Icp Intelligence Mcp

ICP Intelligence MCP v1.2.24

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

Use it hosted (no install)

Add https://icp-intelligence.gtmhelix.com/mcp to Claude or ChatGPT as a custom connector. It needs no sign-in and always runs the newest version (1.2.24). The same tools run as a free web app with a form per tool at https://icp-intelligence.gtmhelix.com/, and the setup steps are at https://icp-intelligence.gtmhelix.com/connect/.

The npm package below is an older version (1.0.0 on npm on 27 September 2026) until the next npm release. Use it only if you need a local stdio server.

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 and inputs

Generated on 27 September 2026 from the server's own tool list, and checked again on 16 October 2026 against tools/list of icp-intelligence-mcp 1.2.24 (the same code as the hosted MCP address), so every tool name, title, description and input below is exactly what the server accepts. Every tool is read-only.

#	Tool	Title	What it does
1	icp_deep_dive	ICP Deep Dive	Analyze customer data to detect ICP patterns: firmographics, technographics, buying behavior
2	icp_scoring_model	ICP Scoring Model	Create a lead qualification scoring template: criteria with example point weights set by importance level, a scorecard and tier bands to adjust. Your success patterns are shown for reference; they do not set the weights
3	buyer_group_analyzer	Buyer Group Analyzer	Map buyer group dynamics, influence relationships, and decision-making process
4	tam_sam_som_calculator	TAM SAM SOM Calculator	Calculate TAM/SAM/SOM using bottom-up methodology from your data (calculation framework, not data source)
5	lookalike_signal_generator	Lookalike Signal Generator	Generate platform-specific targeting criteria and search queries (generates criteria, not data)
6	account_prioritization	Account Prioritization	Rank and prioritize accounts using multi-dimensional scoring
7	icp_gap_analysis	ICP Gap Analysis	Analyze gaps between current customer base and ideal ICP
8	icp_evolution_tracker	ICP Evolution Tracker	Checklist for reviewing how your ICP should evolve: shows your recent wins, losses and market changes next to what to check. It does not analyze the text
9	icp_interview_synthesizer	ICP Interview Synthesizer	Extract ICP patterns from customer interview notes. Pasted notes are shown back with a template to structure them; only structured notes are analysed.

Inputs of each tool

1. ICP Deep Dive (icp_deep_dive)

Input	Required	Type	Description
customers	No	array of object	List of customer objects with available attributes
customer_descriptions	No	string	Alternative: Describe your best customers in text format
product_category	No	string	What type of product you sell

2. ICP Scoring Model (icp_scoring_model)

Input	Required	Type	Description
scoring_criteria	No	array of object	Criteria for scoring with importance levels
success_correlation	No	string	What correlates with success? (e.g., "deals with VP Sales champion close 2x faster")
product_category	No	string

3. Buyer Group Analyzer (buyer_group_analyzer)

Input	Required	Type	Description
product_category	Yes	string	What you sell
deal_size	No	string	ACV range (e.g., "$50K-100K")
target_company_size	No	string	Company size (e.g., "500-1000 employees")
known_stakeholders	No	array of string	Roles you know are involved
typical_champion	No	string	Your typical champion role

4. TAM SAM SOM Calculator (tam_sam_som_calculator)

Input	Required	Type	Description
total_potential_companies	Yes	number (0 or more)	Estimated total companies that could buy (from LinkedIn, industry reports)
average_contract_value	Yes	number (more than 0)	Your average ACV in dollars
icp_percentage	No	number (0 or more)	Percentage that match your ICP (1-100)
year1_market_share_target	No	number (0 or more)	Realistic Year 1 market share percentage (typically 1-5%)
data_sources	No	string	Where you got your numbers (for documentation)
segment_name	No	string	Name of the market segment

5. Lookalike Signal Generator (lookalike_signal_generator)

Input	Required	Type	Description
champion_titles	Yes	array of string	Job titles of your champions
icp_firmographics	No	object	Firmographic criteria
icp_technographics	No	array of string	Technologies your ICP typically uses
buying_triggers	No	array of string	Events that trigger buying
platforms	No	array of string	Accepted but not used yet: the output always includes every platform section (linkedin, google_ads, 6sense, zoominfo)

6. Account Prioritization (account_prioritization)

Input	Required	Type	Description
accounts	No	array of object	List of accounts to prioritize. Each account: name, fit_score (0 to 100), intent_signals (0 to 100), relationship, timing
prioritization_weights	No	object	Optional custom weights in percent for fit, intent, relationship and timing. A missing weight uses its default (40, 30, 15, 15); the tool does not check that the weights sum to 100

7. ICP Gap Analysis (icp_gap_analysis)

Input	Required	Type	Description
current_customers	Yes	string	Description of your current customer base
ideal_icp	Yes	string	Description of your ideal customer profile
current_metrics	No	object	Current performance metrics
target_metrics	No	object	Target performance metrics

8. ICP Evolution Tracker (icp_evolution_tracker)

Input	Required	Type	Description
current_icp	Yes	string	Your current ICP definition
recent_wins	No	string	Description of recent successful customers
recent_losses	No	string	Description of recent lost deals
market_changes	No	string	Recent market or competitive changes
time_period	No	string	Time period for analysis (e.g., "Q4 2024")

9. ICP Interview Synthesizer (icp_interview_synthesizer)

Input	Required	Type	Description
interview_notes	No	array of object	Structured interview notes
raw_transcripts	No	string	Alternative: Paste raw interview transcripts or notes
analysis_focus	No	string	Accepted but not used yet: every run gives the complete analysis (pain_points, buying_journey, value_props, all)

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

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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, Co-Founder and Fractional CMO, Helix GTM Consulting, with 24+ years in B2B and 10+ years of fractional experience

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License

MIT License: see LICENSE for details.

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Part of the Helix GTM Consulting MCP suite: rule-based B2B go-to-market tools (no AI model runs inside them)

Hosted connector (Streamable HTTP)

The same tools are also available as a hosted MCP server, so they work in Claude on the web, desktop and mobile without installing anything.

• Server URL: https://icp-intelligence.gtmhelix.com/mcp
• Transport: Streamable HTTP (stateless, JSON responses). Authentication: none.
• Setup guide: https://icp-intelligence.gtmhelix.com/connect/
• In Claude: Customize, then Connectors, then Add custom connector, and paste the server URL.
• In Claude Code: claude mcp add --transport http icp-intelligence https://icp-intelligence.gtmhelix.com/mcp

The npm package (stdio) and the hosted server run the same createServer() code in src/index.ts.

The tool reference on the docs page (https://icp-intelligence.gtmhelix.com/docs/) is generated from the code. Where it differs from the parameter tables earlier in this README, the docs page is correct.

Privacy Policy

Full policy: https://icp-intelligence.gtmhelix.com/privacy/ (also in PRIVACY.md).

• Data collection: the hosted server receives only the tool name and the inputs of each tool call. The npm package runs on your computer and sends nothing to us.
• Use and storage: inputs are used only to build that call's reply. Nothing is stored: no database, no files, no cache, no logging of inputs or outputs by our code.
• Third-party sharing: none by us. Netlify hosts the server and processes requests under its own policy (https://www.netlify.com/privacy/). Fonts are served from this site, so loading a page contacts no one else.
• Retention: we keep no tool inputs or outputs. Netlify keeps its own platform logs under its policy.
• Contact: shashwat@gtmhelix.com