Execute web searches, news queries, and content extraction.
Created byApr 22, 2025
Search1API MCP Server
A Model Context Protocol (MCP) server that provides search and crawl functionality using Search1API.
Prerequisites
Node.js >= 18.0.0
A valid Search1API API key (See Setup Guide below on how to obtain and configure)
Installation (Standalone / General)
Clone the repository:
Configure API Key: Before building, you need to provide your Search1API key. See the Setup Guide section below for different methods (e.g., using a .env file or environment variables).
Install dependencies and build:Note: If using the project's `.env` file method for the API key, ensure it exists before this step.
Usage (Standalone / General)
Ensure your API key is configured (see Setup Guide).
Start the server:
The server will then be ready to accept connections from MCP clients.
You need to make your API key available to the server. Choose one of the following methods:
Method A: Project `.env` File (Recommended for Standalone or LibreChat)
This method is required if integrating with the current version of LibreChat (see specific section below).
In the search1api-mcp project root directory, create a file named .env:
Replace your_api_key_here with your actual key.
Make sure this file exists before running npm install && npm run build.
Method B: Environment Variable (Standalone Only)
Set the SEARCH1API_KEY environment variable before starting the server.
Method C: MCP Client Configuration (Advanced)
Some MCP clients allow specifying environment variables directly in their configuration. This is useful for clients like Cursor, VS Code extensions, etc.
Note for LibreChat Users: Due to current limitations in LibreChat, Method A (Project .env File) is the required method. See the dedicated integration section below for full instructions.
Integration with LibreChat (Docker)
This section details the required steps for integrating with LibreChat via Docker.
Overview:
Clone this server's repository into a location accessible by your LibreChat docker-compose.yml.
Configure the required API key using the Project `.env` File method within this server's directory.
Build this server.
Tell LibreChat how to run this server by editing librechat.yaml.
Make sure the built server code is available inside the LibreChat container via a Docker volume bind.
Restart LibreChat.
Step-by-Step:
Clone the Repository:
Navigate to the directory on your host machine where you manage external services for LibreChat (this is often alongside your docker-compose.yml). A common location is a dedicated mcp-server directory.
Navigate into the Server Directory:
Configure API Key (Project `.env` File Method - Required for LibreChat):
Install Dependencies and Build:
This step compiles the server code into the build directory.
Configure `librechat.yaml`:
Edit your main librechat.yaml file to tell LibreChat how to execute this MCP server. Add an entry under mcp_servers:
Configure Docker Volume Bind:
Edit your docker-compose.yml (or more likely, your docker-compose.override.yml) to map the search1api-mcp directory from your host machine into the LibreChat API container. Find the volumes: section for the api: service:
Restart LibreChat:
Apply the changes by rebuilding (if you modified docker-compose.yml) and restarting your LibreChat stack.
Now, the Search1API server should be available as a tool provider within LibreChat.
Features
Web search functionality
News search functionality
Web page content extraction
Website sitemap extraction
Deep thinking and complex problem solving with DeepSeek R1
Seamless integration with Claude Desktop, Cursor, Windsurf, Cline and other MCP clients
Tools
1. Search Tool
Name: search
Description: Search the web using Search1API
Parameters:
2. News Tool
Name: news
Description: Search for news articles using Search1API
Parameters:
3. Crawl Tool
Name: crawl
Description: Extract content from a URL using Search1API
Parameters:
4. Sitemap Tool
Name: sitemap
Description: Get all related links from a URL
Parameters:
5. Reasoning Tool
Name: reasoning
Description: A tool for deep thinking and complex problem solving with fast deepseek r1 model and web search ability(You can change to any other model in search1api website but the speed is not guaranteed)
Parameters:
6. Trending Tool
Name: trending
Description: Get trending topics from popular platforms
Parameters:
Version History
v0.2.0: Added fallback .env support for LibreChat integration and updated dependencies.
v0.1.8: Added X(Twitter) and Reddit search services
v0.1.7: Added Trending tool for GitHub and Hacker News
v0.1.6: Added Wikipedia search service
v0.1.5: Added new search parameters (include_sites, exclude_sites, time_range) and new search services (arxiv, wechat, bilibili, imdb)
v0.1.4: Added reasoning tool with deepseek r1 and updated the Cursor and Windsurf configuration guide
v0.1.3: Added news search functionality
v0.1.2: Added sitemap functionality
v0.1.1: Added web crawling functionality
v0.1.0: Initial release with search functionality
License
This project is licensed under the MIT License - see the LICENSE file for details.
Search1API MCP Server
A Model Context Protocol (MCP) server that provides search and crawl functionality using Search1API.
Prerequisites
Node.js >= 18.0.0
A valid Search1API API key (See Setup Guide below on how to obtain and configure)
Installation (Standalone / General)
Clone the repository:
Configure API Key: Before building, you need to provide your Search1API key. See the Setup Guide section below for different methods (e.g., using a .env file or environment variables).
Install dependencies and build:Note: If using the project's `.env` file method for the API key, ensure it exists before this step.
Usage (Standalone / General)
Ensure your API key is configured (see Setup Guide).
Start the server:
The server will then be ready to accept connections from MCP clients.
You need to make your API key available to the server. Choose one of the following methods:
Method A: Project `.env` File (Recommended for Standalone or LibreChat)
This method is required if integrating with the current version of LibreChat (see specific section below).
In the search1api-mcp project root directory, create a file named .env:
Replace your_api_key_here with your actual key.
Make sure this file exists before running npm install && npm run build.
Method B: Environment Variable (Standalone Only)
Set the SEARCH1API_KEY environment variable before starting the server.
Method C: MCP Client Configuration (Advanced)
Some MCP clients allow specifying environment variables directly in their configuration. This is useful for clients like Cursor, VS Code extensions, etc.
Note for LibreChat Users: Due to current limitations in LibreChat, Method A (Project .env File) is the required method. See the dedicated integration section below for full instructions.
Integration with LibreChat (Docker)
This section details the required steps for integrating with LibreChat via Docker.
Overview:
Clone this server's repository into a location accessible by your LibreChat docker-compose.yml.
Configure the required API key using the Project `.env` File method within this server's directory.
Build this server.
Tell LibreChat how to run this server by editing librechat.yaml.
Make sure the built server code is available inside the LibreChat container via a Docker volume bind.
Restart LibreChat.
Step-by-Step:
Clone the Repository:
Navigate to the directory on your host machine where you manage external services for LibreChat (this is often alongside your docker-compose.yml). A common location is a dedicated mcp-server directory.
Navigate into the Server Directory:
Configure API Key (Project `.env` File Method - Required for LibreChat):
Install Dependencies and Build:
This step compiles the server code into the build directory.
Configure `librechat.yaml`:
Edit your main librechat.yaml file to tell LibreChat how to execute this MCP server. Add an entry under mcp_servers:
Configure Docker Volume Bind:
Edit your docker-compose.yml (or more likely, your docker-compose.override.yml) to map the search1api-mcp directory from your host machine into the LibreChat API container. Find the volumes: section for the api: service:
Restart LibreChat:
Apply the changes by rebuilding (if you modified docker-compose.yml) and restarting your LibreChat stack.
Now, the Search1API server should be available as a tool provider within LibreChat.
Features
Web search functionality
News search functionality
Web page content extraction
Website sitemap extraction
Deep thinking and complex problem solving with DeepSeek R1
Seamless integration with Claude Desktop, Cursor, Windsurf, Cline and other MCP clients
Tools
1. Search Tool
Name: search
Description: Search the web using Search1API
Parameters:
2. News Tool
Name: news
Description: Search for news articles using Search1API
Parameters:
3. Crawl Tool
Name: crawl
Description: Extract content from a URL using Search1API
Parameters:
4. Sitemap Tool
Name: sitemap
Description: Get all related links from a URL
Parameters:
5. Reasoning Tool
Name: reasoning
Description: A tool for deep thinking and complex problem solving with fast deepseek r1 model and web search ability(You can change to any other model in search1api website but the speed is not guaranteed)
Parameters:
6. Trending Tool
Name: trending
Description: Get trending topics from popular platforms
Parameters:
Version History
v0.2.0: Added fallback .env support for LibreChat integration and updated dependencies.
v0.1.8: Added X(Twitter) and Reddit search services
v0.1.7: Added Trending tool for GitHub and Hacker News
v0.1.6: Added Wikipedia search service
v0.1.5: Added new search parameters (include_sites, exclude_sites, time_range) and new search services (arxiv, wechat, bilibili, imdb)
v0.1.4: Added reasoning tool with deepseek r1 and updated the Cursor and Windsurf configuration guide
v0.1.3: Added news search functionality
v0.1.2: Added sitemap functionality
v0.1.1: Added web crawling functionality
v0.1.0: Initial release with search functionality
License
This project is licensed under the MIT License - see the LICENSE file for details.