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Icp Intelligence MCP

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Deep ICP Analysis with Pattern Detection - 9 B2B targeting tools

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
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": {
    "icp-intelligence-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "icp-intelligence-mcp"
      ]
    }
  }
}

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

Install Directory Badge Claim listing AlternativesπŸ’» More in Developer Tools

Documentation Overview

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

πŸš€ Quick Start

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

Claude Desktop Configuration

Add to your claude_desktop_config.json:

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

πŸ› οΈ 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

πŸ‘€ 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
πŸ“ž SDR Toolkit8 toolsSDRs, BDRs
🎯 Product Marketing Engine12 toolsPMMs
πŸ“Š Demand Gen & Ops10 toolsDemand gen, marketing ops
πŸ’Ό Account Executive Deal Desk12 toolsAEs, account managers

πŸ“– Tool Details

1. ICP Deep Dive (icp_deep_dive)

Detect patterns from customer data to define ICP attributes.

Inputs:

ParameterRequiredDescription
customer_dataβœ…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:

ParameterRequiredDescription
icp_attributesβœ…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:

ParameterRequiredDescription
current_customersβœ…Current customer characteristics
ideal_icpβœ…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:

ParameterRequiredDescription
historical_dataβœ…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:

ParameterRequiredDescription
interview_notesβœ…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:

ParameterRequiredDescription
productβœ…Your product/service
target_company_sizeβœ…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:

ParameterRequiredDescription
productβœ…Your product/service
target_segmentsβœ…Market segments
pricingβœ…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:

ParameterRequiredDescription
icp_profileβœ…ICP characteristics
platformsβœ…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:

ParameterRequiredDescription
accountsβœ…List of accounts to prioritize
icp_criteriaβœ…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.


πŸ”— Related MCPs

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

πŸ“š 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

πŸ‘¨β€πŸ’» Author

Shashwat Ghosh - Founder, Helix GTM Consulting

LinkedIn Twitter Website


πŸ“„ License

MIT License - see LICENSE for details.


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

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

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Frequently Asked Questions about Icp Intelligence MCP

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "icp-intelligence-mcp": { "command": "npx", "args": ["-y", "icp-intelligence-mcp"] } }

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Technical Specs & Signals

CategoryπŸ’»Developer Tools
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimeNode.js
Last updatedSep 7, 2026
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25Quality signal: Emerging Β· 25/100How this signal is calculated β–Ύ
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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 ownership8/20
Documentation & tools10/30
Adoption & activity1/15
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.

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