Repository avatar
Other Tools
v1.0.0
active

icp-intelligence-mcp

io.github.shashwatgtm/icp-intelligence-mcp

Deep ICP Analysis with Pattern Detection - 9 B2B targeting tools

Documentation

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

ToolPurposePrimary Output
icp_deep_divePattern detection from customer dataICP profile with attributes
icp_scoring_modelAuto-weighted qualification scorecardsLead/account scoring model
icp_gap_analysisCurrent vs ideal customer comparisonMetric gaps & recommendations
icp_evolution_trackerDynamic ICP monitoringWin/loss pattern trends
icp_interview_synthesizerExtract patterns from interviewsVoice of customer insights
buyer_group_analyzerDecision dynamics mappingBuying committee profiles
tam_sam_som_calculatorBottom-up market sizingMarket size with deal targets
lookalike_signal_generatorPlatform-specific targetingAd platform targeting criteria
account_prioritizationMulti-dimensional rankingPrioritized account tiers

👤 Who Is This For?

Primary Users

RoleKey ToolsUse Cases
Founders/CEOstam_sam_som_calculator, icp_deep_diveMarket sizing, customer definition
CMOs/VPs Marketingicp_gap_analysis, icp_evolution_trackerICP health monitoring
Product Marketingbuyer_group_analyzer, icp_interview_synthesizerBuying committee, VOC
Demand Genlookalike_signal_generator, account_prioritizationTargeting, ABM
Sales Ops/RevOpsicp_scoring_model, account_prioritizationLead scoring, account tiering
SDRs/BDRsaccount_prioritization, icp_scoring_modelAccount qualification

Job-to-Tool Mapping

Job To Be DoneRecommended 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 BundleTools CountBest For
🎯 Founder GTM Copilot10 toolsFounders, early-stage CEOs
📞 SDR Toolkit8 toolsSDRs, BDRs
🎯 Product Marketing Engine12 toolsPMMs
📊 Demand Gen & Ops10 toolsDemand gen, marketing ops
💼 Account Executive Deal Desk12 toolsAEs, account managers

📖 Tool Details

1. ICP Deep Dive (icp_deep_dive)

Detect patterns from customer data to define ICP attributes.

Inputs:

ParameterRequiredDescription
customer_dataDescription of current customers
best_customersCharacteristics of top customers
industry_focusIndustry 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:

ParameterRequiredDescription
icp_attributesKey ICP characteristics
deal_dataWin/loss data for weighting
scoring_typelead, 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:

ParameterRequiredDescription
current_customersCurrent customer characteristics
ideal_icpTarget ICP definition
key_metricsMetrics 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:

ParameterRequiredDescription
historical_dataPast customer/deal data
time_periodAnalysis timeframe
win_loss_patternsRecent win/loss trends

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

5. ICP Interview Synthesizer (icp_interview_synthesizer)

Extract patterns from customer interviews.

Inputs:

ParameterRequiredDescription
interview_notesInterview transcripts or notes
interview_typediscovery, win, loss, churn
focus_areasSpecific areas to analyze

Output: Pattern themes, quotes, ICP refinement recommendations.

6. Buyer Group Analyzer (buyer_group_analyzer)

Map buying committee decision dynamics.

Inputs:

ParameterRequiredDescription
productYour product/service
target_company_sizeSMB, mid-market, enterprise
deal_complexitysimple, 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:

ParameterRequiredDescription
productYour product/service
target_segmentsMarket segments
pricingPrice point or ACV
geographic_focusTarget geography
data_sourcesAvailable 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:

ParameterRequiredDescription
icp_profileICP characteristics
platformslinkedin, google_ads, 6sense, zoominfo, etc.
budget_tierlow, medium, high

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

9. Account Prioritization (account_prioritization)

Multi-dimensional account ranking.

Inputs:

ParameterRequiredDescription
accountsList of accounts to prioritize
icp_criteriaScoring criteria
intent_signalsAvailable intent data
relationship_dataExisting relationships

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


🔗 Related MCPs

MCPFocusToolsLink
CRAFT GTMGTM strategy8GitHub
CRAFT ContentContent creation8GitHub
IMPACTB2B positioning8GitHub
Revenue EnablementSales execution12GitHub

📚 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