dsh-search-mcp
Run the following command in DeepSeek Harness:
dsh plugin install gxpppp/dsh-search-mcp
Paste the following prompt into your AI chat to install this plugin:
Run dsh plugin install gxpppp/dsh-search-mcp in your DeepSeek Harness terminal to install, or visit the official repository at https://github.com/gxpppp/dsh-search-mcp for more details.
About this plugin
When using DeepSeek Harness for web searches, the built-in search provider might not fully meet your customized needs for specific search engines or result quality. The dsh-search-mcp plugin is designed to solve this exact pain point by completely replacing DSH's native web search functionality with MCP (Model Context Protocol) servers. From the model's perspective, it continues to use the familiar native web_search tool, but the underlying search requests are seamlessly intercepted and routed to your configured MCP servers.
The core strength of this plugin lies in its robust compatibility and flexible configuration experience. It comes with built-in presets for major search engines like Tavily, Brave, Exa, Perplexity, and DuckDuckGo, while also supporting custom HTTP or stdio-based MCP servers. Through an intuitive visual settings interface, you can easily manage multiple server nodes, securely store API credentials, and adjust global or node-specific result limits and timeout settings. Furthermore, the plugin automatically normalizes search results and deduplicates URLs, ensuring the model receives high-quality contextual information.
If you are a DeepSeek Harness user or developer who wants to take control of search data sources, achieve higher search relevance, or build a standardized toolchain based on the MCP protocol, this plugin is the ideal choice. It not only centralizes and secures your search configurations but also significantly enhances the precision and freedom of web retrieval without requiring any changes to the model's prompting habits.
Use Cases
- When needing to integrate specific search engines to improve AI web retrieval quality.
- When wanting to centrally manage multiple search API keys and server configurations in a unified interface.
- When building a standardized AI toolchain based on the MCP protocol and replacing the default search backend.
Best For
- DeepSeek Harness users seeking high-quality web search results.
- AI developers needing to centrally manage multiple search API credentials.
- Tech enthusiasts dedicated to building and testing standardized MCP toolchains.
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