ntop-ai-helper-mcp
Troubleshoot nTop issues with AI-powered error diagnosis, swarm analysis, screen capture, and macro automation.
README
ntop-ai-helper-mcp
MCP server that helps troubleshoot nTop issues with:
- AI diagnosis (
diagnose_ntop_error) - 20-agent parallel swarm mode (
swarm_diagnose_ntop) - Screen capture (
capture_screen) - Macro automation (
save_macro,list_macros,run_macro) - Optional direct terminal execution (
run_terminal_command)
Quick Start
cd "$HOME\Documents\ntop-ai-helper-mcp"
npm install
npm run build
Run directly:
npm start
Run in dev mode:
npm run dev
Environment Variables
Copy .env.example to .env and set values:
OPENAI_API_KEY(required for real AI diagnosis/swarm)OPENAI_MODEL(default:gpt-5.2)ENABLE_COMMAND_TOOL(falseby default; set totrueto allow shell command tool)
MCP Client Config Example
Use the built server file as the MCP command target:
{
"mcpServers": {
"ntop-ai-helper": {
"command": "node",
"args": [
"C:\\Users\\sohum\\Documents\\ntop-ai-helper-mcp\\dist\\server.js"
],
"env": {
"OPENAI_API_KEY": "YOUR_KEY_HERE",
"OPENAI_MODEL": "gpt-5.2",
"ENABLE_COMMAND_TOOL": "false"
}
}
}
}
Tools
-
capture_screen- Inputs:
label? - Output: file path to PNG in
captures/
- Inputs:
-
list_macros- Inputs: none
- Output: all macros from
data/macros.json
-
save_macro- Inputs:
name,description?,steps[] - Step types:
sleep:{ "type": "sleep", "ms": 500 }sendKeys:{ "type": "sendKeys", "keys": "^l" }command:{ "type": "command", "command": "dir" }
- Inputs:
-
run_macro- Inputs:
name,dryRun? - Executes macro step-by-step and returns a run report
- Inputs:
-
diagnose_ntop_error- Inputs:
errorText,context?,goal? - Uses OpenAI if available; otherwise local fallback heuristics
- Inputs:
-
swarm_diagnose_ntop- Inputs:
errorText,context?,goal?,agentCount? - Runs up to 40 agents in parallel (default 20), plus final synthesis
- Inputs:
-
run_terminal_command- Inputs:
command,cwd?,timeoutMs? - Disabled by default for safety
- Inputs:
Notes
- Screen capture and
sendKeysare Windows-oriented. - Macro steps are intentionally explicit for predictable automation.
- If you want stricter safety, keep
ENABLE_COMMAND_TOOL=false.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.