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  1. Home
  2. πŸ”Ž Search & Data Extraction
  3. Scout Intel MCP
Scout Intel MCP logo
Health: ActiveRecent health check succeeded.Last checked 9/11/2026, 3:45:43 PM

Scout Intel MCP

User RatingsBe the first to rate and review this MCP server!
View Repository2 GitHub StarsTotal stargazers on GitHub for the source repository (2 stars).Visit Website

Provides structured business intelligence and market research via 6 tools aggregating multiple data sources with confidence scoring.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag β€” we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "omniologynow-rgb-scout-intel-mcp": {
      "command": "uvx",
      "args": [
        "scout-mcp"
      ]
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing AlternativesπŸ”Ž More in Search & Data Extraction

Overview

This MCP server offers AI agents access to structured business and market intelligence by aggregating data from sources like DuckDuckGo, NewsAPI, Wikipedia, web scraping, and social profiles. It returns Pydantic-validated JSON with per-source confidence breakdowns and data quality grades to help agents assess reliability. The server includes six tools for company, market, competitor, trend, product, and public figure research, suitable for tasks requiring detailed, multi-source business insights.

Use cases

β€’Analyze company profiles including industry, funding, and key personnel
β€’Conduct market research on size, growth, and trends
β€’Perform competitor analysis covering positioning and pricing
β€’Track trends with sentiment and related topic insights
β€’Research public figures’ roles and social profiles (Pro tier)

Key features

β€’Aggregates data from 5+ sources including DuckDuckGo, NewsAPI, and Wikipedia
β€’Provides 6 specialized intelligence tools for business and market insights
β€’Returns structured JSON with Pydantic validation
β€’Includes data quality grades (A+ to F) to indicate reliability
β€’Offers per-source confidence breakdowns for transparency
β€’Supports self-hosting with Python package and Docker

Capabilities & Tool Schemas

Inspect callable tools, capabilities, and parameters exposed to AI agents by Scout Intel MCP.

Extracted Tool Capabilities
Aggregates data from 5+ sources including DuckDuckGo, NewsAPI, and Wikipedia
Provides 6 specialized intelligence tools for business and market insights
Returns structured JSON with Pydantic validation
Includes data quality grades (A+ to F) to indicate reliability
Offers per-source confidence breakdowns for transparency
Supports self-hosting with Python package and Docker

Documentation Overview

Scout MCP
Business & Market Intelligence for AI Agents

Python 3.11+ FastMCP 3.x MIT License 6 Tools 5+ Data Sources PyPI version PyPI Downloads/month MCPize


Google for AI agents β€” instead of web pages, it returns clean, structured JSON that agents can reason over.

Scout MCP gives any AI agent instant access to structured business intelligence, market research, and competitive analysis. It aggregates data from DuckDuckGo, NewsAPI, Wikipedia, web scraping, and social profiles into Pydantic-validated JSON responses with per-source confidence breakdowns and data quality grades.


Table of Contents

  • Quick Install
  • The 6 Intelligence Tools
  • Data Quality Grades
  • Confidence Breakdown
  • Full API Reference
  • Example Responses
  • Architecture
  • Configuration
  • Pricing & Rate Limits
  • Self-Hosting
  • Docker
  • Tech Stack
  • Data Sources
  • Contributing

Quick Install

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

config.json
{
  "mcpServers": {
    "scout-mcp": {
      "command": "python",
      "args": ["-m", "scout_mcp.mcp_server"],
      "cwd": "/path/to/scout-mcp/src",
      "env": {
        "NEWS_API_KEY": "your-newsapi-key"
      }
    }
  }
}

Cursor

Add to Cursor Settings > MCP:

config.json
{
  "scout-mcp": {
    "command": "python",
    "args": ["-m", "scout_mcp.mcp_server"],
    "cwd": "/path/to/scout-mcp/src",
    "env": {
      "NEWS_API_KEY": "your-newsapi-key"
    }
  }
}

VS Code (Copilot MCP)

Add to .vscode/mcp.json:

config.json
{
  "servers": {
    "scout-mcp": {
      "command": "python",
      "args": ["-m", "scout_mcp.mcp_server"],
      "cwd": "/path/to/scout-mcp/src",
      "env": {
        "NEWS_API_KEY": "your-newsapi-key"
      }
    }
  }
}

pip (self-hosted)

Terminal
pip install scout-mcp
scout-mcp  # starts STDIO server for MCP clients

The 6 Intelligence Tools

#ToolWhat It DoesTier
1scout_companyStructured intel on any company: industry, funding, tech stack, competitors, news, key peopleFree
2scout_marketMarket research: size, CAGR, key players, trends, growth drivers, risksFree
3scout_competitorsCompetitor analysis: positioning, pricing, strengths, weaknesses, differentiatorsFree
4scout_trendsTrend tracking: sentiment analysis, key developments, trending direction, related topicsFree
5scout_productProduct intelligence: pricing, ratings, features, alternatives, recent updatesFree
6scout_personPublic figure research: role, background, achievements, social profilesPro

Data Quality Grades

Every response includes a data_quality_grade β€” a letter grade that lets agents instantly assess intelligence reliability:

GradeConfidenceMeaning
A+90%+Exceptional β€” multiple high-quality sources confirmed
A80-90%High β€” strong multi-source corroboration
B65-80%Good β€” solid data from key sources
C45-65%Fair β€” limited sources, gaps likely
D25-45%Low β€” sparse data, treat with caution
F<25%Insufficient β€” minimal data available

How Agents Should Use Grades

python
result = scout_company("Stripe")

if result["data_quality_grade"] in ("A+", "A"):
    # High confidence β€” safe to make decisions on this data
    proceed_with_analysis(result)
elif result["data_quality_grade"] == "B":
    # Good but verify key claims
    proceed_with_caveats(result)
else:
    # C/D/F β€” supplement with additional sources
    request_more_data(result)

Confidence Breakdown

Beyond the letter grade, every response includes a confidence_breakdown dict showing per-source reliability:

config.json
{
  "confidence": 0.86,
  "data_quality_grade": "A",
  "confidence_breakdown": {
    "duckduckgo": {
      "score": 0.60,
      "reason": "8 results found"
    },
    "company_website": {
      "score": 0.90,
      "reason": "scraped stripe.com, 3 data points extracted"
    },
    "wikipedia": {
      "score": 0.90,
      "reason": "page found, structured data extracted"
    },
    "newsapi": {
      "score": 0.90,
      "reason": "6 articles found"
    },
    "competitor_extraction": {
      "score": 0.80,
      "reason": "5 competitors identified"
    }
  }
}

Source Weights

Different sources carry different weights in the overall confidence calculation:

SourceWeightWhy
Wikipedia3xCurated, structured, authoritative
NewsAPI2xFresh, professional journalism
Company Website2xFirst-party data, most current
DuckDuckGo Search1xBroad but variable quality
Competitor Extraction1xDerived analysis
Social Profiles1xSupplementary

Full API Reference

Base URL

Code
POST /api/scout/{tool_name}

Authentication

Pass your API key via the X-Api-Key header:

Terminal
curl -X POST /api/scout/company \
  -H "X-Api-Key: your-key-here" \
  -H "Content-Type: application/json" \
  -d '{"name": "Stripe"}'

No key = free tier (50 requests/day).

Health & Info

EndpointMethodDescription
/api/GETService info + list of tools
/api/healthGETHealth check + DuckDuckGo backoff status
/api/toolsGETAll tools with params, tiers, and grade descriptions
/api/cache/statsGETCache hit/miss statistics
/api/cache/clearPOSTClear all cached responses

Tool Endpoints

POST /api/scout/company

Research any company.

ParameterTypeRequiredDescription
namestringYesCompany name (e.g., "Stripe", "OpenAI")
domainstringNoCompany domain (e.g., "stripe.com"). Auto-detected if omitted.

Response fields: name, domain, description, industry, founded, headquarters, employee_range, funding, tech_stack, social_profiles, recent_news, top_competitors, key_people, confidence, confidence_breakdown, data_quality_grade, data_freshness, sources_used, sources_failed


POST /api/scout/market

Research any market or industry.

ParameterTypeRequiredDescription
querystringYesMarket to research (e.g., "AI SaaS", "electric vehicles")
depthstringNo"summary" (default) or "detailed"

Response fields: market_name, query, depth, market_size, market_size_projections, cagr, key_players, trends, growth_drivers, risks, source_links, confidence, confidence_breakdown, data_quality_grade


POST /api/scout/competitors

Find and analyze competitors.

ParameterTypeRequiredDescription
company_or_productstringYesCompany or product name (e.g., "Notion")
maxintegerNoMax competitors to return (default 10)

Response fields: target, competitors (array of {name, domain, positioning, pricing, strengths, weaknesses, key_differentiator}), market_positioning_summary, confidence, confidence_breakdown, data_quality_grade


POST /api/scout/trends

Track trends and sentiment.

ParameterTypeRequiredDescription
topicstringYesTopic to track (e.g., "generative AI")
timeframestringNo"1d", "7d" (default), "30d", "1y"

Response fields: topic, timeframe, sentiment ({score, label}), trending_direction, key_developments, related_topics, social_buzz, confidence, confidence_breakdown, data_quality_grade


POST /api/scout/product

Get intelligence on any product.

ParameterTypeRequiredDescription
namestringYesProduct name (e.g., "Slack", "Vercel")

Response fields: name, category, description, pricing, ratings, features, ideal_for, alternatives, recent_updates, confidence, confidence_breakdown, data_quality_grade


POST /api/scout/person (PRO)

Research a public figure. Requires Pro tier or higher.

ParameterTypeRequiredDescription
namestringYesPerson's name (e.g., "Sam Altman")
companystringNoCompany context (e.g., "OpenAI")

Read the full README β†’View source on GitHub β†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks β€” not a rating.

GitHub stars
2
Stargazers on the source repository.
Last commit
4mo ago
Most recent push to the default branch.
Directory activity
1 views
Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet β€” be the first to share how this listing worked for you.

Frequently Asked Questions about Scout Intel MCP

It aggregates data from DuckDuckGo, NewsAPI, Wikipedia, web scraping, and social profiles.

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Technical Specs & Signals

CategoryπŸ”ŽSearch & Data Extraction
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimePython
Last updatedAug 7, 2026
10/11 checks healthy over the last 32d
Views1
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars2
GitHub Star CountTotal stargazers on GitHub representing community popularity (2 stars).
Last commit4mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on May 3, 2026
47Quality signal: Fair Β· 47/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools23/30
Adoption & activity2/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 26d ago via OSV.dev Β· scout-mcp (PyPI)

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