@kyaulabs/deepseek-websearch

An OpenCode-native MCP server that gives your agents real-time web search via DeepSeek's server-side web_search_20250305 tool. One tool call handles search, page fetch, decryption, and answer synthesis — no third-party search API required.

Based on lyumeng/websearch-deepseek (MIT). See Attribution.

How It Works

DeepSeek's Anthropic-compatible endpoint implements a built-in web_search_20250305 tool type. When your OpenCode agent calls the web_search tool, this MCP server forwards the query to DeepSeek, which performs the entire search pipeline server-side:

Agent calls web_search("latest Rust version")
    │
    ▼
MCP Server ──POST──▶ api.deepseek.com/anthropic/v1/messages
                      tools: [{ type: "web_search_20250305" }]
                      │
                      ▼  (all server-side)
                      1. Search the web
                      2. Fetch relevant pages
                      3. Decrypt page content
                      4. Synthesize a detailed answer
                      │
                      ▼
MCP Server ◀──response── { text answer + source URLs }
    │
    ▼
Agent receives Markdown answer with cited sources

No SerpAPI. No Tavily. No Brave Search key. DeepSeek does the searching itself.

Related MCP server: websearch-deepseek

Quick Start

1. Get a DeepSeek API Key

Sign up at platform.deepseek.com and create an API key.

2. Add to Your OpenCode Config

Add the server to your project's opencode.json (or ~/.config/opencode/opencode.json for global):

{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "deepseek-websearch": {
      "type": "local",
      "command": ["npx", "@kyaulabs/deepseek-websearch"],
      "enabled": true,
      "environment": {
        "DEEPSEEK_API_KEY": "{env:DEEPSEEK_API_KEY}"
      }
    }
  }
}

The {env:DEEPSEEK_API_KEY} syntax reads from your environment — set it in .envrc (direnv) or your shell profile:

export DEEPSEEK_API_KEY=sk-xxxxxxxxxxxxxxxx

3. Ask Your Agent

Restart OpenCode. Your agent now has a web_search tool available. Ask anything that needs current information:

• "What's new in React 19?"

• "Search for the latest Node.js LTS release schedule"

• "Find the current DeepSeek API pricing"

The agent will automatically invoke web_search when it needs real-time data beyond its training cutoff.

Configuration

Environment Variables

JSON Config File

Prefer a config file over env vars? Create ~/.deepseek-websearch.json:

{
  "apiKey": "sk-xxxxxxxxxxxxxxxx",
  "model": "deepseek-v4-pro",
  "thinking": "disabled",
  "maxTokens": 16384
}

Resolution order (each layer overrides the previous): defaults → JSON file → environment variables.

Model Selection

Cost

Each search consumes ~8,000–15,000 DeepSeek API tokens (search + thinking + answer generation). Check DeepSeek pricing for current rates.

Features

• Zero runtime dependencies beyond the official @modelcontextprotocol/sdk

• Official MCP SDK — proper capability negotiation, error envelopes, no hand-rolled JSON-RPC

• TypeScript strict mode with 90%+ test coverage (Vitest)

• Structured errors — rate-limit detection (429), network errors, API errors, cancellation

• Configurable — env vars, JSON config file, or per-call programmatic overrides

• AbortSignal support — searches are cancellable

• Clean module separation — import searchWeb() directly from your own code if you don't need the MCP layer

Development

npm install              # install dependencies
npm test                 # run unit test suite (56 tests)
npm run test:integration # run live API tests (requires DEEPSEEK_API_KEY)
npm run build            # compile TypeScript → dist/
npm run check            # type-check without emitting

Using the Core Library Directly

The search logic is framework-agnostic. You can import it without the MCP server:

import { searchWeb } from "@kyaulabs/deepseek-websearch/search";

const result = await searchWeb("latest TypeScript features");
console.log(result.textAnswer);  // AI-generated answer
console.log(result.results);     // SearchResult[] with title, url, pageAge

Attribution

This project is based on lyumeng/websearch-deepseek by @lyumeng, originally released under the MIT License.

The original project established the approach of using DeepSeek's Anthropic-compatible endpoint with the web_search_20250305 tool type for server-side web search via MCP. This version is an independent engineering rewrite with the following improvements:

• Official @modelcontextprotocol/sdk replaces hand-rolled JSON-RPC

• TypeScript strict mode with comprehensive Vitest test suite (90%+ coverage)

• Structured error handling with actionable codes (rate-limit detection, invalid config)

• Env vars + optional JSON config file with merge cascade

• Bug fix: system prompt placed as top-level system parameter (correct Anthropic Messages API format)