial videos
Claude: [Calls search_videos("Python tutorial")]
News search:
User: What's happening with climate change?
Claude: [Calls search_news("climate change")]
🐳 Docker Management
Start SearXNG:
docker-compose up -d
Stop SearXNG:
docker-compose down
View logs:
docker-compose logs -f searxng
Rebuild:
docker-compose down
docker-compose up -d --build
🛠️ Development
Run tests:
pytest
Format code:
black .
Type checking:
mypy .
Lint:
ruff .
🎯 Why Only 4 Tools?
This MCP server is optimized for efficiency:
- Focused functionality - Each tool has a clear, distinct purpose
- LLM-friendly - Tool descriptions include "Use this when..." guidance
- Low context - Minimal tool set reduces token usage
- Privacy-first - SearXNG aggregates without tracking
Unlike direct search engine APIs, SearXNG provides:
- Privacy protection (no tracking)
- Multi-engine aggregation
- Self-hosted control
- No API keys needed
📁 Project Structure
SearxngMCP/
├── docker-compose.yml # SearXNG Docker setup
├── searxng/
│ └── settings.yml # SearXNG configuration
├── src/searxng_mcp/
│ ├── server.py # Main MCP server
│ ├── config/ # Configuration handling
│ │ ├── models.py
│ │ └── loader.py
│ └── tools/ # Search tool implementations
│ └── search.py
├── searxng-config/
│ └── config.json # MCP configuration
├── run-server.sh # Server startup script
├── pyproject.toml # Dependencies
└── README.md
📄 License
MIT License
🙏 Credits
- SearXNG - Privacy-respecting metasearch engine
- Model Context Protocol - MCP specification
- Built with FastMCP
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