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Model Context Protocol (MCP) Integration

Hindsight exposes its AI agent capabilities through the Model Context Protocol (MCP), allowing AI assistants to directly query your deal data, research competitors, and analyze pipeline metrics. Compatible with: Claude Desktop, Claude Code, ChatGPT, Cursor, Cline, and any MCP-compatible client. Generate an API key from Settings → API Keys in the Hindsight app before getting started.

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Setup

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Claude Desktop

Open your config file and add the Hindsight server:
  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json
{
  "mcpServers": {
    "hindsight": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://app.usehindsight.com/api/mcp", "--header", "Authorization: Bearer YOUR_API_KEY"]
    }
  }
}
Restart Claude Desktop after saving. For more details, see Anthropic’s MCP setup guide.

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Claude Code

Run this command in your terminal:
claude mcp add hindsight --transport http https://app.usehindsight.com/api/mcp \
  --header "Authorization: Bearer YOUR_API_KEY"

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Available Tools

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1. pull_schema

Fetch the schema of your deal grid — field names, types, and structure. Use this before create_dataset to understand what data is available.

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2. create_dataset

Export your deal grid data as a structured JSON dataset. Returns a json_id that you pass to analyze_deal_data.

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3. analyze_deal_data

Analyze quantitative deal data: win rates, trends, counts, and metrics across your pipeline. Requires a json_id from create_dataset. Parameters:
ParameterTypeDescription
questionstringThe data analysis question to answer
json_idstringDataset ID returned by create_dataset
Example flow: 
1. Call pull_schema → understand your deal fields
2. Call create_dataset → get a json_id
3. Call analyze_deal_data with your question + json_id
Example questions:
  • “What is our win rate by industry?”
  • “Which competitors do we lose to most often?”
  • “What’s the average deal size for closed won deals in Q1?“

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4. research_competitive_intel

Research competitive intelligence using Hindsight’s knowledge base and live web search. Handles multi-step research internally. Parameters:
ParameterTypeDescription
questionstringThe competitive intelligence question to research
Example questions:
  • “What are Salesforce’s main weaknesses based on our deals?”
  • “How should we position against HubSpot?”
  • “What recent news is there about Gong?“

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5. research_deals

Research qualitative insights from deal transcripts, emails, call recordings, and CRM notes. Handles multi-step document retrieval internally. Parameters:
ParameterTypeDescription
questionstringThe deal research question to investigate
Example questions:
  • “Why are we losing deals to Competitor X?”
  • “What objections come up most often in enterprise deals?”
  • “What did prospects say about our pricing in lost deals last quarter?”

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How It Works

Each tool delegates to Hindsight’s AI agent pipeline. When you call research_competitive_intel or research_deals, Hindsight runs a full multi-step agent behind the scenes — searching documents, querying your knowledge base, and synthesizing a response — and returns the final answer. For analyze_deal_data, Hindsight runs structured queries against your exported deal grid and computes the metrics you ask for.

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Authentication

MCP requests authenticate using your Hindsight API key as a Bearer token. Keys are scoped to your organization — all tools operate on your org’s data only. Generate an API key from Settings → API Keys in the Hindsight app.