Traylinx Search Engine MCP Server
About
# Traylinx Search Engine MCP Server [](https://smithery.ai/server/traylinx/traylinx-search-engine-mcp-server) A Model Context Protocol (MCP) server that acts as a bridge to the deployed **Agentic Search API**. It allows MCP clients…
Details
- License
- MIT license
Explore
Rich Content Types: Returns multiple content types beyond just text
Time Filtering: Filter results by recency (month, week, day, hour)
Secure API Key Handling: API key stays in environment variables
Configurable Endpoint: Easily switch between API endpoints if needed
- Full MCP Compliance: Implements all required MCP server methods
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Traylinx Search Engine MCP ServerCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Node.js >= 18.0.0
An API Key from Traylinx.com
npm install
The Traylinx Search Engine MCP Server supports multiple response types:
Text Content: Standard markdown text summarizing the search results
Embedded HTML: For URL extractions, the server can return the scraped HTML
Search Items: Structured search results with title, URL, and snippet
Media Items: Images, videos, and other media found during the search
News Articles: Recent news with thumbnails and metadata
Raw API Response: Complete response data for advanced use cases
This MCP server can be deployed to Smithery.ai:
1. Create/login to your Smithery account
2. Click "Deploy a New MCP Server"
3. Enter ID: traylinx-search-engine-mcp-server
4. Use base directory: . (dot for root)
5. Click "Create"
Once deployed, you can reference this server in Claude's web interface by using:
Use the traylinx-search-engine-mcp-server to search for [your query]
Note: You'll need to provide your AGENTIC_SEARCH_API_KEY as an environment variable in the Smithery deployment settings.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"traylinx search engine mcp server": {
"traylinx-search-engine-mcp-server": {
"command": "node",
"args": [
"path/to/traylinx-search-engine-mcp-server/dist/index.js"
],
"env": {
"AGENTIC_SEARCH_API_KEY": "<YOUR_TOKEN>",
"AGENTIC_SEARCH_API_URL": "https://agentic-search-engines-n3n7u.ondigitalocean.app",
"LOG_LEVEL": "INFO"
}
}
}
}
}McpServers
{
"traylinx-search-engine-mcp-server": {
"command": "node",
"args": [
"path/to/traylinx-search-engine-mcp-server/dist/index.js"
],
"env": {
"AGENTIC_SEARCH_API_KEY": "<YOUR_TOKEN>",
"AGENTIC_SEARCH_API_URL": "https://agentic-search-engines-n3n7u.ondigitalocean.app",
"LOG_LEVEL": "INFO"
}
}
}A Model Context Protocol (MCP) server that acts as a bridge to the deployed Agentic Search API. It allows MCP clients like Claude Desktop and Cursor to utilize intelligent search capabilities with both text summaries and structured data (HTML, images, and more).
Tools
search
Perform a web search using Traylinx's API, which provides detailed and contextually relevant results with citations. By default, no time filtering is applied to search results.
Inputs:
- query (string): The search query to perform.
- search_recency_filter (string, optional): Filter search results by recency. Options: "month", "week", "day", "hour". If not specified, no time filtering is applied.
How it Works
1. You configure this MCP server with your Agentic Search API URL and API Key (via environment variables passed by the client config).
2. An MCP client (e.g., Claude) sends a tool call to this server with a search query and optional recency filter.
3. This MCP server makes a request to the Agentic Search API with the query and authorization header.
4. It parses the rich response (text, HTML, search results, media, news) and returns structured content to the MCP client.
Installation
Prerequisites
Node.js >= 18.0.0
An API Key from Traylinx.com
Step 1: Get an API Key from Traylinx
1. Visit traylinx.com and sign up for an account
2. Navigate to the developer dashboard/API section
3. Generate your API key for the Agentic Search API
4. Keep this key secure - you'll need it for configuration
Step 2: Set Up the MCP Server
```bash
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