websearch-deepseek
An MCP server that provides web search powered by DeepSeek's native search API, returning AI-generated answers with source links. Integrates with MCP-compatible clients like Claude Code and Cursor.
README
websearch-deepseek
A universal MCP Server that provides a web search tool powered by DeepSeek's native web search API β no third-party search API required.
Works with Claude Code, Cursor, Continue, OpenCode, pi, and any tool that supports the MCP protocol.
Features
- π DeepSeek Native Search β Uses the server-side
web_search_20250305tool, no third-party search API needed - π AI-Generated Answers β Returns detailed answers synthesized from full page content, not just a list of URLs
- π Source URLs Included β Every answer comes with original source links for verification
- βοΈ Flexible Configuration β Choose model, toggle thinking mode, adjust token limits
- π MCP Protocol β Standard JSON-RPC over stdio, compatible with all MCP clients
How It Works
User Query β DeepSeek Model
β
Server executes web_search (fetches pages)
β
Encrypted page content β Server decrypts β Feeds to model
β
Model generates detailed answer based on full content
β
Returns: AI-generated answer + source URL list
One MCP tool call = One DeepSeek API request β search, decryption, and answer generation all happen server-side.
Quick Start
1. Get a DeepSeek API Key
Visit DeepSeek Platform to sign up and get your API Key.
2. Install
npm install -g websearch-deepseek
3. Configure Your AI Coding Assistant
Add the following to your MCP configuration file:
Claude Code
Edit ~/.claude/claude_desktop_config.json or .mcp.json in your project:
{
"mcpServers": {
"websearch-deepseek": {
"command": "npx",
"args": ["websearch-deepseek"],
"env": {
"DEEPSEEK_API_KEY": "sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx",
"WEBSEARCH_MODEL": "deepseek-v4-flash",
"WEBSEARCH_THINKING": "enabled"
}
}
}
}
Cursor
Edit ~/.cursor/mcp.json:
{
"mcpServers": {
"websearch-deepseek": {
"command": "npx",
"args": ["websearch-deepseek"],
"env": {
"DEEPSEEK_API_KEY": "sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
}
}
}
}
Continue (VS Code)
Edit ~/.continue/config.json, add to mcpServers:
{
"mcpServers": [
{
"name": "websearch-deepseek",
"command": "npx",
"args": ["websearch-deepseek"],
"env": {
"DEEPSEEK_API_KEY": "sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
}
}
]
}
pi
Edit ~/.pi/agent/settings.json, add to mcp:
{
"mcp": {
"websearch-deepseek": {
"command": "npx",
"args": ["websearch-deepseek"],
"env": {
"DEEPSEEK_API_KEY": "sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
}
}
}
}
4. Start Using It
Restart your AI coding assistant and ask a question that needs real-time information. The assistant will automatically call the web_search tool when needed.
Examples:
- "What's new in React 19?"
- "Search for Python 3.13 release date and major updates"
- "What are the latest AI industry news?"
Environment Variables
| Variable | Required | Default | Description |
|---|---|---|---|
DEEPSEEK_API_KEY |
β Yes | β | DeepSeek API Key |
WEBSEARCH_API_KEY |
β No | β | Alternative API Key variable name |
WEBSEARCH_MODEL |
β No | deepseek-v4-flash |
Model: deepseek-v4-flash (fast) or deepseek-v4-pro (powerful) |
WEBSEARCH_THINKING |
β No | enabled |
Thinking mode: enabled / disabled |
WEBSEARCH_MAX_TOKENS |
β No | 8192 |
Max tokens for response |
Model Selection Guide
| Scenario | Recommended Model | Notes |
|---|---|---|
| Daily search (default) | deepseek-v4-flash |
Fast, low cost, good quality |
| Deep research | deepseek-v4-pro |
More detailed and accurate, slightly slower |
Thinking Mode
- enabled (default): The model thinks before answering, producing higher quality results but consuming more tokens
- disabled: Skips the thinking step for faster responses, suitable for simple queries
CLI Usage
You can also use it directly from the terminal:
# Set API Key
export DEEPSEEK_API_KEY=sk-xxxxxxxxxxxxxxxx
# Search
npx websearch-deepseek search "Node.js LTS versions"
# JSON output
npx websearch-deepseek search --json "TypeScript 5.8"
# Specify model and disable thinking
npx websearch-deepseek search --model deepseek-v4-pro --no-thinking "Rust latest version"
Output Example
## Node.js Latest LTS Versions
As of July 2025, the latest Active LTS version of Node.js is Node.js 24.x...
| Version | Status | Initial Release | Support Until |
|---------|--------|-----------------|---------------|
| 24.x | Active LTS | 2025-05-06 | 2028-04 |
| 22.x | Maintenance | 2024-10 | 2027-04 |
### Recommendations
- New projects: Use Node.js 24 LTS
- Existing projects: Node.js 22 continues to receive security updates
---
### Sources (10):
1. [Node.js 24.0 is available...](https://...)
2. [Node.js β Node.js Releases](https://...)
...
Pricing
This tool uses the DeepSeek API, which charges per token. A single search typically consumes:
| Component | Estimated Tokens |
|---|---|
| Search + thinking | ~5,000β8,000 |
| Generate answer | ~1,000β3,000 |
| Total per search | ~8,000β15,000 tokens |
Check DeepSeek pricing for current rates.
License
MIT
<p align="center"> <a href="./README.zh-CN.md">δΈζη</a> </p>
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
Neon Database
MCP server for interacting with Neon Management API and databases
E2B
Using MCP to run code via e2b.
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.