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How to Connect Heap to Gemini — via MCP

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

HCBy HelpCode teamUpdated 2 min read Open source on GitHub

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MCP connector

Heap

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

Tools

5

Region

INTL

Category

analytics

Authentication

Public API

Required env vars

HEAP_APP_ID
Install in one click on Cloud

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  • 7-day free trial
    No credit card required
  • GDPR & SOC 2 ready
    EU data residency, audit logs
  • Open-source on GitHub
    Source-available BSL-1.1
  • Works with ChatGPT, Claude, Gemini
    Any MCP-compatible client

No install? Use cloud.anythingmcp.com directly.

Sign in, install the Heap in one click, paste the credentials, mint an MCP API key — done. No Docker, no git clone, no local server to run.

Open Cloud

TL;DR

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

💡 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

heap.io/docs/server-side-apis).

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

git clone https://github.com/HelpCode-ai/anythingmcp.git
cd anythingmcp && docker compose up -d

Step 3 — Add the connector in Gemini

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",
      "headers": { "Authorization": "Bearer YOUR_MCP_API_KEY" }
    }
  }
}
  1. Get your MCP API key from AnythingMCP → Profile → MCP API Keys → New Key.
  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 to the tools array of your request with the same Bearer header.

Available tools

ToolWhat it does
heap_track_eventTrack a single behavioral event for a user
heap_bulk_trackBulk-track many events in one call (up to 1000 events, 1MB total)
heap_add_user_propertiesSet or update user-level properties (Heap merges with existing)
heap_add_account_propertiesSet or update properties on an account (B2B model — accounts group users)
heap_add_user_to_accountAssociate a user (identity) with an account (account_id)

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 Bearer headers.

Next steps

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