kindly-web-search-mcp-server

🥈Silver

Kindly Web Search MCP Server enables AI coding tools to perform web searches and retrieve content. It supports Serper, Tavily, and SearXNG. Use it to debug errors, research solutions, and automate content retrieval for developers and operations teams.

25460Updated 1w ago

Intermediate30min to implementautomation

Saves ~45 min per use

Quick InstallView Source

git clone https://github.com/Shelpuk-AI-Technology-Consulting/kindly-web-search-mcp-server.git

Works with:

Claude

Overview

About This Skill

How to Use

[{"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."}]

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/Shelpuk-AI-Technology-Consulting/kindly-web-search-mcp-server

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Use the Kindly Web Search MCP Server to find solutions for the following error: [ERROR_MESSAGE]. Search Serper with the query '[ERROR_MESSAGE] + solution' and retrieve the top 3 most relevant results. Summarize the findings and suggest the most likely fix based on the results.

Example Output

I encountered the following error while deploying a Node.js application to AWS Lambda:

```
Error: ENOENT: no such file or directory, open '/var/task/node_modules/some-package/package.json'
```

After using the Kindly Web Search MCP Server with Serper, I retrieved these results:

1. **Stack Overflow Thread (2024)**: A user reported the same error when deploying to Lambda with a custom layer. The top answer suggested running `npm install --production` locally before zipping the deployment package to ensure all dependencies are included. The solution was validated by 47 upvotes and marked as accepted.

2. **AWS Documentation**: The Lambda deployment package documentation explicitly states that all dependencies must be included in the deployment package. It recommends using `npm install --production` to avoid including devDependencies and to ensure the package.json is present in the root of the deployment archive.

3. **GitHub Issue (2023)**: A developer documented a similar issue when using Lambda Layers. The fix involved ensuring the node_modules directory was correctly included in the deployment package and that the layer was properly configured in the Lambda function's deployment settings.

**Recommended Fix**: 
Based on the results, the most likely cause is that the node_modules directory was not properly included in the deployment package. The fix involves:
1. Running `npm install --production` locally to generate a complete node_modules directory.
2. Zipping the entire directory (including node_modules) and deploying to Lambda.
3. Verifying the Lambda function's handler path is correct in the deployment package.

This should resolve the ENOENT error by ensuring all required files are present in the deployment package.