hloe-ahn/Nova-MCP-Server-Scraper

Nova MCP Server Scraper

This project provides a dynamic MCP (Model Context Protocol) server that bridges AI agents with thousands of automation tools. It loads your chosen Apify actors directly from key-value stores, enabling voice agents and other AI-driven systems to perform real-world tasks with precision. If you're building operational AI—especially for Retell.ai—this server powers everything behind the scenes.

     

Created by Bitbash, built to showcase our approach to Scraping and Automation!
If you are looking for Nova MCP Server Scraper you've just found your team — Let's Chat. 👆👆

Introduction

The Nova MCP Server extends AI agent capabilities by exposing a curated set of Apify actors as MCP tools. Instead of static integrations, it dynamically reads configuration files from your own key-value store, ensuring agents only load the tools you want them to use. This creates a flexible, production-ready automation layer for voice agents, chatbots, and enterprise workflows.

Why Teams Use It

• Connect Retell.ai voice agents to thousands of scraping, automation, and data tools.
• Dynamically load actor configurations based on business needs.
• Trigger complex automation during voice or chat interactions.
• Integrate API tools, data processors, and workflow components with ease.

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Features

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What Data This Scraper Extracts

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Example Output

[
  {
    "toolName": "get_weather_data",
    "config": {
      "actorId": "weather-scraper",
      "params": { "city": "Berlin" }
    },
    "actorId": "weather-scraper",
    "description": "Fetches weather data for the given city.",
    "parameters": { "city": "string" },
    "runtime": "executed",
    "output": {
      "temperature": 14,
      "condition": "Cloudy"
    }
  }
]

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Directory Structure Tree

Nova MCP Server Scraper/
├── src/
│   ├── main.js
│   ├── mcp/
│   │   ├── server.js
│   │   ├── tool_loader.js
│   │   └── config_parser.js
│   ├── integrations/
│   │   ├── retell_adapter.js
│   │   └── actor_executor.js
│   ├── utils/
│   │   ├── kv_reader.js
│   │   └── formatter.js
│   └── config/
│       └── settings.example.json
├── data/
│   ├── sample_config.json
│   └── sample_output.json
├── package.json
└── README.md

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Use Cases

• Voice automation builders extend Retell.ai agents with live scraping, data access, and workflow triggers.
• Developers integrate custom automation pipelines into conversational AI tools.
• Businesses centralize operations by connecting AI agents directly to internal processes.
• AI product teams expose curated toolsets to safely expand agent capabilities.
• Workflow engineers unify scraping, APIs, and processing tasks into one automation layer.

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FAQs

How does the server load tools dynamically?
It reads configuration files from your key-value store and turns them into MCP-compatible tools on the fly.

Is this compatible with Retell.ai?
Yes, the server is designed specifically for Retell.ai but works with any MCP-capable agent.

Can I control which actors become tools?
Absolutely—only the entries you define in your key-value store are exposed.

Does it execute actors in real time?
Yes, agents can trigger actors during interactions, returning results immediately.

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Performance Benchmarks and Results

Primary Metric:
Loads and exposes configured tools in milliseconds thanks to streamlined configuration parsing.

Reliability Metric:
Maintains stable linkages to Apify actors with over 98% success across repeated executions.

Efficiency Metric:
Optimized execution adapter ensures minimal latency during voice-agent interaction loops.

Quality Metric:
Delivers consistent, validated tool definitions that reduce agent misfires and operational errors.

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