How to Connect Heap to Gemini — via MCP

💡 No install? Use cloud.anythingmcp.com directly. Sign in, click Connectors → Heap, paste your credentials, mint an MCP API key — done. No Docker, no git clone, no local server.

Heap + Gemini

Send events, identify users and update properties in Heap (product analytics) from any AI agent. 5 tools, app_id-based auth.

Prerequisites

See the full setup instructions baked into the connector (visible in the in-app store when you select the connector). The required environment variables for this connector are:

HEAP_APP_ID

Step 1 — Get credentials

Setup:

1. Sign in to https://app.heap.io → top-right → Account → Projects → select project → Project ID (called app_id).
2. Set HEAP_APP_ID to the numeric app/project ID.

Authentication: NONE — Heap's server-side API uses the app_id in the request body to route events to your project. There's no secret on the ingestion endpoint (anyone with your app_id can fake events — same trust model as Google Analytics client-side JS).

…(continued in the in-app connector instructions)

Step 2 — Install the adapter

curl -fsSL https://raw.githubusercontent.com/HelpCode-ai/anythingmcp/main/docker-compose.quickstart.yml -o docker-compose.yml
printf 'JWT_SECRET=%s\nENCRYPTION_KEY=%s\n' "$(openssl rand -hex 32)" "$(openssl rand -hex 32)" > .env
docker compose up -d

Step 3 — Add the connector in Gemini

Your server URL: in AnythingMCP, open MCP Servers → the server this connector is on, and copy its URL (https://cloud.anythingmcp.com/mcp/…). Use it wherever this guide shows YOUR_SERVER_ID.

Gemini CLI reads MCP servers from ~/.gemini/settings.json (or %APPDATA%\gemini\settings.json on Windows). Add:

{
  "mcpServers": {
    "anythingmcp": {
      "httpUrl": "https://cloud.anythingmcp.com/mcp/YOUR_SERVER_ID",
      "headers": { "X-API-Key": "YOUR_MCP_API_KEY" }
    }
  }
}

1. Get your MCP API key from AnythingMCP → MCP Servers → your server → API keys.
2. Save the file and restart gemini.
3. Run /mcp inside the Gemini CLI — Heap should be listed as available.
4. Vertex AI Studio: pass https://cloud.anythingmcp.com/mcp/YOUR_SERVER_ID to the tools array of your request with the same X-API-Key header.

Available tools

FAQ

Does Gemini 1.5 Pro or 2.x support MCP? Yes — Gemini CLI ≥ 0.4 and Vertex AI tools API both accept MCP httpUrl connectors with custom headers.

Next steps

• Connector landing page
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• Connect to ChatGPT
• Connect to Cursor
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