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omniologynow-rgb/scout-intel-mcp

by Various

The Google for AI agents — give Claude the power to research any company, analyze competitors, and track market trends. 6 tools, 5+ data sources, confidence-scored JSON. pip instal

O

MCP

omniologynow-rgb/scout-intel-mcp

Added 1 June 2026

#ai-agent #business-intelligence #claude #company-research #competitive-analysis #copilot #cursor #data-extraction

Overview

Scout Intel MCP is a Python package that gives Claude and other AI agents access to 6 tools for company research, competitor analysis, and market trend tracking. It aggregates data from 5+ sources and returns confidence-scored JSON. Install via pip.

Best for

Best for
Developers building AI agents that need automated company and market intelligence

Use cases

  • Research a company's background and recent news
  • Analyze competitors in a given market
  • Track emerging market trends from multiple data sources

Notes

Scout Intel MCP is a Python package that gives Claude and other AI agents access to 6 tools for company research, competitor analysis, and market trend tracking. It aggregates data from 5+ sources and returns confidence-scored JSON. Install via pip.

0 stars on GitHub. Last updated 2026-05-03. Licensed AGPL-3.0.

Use cases

  • Research a company’s background and recent news
  • Analyze competitors in a given market
  • Track emerging market trends from multiple data sources

Pros

  • Provides structured, confidence-scored JSON output for easy parsing
  • Aggregates data from multiple sources in one tool
  • Simple pip install and integration with Claude

Cons

  • No public star count or community adoption metrics available
  • Limited to 6 tools and 5+ data sources, may not cover niche needs
  • Requires Python environment and MCP-compatible agent setup

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Provides structured, confidence-scored JSON output for easy parsing
  • Aggregates data from multiple sources in one tool
  • Simple pip install and integration with Claude

Cons

  • No public star count or community adoption metrics available
  • Limited to 6 tools and 5+ data sources, may not cover niche needs
  • Requires Python environment and MCP-compatible agent setup
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