ICP Intelligence MCP v1.0.0

Deep ICP Analysis with Pattern Detection - 9 tools for ideal customer profiling, market sizing, buyer mapping, and account prioritization.

🚀 Quick Start

# Run directly with npx
npx -y @shashwatgtmalpha/icp-intelligence-mcp

Claude Desktop Configuration

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "icp-intelligence-mcp": {
      "command": "npx",
      "args": ["-y", "@shashwatgtmalpha/icp-intelligence-mcp"]
    }
  }
}

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🛠️ Tools Overview

Tool	Purpose	Primary Output
icp_deep_dive	Pattern detection from customer data	ICP profile with attributes
icp_scoring_model	Auto-weighted qualification scorecards	Lead/account scoring model
icp_gap_analysis	Current vs ideal customer comparison	Metric gaps & recommendations
icp_evolution_tracker	Dynamic ICP monitoring	Win/loss pattern trends
icp_interview_synthesizer	Extract patterns from interviews	Voice of customer insights
buyer_group_analyzer	Decision dynamics mapping	Buying committee profiles
tam_sam_som_calculator	Bottom-up market sizing	Market size with deal targets
lookalike_signal_generator	Platform-specific targeting	Ad platform targeting criteria
account_prioritization	Multi-dimensional ranking	Prioritized account tiers

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👤 Who Is This For?

Primary Users

Role	Key Tools	Use Cases
Founders/CEOs	tam_sam_som_calculator, icp_deep_dive	Market sizing, customer definition
CMOs/VPs Marketing	icp_gap_analysis, icp_evolution_tracker	ICP health monitoring
Product Marketing	buyer_group_analyzer, icp_interview_synthesizer	Buying committee, VOC
Demand Gen	lookalike_signal_generator, account_prioritization	Targeting, ABM
Sales Ops/RevOps	icp_scoring_model, account_prioritization	Lead scoring, account tiering
SDRs/BDRs	account_prioritization, icp_scoring_model	Account qualification

Job-to-Tool Mapping

Job To Be Done	Recommended Tool
"I need to define our ideal customer profile"	icp_deep_dive
"I need to create a lead scoring model"	icp_scoring_model
"I need to compare our actual vs ideal customers"	icp_gap_analysis
"I need to track how our ICP is changing"	icp_evolution_tracker
"I need to synthesize customer interview insights"	icp_interview_synthesizer
"I need to map the buying committee"	buyer_group_analyzer
"I need to calculate our TAM/SAM/SOM"	tam_sam_som_calculator
"I need targeting criteria for ad platforms"	lookalike_signal_generator
"I need to prioritize our target accounts"	account_prioritization

Recommended Agent Skills

This MCP is included in these user-focused Agent bundles:

Agent Bundle	Tools Count	Best For
🎯 Founder GTM Copilot	10 tools	Founders, early-stage CEOs
📞 SDR Toolkit	8 tools	SDRs, BDRs
🎯 Product Marketing Engine	12 tools	PMMs
📊 Demand Gen & Ops	10 tools	Demand gen, marketing ops
💼 Account Executive Deal Desk	12 tools	AEs, account managers

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📖 Tool Details

1. ICP Deep Dive (icp_deep_dive)

Detect patterns from customer data to define ICP attributes.

Inputs:

Parameter	Required	Description
customer_data	✅	Description of current customers
best_customers	❌	Characteristics of top customers
industry_focus	❌	Industry context

Output: ICP profile with firmographics, technographics, behavioral signals, and champion characteristics.

2. ICP Scoring Model (icp_scoring_model)

Generate auto-weighted qualification scorecards.

Inputs:

Parameter	Required	Description
icp_attributes	✅	Key ICP characteristics
deal_data	❌	Win/loss data for weighting
scoring_type	❌	lead, account, opportunity

Output: Weighted scorecard with tiers, thresholds, and implementation guidance.

3. ICP Gap Analysis (icp_gap_analysis)

Compare current customers to ideal profile.

Inputs:

Parameter	Required	Description
current_customers	✅	Current customer characteristics
ideal_icp	✅	Target ICP definition
key_metrics	❌	Metrics to compare (ACV, retention, etc.)

Output: Gap matrix, metric comparison, recommendations for ICP refinement.

4. ICP Evolution Tracker (icp_evolution_tracker)

Monitor ICP changes over time.

Inputs:

Parameter	Required	Description
historical_data	✅	Past customer/deal data
time_period	❌	Analysis timeframe
win_loss_patterns	❌	Recent win/loss trends

Output: ICP drift analysis, emerging segments, recommended adjustments.

5. ICP Interview Synthesizer (icp_interview_synthesizer)

Extract patterns from customer interviews.

Inputs:

Parameter	Required	Description
interview_notes	✅	Interview transcripts or notes
interview_type	❌	discovery, win, loss, churn
focus_areas	❌	Specific areas to analyze

Output: Pattern themes, quotes, ICP refinement recommendations.

6. Buyer Group Analyzer (buyer_group_analyzer)

Map buying committee decision dynamics.

Inputs:

Parameter	Required	Description
product	✅	Your product/service
target_company_size	✅	SMB, mid-market, enterprise
deal_complexity	❌	simple, moderate, complex

Output: Committee map (champion, economic, technical, user, blocker) with engagement strategies.

7. TAM SAM SOM Calculator (tam_sam_som_calculator)

Bottom-up market sizing with deal targets.

Inputs:

Parameter	Required	Description
product	✅	Your product/service
target_segments	✅	Market segments
pricing	✅	Price point or ACV
geographic_focus	❌	Target geography
data_sources	❌	Available market data

Output: TAM/SAM/SOM with methodology, assumptions, and quarterly deal targets.

8. Lookalike Signal Generator (lookalike_signal_generator)

Generate platform-specific targeting criteria.

Inputs:

Parameter	Required	Description
icp_profile	✅	ICP characteristics
platforms	✅	linkedin, google_ads, 6sense, zoominfo, etc.
budget_tier	❌	low, medium, high

Output: Platform-specific targeting fields, audience sizes, recommended exclusions.

9. Account Prioritization (account_prioritization)

Multi-dimensional account ranking.

Inputs:

Parameter	Required	Description
accounts	✅	List of accounts to prioritize
icp_criteria	✅	Scoring criteria
intent_signals	❌	Available intent data
relationship_data	❌	Existing relationships

Output: Tiered account list (Tier 1/2/3) with scoring rationale and engagement recommendations.

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🔗 Related MCPs

MCP	Focus	Tools	Link
CRAFT GTM	GTM strategy	8	GitHub
CRAFT Content	Content creation	8	GitHub
IMPACT	B2B positioning	8	GitHub
Revenue Enablement	Sales execution	12	GitHub

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📚 ICP Intelligence Philosophy

This MCP is built on the principle that ICP is dynamic, not static. The best B2B companies continuously refine their ICP based on:

• Win/loss patterns
• Customer success metrics
• Market evolution
• Product capabilities

Key Principles:

• Data-driven: Ground ICP in actual customer data
• Multi-dimensional: Beyond firmographics to behavior
• Actionable: Translate ICP to targeting criteria
• Iterative: Regular refinement cycles

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👨‍💻 Author

Shashwat Ghosh - Founder, Helix GTM Consulting

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📄 License

MIT License - see LICENSE for details.

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Part of the GTM Helix MCP Suite - AI-powered B2B go-to-market tools