io.github.shashwatgtm/icp-intelligence-mcp

Measured conclusion: Deep-tested. L2 outcome: tools_ok.

ICP Intelligence: 9 ideal customer profile tools by Helix GTM Consulting

Add to your agent

Copy this into your MCP client config:

{
  "mcpServers": {
    "icp-intelligence-mcp": {
      "url": "https://icp-intelligence.gtmhelix.com/mcp",
      "transport": "streamable-http"
    }
  }
}

Measured tools (9)

• icp_deep_dive read-only

  Analyze customer data to detect ICP patterns (industry, size, deal size, sales cycle, tech stack, triggers, champion roles). Ties are named as ties, the budget is the ACV range seen in your customers, and sector notes are added when your inputs name one of the supported sectors

  Parameters:

  • company — string — Optional: your company or product name, so the answer can name it
  • customers — array — List of customer objects with available attributes
  • business_model — string — Optional: how you charge (software subscription, services, connectivity, per transaction, marketplace, hardware plus software, or investment management). Read from your other inputs when left out
  • product_category — string — What type of product you sell
  • customer_descriptions — string — Alternative: Describe your best customers in text format

  Hints: read-only yes · destructive no · idempotent not declared · open-world no

• icp_scoring_model read-only

  Create a lead qualification scoring template: criteria with example point weights set by importance level, example points for each value you list, a scorecard and tier bands to adjust. Your success pattern is matched to your criteria; it does not set the weights. Sector notes are added when your inputs name one of the supported sectors

  Parameters:

  • company — string — Optional: your company or product name, so the answer can name it
  • product_category — string — Optional: what you sell, as a product category, so the scoring notes use your sector
  • scoring_criteria — array — Criteria for scoring with importance levels
  • success_correlation — string — What correlates with success? (e.g., "deals with VP Sales champion close 2x faster")

  Hints: read-only yes · destructive no · idempotent not declared · open-world no

• buyer_group_analyzer read-only

  Map the buyer group for a deal: the champion you name, your known stakeholders placed by their titles (economic buyer, technical evaluator, reviewers, users), each role's concern and message prompts, an influence map and discovery questions. Sector roles and questions are added when your inputs name one of the supported sectors

  Parameters:

  • product_category (required) — string — What you sell
  • company — string — Optional: your company or product name, so the answer can name it
  • deal_size — string — ACV range (e.g., "$50K-100K")
  • business_model — string — Optional: how you charge (software subscription, services, connectivity, per transaction, marketplace, hardware plus software, or investment management). Read from your other inputs when left out
  • typical_champion — string — Your typical champion role
  • known_stakeholders — array — Roles you know are involved
  • target_company_size — string — Company size (e.g., "500-1000 employees")

  Hints: read-only yes · destructive no · idempotent not declared · open-world no

• tam_sam_som_calculator read-only

  Calculate TAM/SAM/SOM bottom-up from your company count, ACV, ICP match rate and Year 1 share (calculation framework, not a data source). Sector notes are added when your inputs name one of the supported sectors

  Parameters:

  • total_potential_companies (required) — number — Estimated total companies that could buy (from LinkedIn, industry reports)
  • average_contract_value (required) — number — Your average ACV in dollars
  • company — string — Optional: your company or product name, so the answer can name it
  • data_sources — string — Where you got your numbers (for documentation)
  • segment_name — string — Name of the market segment
  • icp_percentage — number — Percentage of those companies that match your ICP, from 0 to 100. Left out, 30 is used and marked as an example
  • product_category — string — Optional: what you sell (for example "spend management software"), used for sector notes. The arithmetic does not use it
  • year1_market_share_target — number — Realistic Year 1 market share percentage, from 0 to 100 (typically 1-5%). Left out, 3 is used and marked as an example

  Hints: read-only yes · destructive no · idempotent not declared · open-world no

• lookalike_signal_generator read-only

  Generate platform-specific targeting criteria and search queries from your firmographics, technographics, champion titles and buying triggers (generates criteria, not data). Each trigger gets its own signal; search keywords come from what you sell and the sector; platforms limits the sections

  Parameters:

  • champion_titles (required) — array — Job titles of your champions
  • company — string — Optional: your company or product name, so the answer can name it
  • platforms — array — Optional: the sections to include (linkedin, google_ads, 6sense, zoominfo). Left out, every section is included
  • buying_triggers — array — Events that trigger buying
  • product_category — string — Optional: what you sell (for example "spend management software"), used for search keywords and sector notes
  • icp_firmographics — object — Firmographic criteria
  • icp_technographics — array — Technologies your ICP typically uses

  Hints: read-only yes · destructive no · idempotent not declared · open-world no

• account_prioritization read-only

  Rank and prioritize accounts by a weighted score of fit, intent, relationship and timing; each account shows the points its timing earned and the factor that added the most points

  Parameters:

  • company — string — Optional: your company or product name, so the answer can name it
  • accounts — array — List of accounts to prioritize. Each account: name, fit_score (0 to 100), intent_signals (0 to 100), relationship (0 to 100), timing (now, soon, later or unknown)
  • product_category — string — Optional: what you sell (for example "spend management software"), used for sector notes. The arithmetic does not use it
  • prioritization_weights — 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

  Hints: read-only yes · destructive no · idempotent not declared · open-world no

• icp_gap_analysis read-only

  Analyze gaps between your current customer base and your ideal ICP: what the ideal profile has that the current base lacks, metric gaps from your current and target figures, causes to check and actions that fit your business model. Sector notes are added when your inputs name one of the supported sectors

  Parameters:

  • current_customers (required) — string — Description of your current customer base
  • ideal_icp (required) — string — Description of your ideal customer profile
  • company — string — Optional: your company or product name, so the answer can name it
  • business_model — string — Optional: how you charge (software subscription, services, connectivity, per transaction, marketplace, hardware plus software, or investment management). Read from your other inputs when left out
  • target_metrics — object — Target performance metrics
  • current_metrics — object — Current performance metrics
  • product_category — string — Optional: what you sell, used for sector notes

  Hints: read-only yes · destructive no · idempotent not declared · open-world no

• icp_evolution_tracker read-only

  Review how your ICP should evolve: reads your recent wins, losses and market changes against your current ICP, states a candidate change for each (an addition to test, a disqualifier to test, an implication to check) and writes a draft of the updated ICP, with the roles your ICP does not name, the loss reasons to tag and what to pull from your CRM. It does not compute win rates; check each candidate against your CRM

  Parameters:

  • current_icp (required) — string — Your current ICP definition
  • company — string — Optional: your company or product name, so the answer can name it
  • recent_wins — string — Description of recent successful customers
  • time_period — string — Time period you are reviewing, in your own words (for example "last quarter")
  • recent_losses — string — Description of recent lost deals
  • market_changes — string — Recent market or competitive changes
  • product_category — string — Optional: what you sell, used for sector notes

  Hints: read-only yes · destructive no · idempotent not declared · open-world no

• icp_interview_synthesizer read-only

  Extract ICP patterns from customer interview notes: pain points, objections, buying triggers, value realized, champion roles and quotes kept word for word, with discovery questions and sector notes. Pasted notes are shown back (shortened) with a template to structure them; only structured notes are analyzed.

  Parameters:

  • company — string — Optional: your company or product name, so the answer can name it
  • analysis_focus — string — Accepted but not used yet: every run gives the complete analysis (pain_points, buying_journey, value_props, all)
  • interview_notes — array — Structured interview notes
  • raw_transcripts — string — Alternative: paste interview notes or transcripts. This tool does not analyze pasted text: it shows up to 500 characters back with a template to structure them as interview_notes, which it does analyze
  • product_category — string — Optional: what you sell, used for sector notes

  Hints: read-only yes · destructive no · idempotent not declared · open-world no

Publisher website Repository

Measured by MCPYP probing. Untested fields are omitted, never estimated. Listing is always free; MCPYP never proxies calls or stores user tokens.