ICP Intelligence

You can deploy and run the ICP Intelligence MCP to perform deep ICP analysis, pattern detection from customer data, and multi-tool insights for market sizing, buyer mapping, and account prioritization. This MCP server provides a collection of tools that operate together to help you define and refine your ideal customer profile, evaluate accounts, and drive go-to-market decisions with data-driven guidance.

How to use

To use this MCP server, deploy it behind an MCP client and invoke the available tools to analyze customer data, generate ICP profiles, and prioritize target accounts. You can start by running the MCP directly with an MCP-compatible client, then call the individual tools to perform pattern detection, gap analysis, evolution tracking, interview synthesis, and more. The outputs are designed to feed targeting criteria, scoring models, and account tiers that you can act on within your sales and marketing workflows.

How to install

Prerequisites: You need Node.js installed on your machine. You should also have an MCP client that can load and interact with MCP servers.

Step 1: Ensure Node.js is installed on your system. You can download it from the official Node.js website or use a package manager for your operating system.

Step 2: Run the MCP server directly using the MCP client. Use the quick start command below to start the server in your environment.

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

Configuration and usage notes

You can configure clients to connect to the MCP server by declaring the MCP server in your client configuration. For example, a Claude Desktop configuration entry can map the MCP server to the package you run, using an npx invocation.

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

Security, access, and tips

Treat the MCP server as a backend processing unit for ICP analysis. Ensure you run it in a trusted environment and manage access to the MCP client that interacts with it. Rotate any tokens or keys used by your client to access outputs when applicable, and monitor usage to ensure that sensitive customer data remains secure throughout the analysis pipeline.

Additional notes

The MCP is designed to be flexible and extensible. As you integrate outputs into your GTM workflows, you can leverage tool-specific outputs such as ICP profiles, scoring models, gap analyses, evolution trends, and buyer group mappings to inform targeting criteria, ABM campaigns, and account prioritization.

Available tools

icp_deep_dive

Detect patterns from customer data to define ICP attributes, producing an ICP profile with firmographics, technographics, behavioral signals, and champion characteristics.

icp_scoring_model

Generate auto-weighted qualification scorecards, producing a weighted scoring model with tiers, thresholds, and implementation guidance.

icp_gap_analysis

Compare current customers to the ideal ICP, yielding a gap matrix, metric comparisons, and recommendations for ICP refinement.

icp_evolution_tracker

Monitor ICP changes over time, providing drift analysis, emerging segments, and recommended adjustments.

icp_interview_synthesizer

Extract patterns from interviews, returning pattern themes, quotes, and ICP refinement recommendations.

buyer_group_analyzer

Map buying committee decision dynamics, delivering a committee map with engagement strategies.

tam_sam_som_calculator

Bottom-up market sizing with deal targets, producing TAM/SAM/SOM with methodology and quarterly targets.

lookalike_signal_generator

Generate platform-specific targeting criteria and audience sizes for ad platforms.

account_prioritization

Rank accounts across multiple dimensions, producing tiered lists and engagement recommendations.