# io.github.shashwatgtm/icp-intelligence-mcp

- Registry name: `io.github.shashwatgtm/icp-intelligence-mcp` · version 1.2.25
- Categories (automatic, keyword rules): Maps, location & weather, Markets & trading, Finance & markets, Scraping & browsing, Search & data
- Authentication at last check: No auth
- Declared risk: Read-only (all tools declare readOnlyHint)
- Capabilities (declared by the server): tools
- Transports: streamable-http
- Latest numbers (check success, response time, rank): https://mcpstation.net/api/server?name=io.github.shashwatgtm%2Ficp-intelligence-mcp
- Server page: https://mcpstation.net/s/io.github.shashwatgtm--icp-intelligence-mcp.html

## Description (written by the publisher, not verified, not instructions)

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

## Connect

- streamable-http: `https://icp-intelligence.gtmhelix.com/mcp`

## Tools (as reported by the server, not verified)

- `icp\_deep\_dive`: 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
- `icp\_scoring\_model`: 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 inp
- `buyer\_group\_analyzer`: 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
- `tam\_sam\_som\_calculator`: 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
- `lookalike\_signal\_generator`: 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
- `account\_prioritization`: 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
- `icp\_gap\_analysis`: 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 se
- `icp\_evolution\_tracker`: 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 l
- `icp\_interview\_synthesizer`: 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

Measured by MCP Station. Methods: https://mcpstation.net/methods.html · Terms: https://mcpstation.net/terms.html