ICP Intelligence MCP

ICP Intelligence MCP

Enables deep ICP analysis with 9 tools for ideal customer profiling, market sizing, buyer mapping, and account prioritization.

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README

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.

NPM Version License: MIT MCP Registry

🚀 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"]
    }
  }
}

🛠️ 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

👤 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

📖 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.


🔗 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

📚 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

👨‍💻 Author

Shashwat Ghosh - Founder, Helix GTM Consulting

LinkedIn Twitter Website


📄 License

MIT License - see LICENSE for details.


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

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