NetworksDB-MCP

Created By
MorDavida year ago
Fast MCP integration for NetworksDB API - Query IP addresses, organizations, ASNs, and DNS records using natural language through Model Context Protocol
Overview

What is NetworksDB-MCP?

NetworksDB-MCP is a powerful integration that brings the capabilities of Model Context Protocol (MCP) Server to NetworksDB, enabling natural language queries for network intelligence, IP geolocation, organization details, and DNS information.

How to use NetworksDB-MCP?

To use NetworksDB-MCP, clone the repository from GitHub, install the required dependencies, and configure the MCP Server with your NetworksDB API key. You can then query network data using natural language through the MCP interface.

Key features of NetworksDB-MCP?

  • Natural Language Interface for querying network data
  • Comprehensive analysis categories including IP address information, organization search, ASN information, and DNS intelligence
  • API Key management and usage tracking
  • Mass reverse DNS lookup for network ranges

Use cases of NetworksDB-MCP?

  1. Finding information about specific IP addresses
  2. Searching for organizations and their network infrastructure
  3. Analyzing geolocation data for IP addresses
  4. Retrieving DNS records for domains

FAQ from NetworksDB-MCP?

  • What is required to run NetworksDB-MCP?

You need a NetworksDB API key, Python 3.8 or higher, and the MCP Client.

  • Is NetworksDB-MCP an official product?

No, it is a community-driven integration and not an official NetworksDB product.

  • How can I get support?

Join the Telegram channel for updates, tips, and discussions.

Server Config

{
  "mcpServers": {
    "NetworksDB-MCP": {
      "command": "python",
      "args": [
        "<Your_Path>\\NetworksDB-MCP.py"
      ],
      "env": {
        "NETWORKSDB_API_KEY": "<Your_API_Key>"
      }
    }
  }
}
Project Info
Created At
a year ago
Updated At
a year ago
Author Name
MorDavid
Star
0
Language
Python
License
-

Recommend Servers

View All
Bring your real authenticated browser session to AI coding agents. Local-first MCP server + Chrome MV3 extension. No cloud. No telemetry.
@Cubenest

peek records the user's actual logged-in browser (DOM via rrweb, console events, network metadata, optional response bodies via opt-in Deep capture) through a Chrome MV3 extension. The extension ships events through a native-messaging stdio bridge to a local MCP server (peek-mcp), which persists them to a SQLite database at ~/.peek/sessions.db. AI coding agents (Claude Code, Cursor, Cline, Windsurf) read sessions from the database via 10 MCP tools: Tool What it does list_recent_sessions List recently recorded sessions (id, origin, ts, event count). get_session_summary LLM-readable narrative summary of a session. get_session_console_errors Console errors recorded in a session. get_session_network_errors Failed/notable network requests in a session. get_user_action_before_error Last N user actions before a console error. generate_playwright_repro Generate a runnable Playwright test from a session. get_dom_snapshot Reconstruct the DOM at a given timestamp. query_dom_history Timeline of attribute/text changes for a selector. request_authorization Side-panel consent for write actions (Level 3). execute_action Dispatch a UI action (gated by permission level + destructive blocklist). Why local-first matters Every other "browser session for AI" tool ships to a vendor cloud. peek's SQLite + extension live on the user's machine — no remote endpoints, no telemetry. The privacy policy (docs/peek/PRIVACY_POLICY.md) is the source of truth. Install # 1. Add the MCP server to Claude Code claude mcp add peek -- npx -y @peekdev/mcp # 2. Install the Chrome extension from the Chrome Web Store # (link added once the CWS listing is approved)

a day ago