Google Analytics Automation via Rube MCP

Automate Google Analytics 4 (GA4) reporting and property management through Composio's Google Analytics toolkit via Rube MCP.

Prerequisites

• Rube MCP must be connected (RUBE_SEARCH_TOOLS available)
• Active Google Analytics connection via RUBE_MANAGE_CONNECTIONS with toolkit google_analytics
• Always call RUBE_SEARCH_TOOLS first to get current tool schemas

Setup

Get Rube MCP: Add https://rube.app/mcp as an MCP server in your client configuration. No API keys needed — just add the endpoint and it works.

1. Verify Rube MCP is available by confirming RUBE_SEARCH_TOOLS responds
2. Call RUBE_MANAGE_CONNECTIONS with toolkit google_analytics
3. If connection is not ACTIVE, follow the returned auth link to complete Google OAuth
4. Confirm connection status shows ACTIVE before running any workflows

Core Workflows

1. List Accounts and Properties

When to use: User wants to discover available GA4 accounts and properties

Tool sequence:

1. GOOGLE_ANALYTICS_LIST_ACCOUNTS - List all accessible GA4 accounts [Required]
2. GOOGLE_ANALYTICS_LIST_PROPERTIES - List properties under an account [Required]

Key parameters:

• pageSize: Number of results per page
• pageToken: Pagination token from previous response
• filter: Filter expression for properties (e.g., parent:accounts/12345)

Pitfalls:

• Property IDs are numeric strings prefixed with 'properties/' (e.g., 'properties/123456')
• Account IDs are prefixed with 'accounts/' (e.g., 'accounts/12345')
• Always list accounts first, then properties under each account
• Pagination required for organizations with many properties

2. Run Standard Reports

When to use: User wants to query metrics and dimensions from GA4 data

Tool sequence:

1. GOOGLE_ANALYTICS_LIST_PROPERTIES - Get property ID [Prerequisite]
2. GOOGLE_ANALYTICS_GET_METADATA - Discover available dimensions and metrics [Optional]
3. GOOGLE_ANALYTICS_CHECK_COMPATIBILITY - Verify dimension/metric compatibility [Optional]
4. GOOGLE_ANALYTICS_RUN_REPORT - Execute the report query [Required]

Key parameters:

• property: Property ID (e.g., 'properties/123456')
• dateRanges: Array of date range objects with startDate and endDate
• dimensions: Array of dimension objects with name field
• metrics: Array of metric objects with name field
• dimensionFilter / metricFilter: Filter expressions
• orderBys: Sort order configuration
• limit: Maximum rows to return
• offset: Row offset for pagination

Pitfalls:

• Date format is 'YYYY-MM-DD' or relative values like 'today', 'yesterday', '7daysAgo', '30daysAgo'
• Not all dimensions and metrics are compatible; use CHECK_COMPATIBILITY first
• Use GET_METADATA to discover valid dimension and metric names
• Maximum 9 dimensions per report request
• Row limit defaults vary; set explicitly for large datasets
• offset is for result pagination, not date pagination

3. Run Batch Reports

When to use: User needs multiple different reports from the same property in one call

Tool sequence:

1. GOOGLE_ANALYTICS_LIST_PROPERTIES - Get property ID [Prerequisite]
2. GOOGLE_ANALYTICS_BATCH_RUN_REPORTS - Execute multiple reports at once [Required]

Key parameters:

• property: Property ID (required)
• requests: Array of individual report request objects (same structure as RUN_REPORT)

Pitfalls:

• Maximum 5 report requests per batch call
• All reports in a batch must target the same property
• Each individual report has the same dimension/metric limits as RUN_REPORT
• Batch errors may affect all reports; check individual report responses

4. Run Pivot Reports

When to use: User wants cross-tabulated data (rows vs columns) like pivot tables

Tool sequence:

1. GOOGLE_ANALYTICS_LIST_PROPERTIES - Get property ID [Prerequisite]
2. GOOGLE_ANALYTICS_RUN_PIVOT_REPORT - Execute pivot report [Required]

Key parameters:

• property: Property ID (required)
• dateRanges: Date range objects
• dimensions: All dimensions used in any pivot
• metrics: Metrics to aggregate
• pivots: Array of pivot definitions with fieldNames, limit, and orderBys

Pitfalls:

• Dimensions used in pivots must also be listed in top-level dimensions
• Pivot fieldNames reference dimension names from the top-level list
• Complex pivots with many dimensions can produce very large result sets

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