Enables AI assistants to perform intelligent web searches using the Baidu Wenxin API, supporting multiple models, search modes, and providing search results with reference sources.
Enables LLMs to interact with Oracle Databases by providing specific table and column metadata as context. Users can generate SQL statements and retrieve query results directly through natural language prompts.
A Model Context Protocol server that enables AI agents to query Saagar Patel's writing, projects, and benchmark results from a static corpus, without scraping HTML.
A multi-tool AI assistant system that uses Model Context Protocol to connect language models with various tools, including math calculations and weather information.
Enables integration of Google search functionality into MCP-enabled applications using the Serper API, providing rich search results, configurable parameters, and efficient response handling.
Real-time web search with answer-ready results for Claude, Cursor and any MCP client. A Tavily alternative: same speed, 20.2% fewer tokens, higher answer quality (60.7% of decided duels won) on a public benchmark. Hosted on mcp.serpdive.com or npx serpdive-mcp.
Keyless, local MCP server bringing ISTQB / OWASP / IEEE / ISO / EU AI Act QA standards into your AI client. Standards-grounded retrieval, deterministic QA effort estimation, automated QA document quality review (0-100 rubric), and JUnit/CSV test-results flakiness analysis.