kindly-web-search-mcp-server

Kindly Web Search MCP Server provides AI coding tools with web search and robust content retrieval across multiple sources including Serper, Tavily, and SearXNG. Unlike generic search servers that return only snippets and URLs, Kindly delivers complete conversation context—questions, answers, comments, and metadata—in a single call, eliminating the need for secondary scraping requests. It integrates directly with StackExchange, GitHub Issues, arXiv, and Wikipedia APIs, parsing webpages in real-time using a headless browser to extract LLM-optimized content. Built for developers and operations teams who need comprehensive solution context when debugging errors or researching technical problems with their AI assistants.

[{"step":"Identify the specific error or problem you need to research. Copy the exact error message or describe the issue in detail.","tip":"Include relevant context like programming language, framework, or environment (e.g., 'Python 3.11', 'React 18', 'AWS Lambda')."},{"step":"Use the Kindly Web Search MCP Server to search for solutions. Specify the search engine (Serper, Tavily, or SearXNG) and craft a query that includes the error message and relevant keywords (e.g., '[ERROR_MESSAGE] + [LANGUAGE] + solution').","tip":"For technical errors, include the programming language or framework in the query to narrow down results (e.g., 'TypeError: Cannot read property of undefined React Hook')."},{"step":"Retrieve and review the top 3-5 results. Focus on recent results (last 1-2 years) and prioritize official documentation, Stack Overflow answers with high upvotes, or GitHub issues with confirmed fixes.","tip":"Use the MCP Server's ability to fetch full content from URLs to read detailed solutions rather than just snippets."},{"step":"Summarize the findings and suggest the most likely fix based on the results. Include specific steps or commands to implement the solution.","tip":"Cross-reference multiple sources to validate the solution before implementing it in your workflow."},{"step":"Implement the fix in your environment and verify the results. If the issue persists, refine your search query or try a different search engine.","tip":"Document the solution and the search process for future reference or team sharing."}]