Segment Automation

Segment Automation via Rube MCP

Automate Segment customer data platform operations through Composio's Segment toolkit via Rube MCP.

Prerequisites

• Rube MCP must be connected (RUBE_SEARCH_TOOLS available)
• Active Segment connection via RUBE_MANAGE_CONNECTIONS with toolkit segment
• 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 segment
3. If connection is not ACTIVE, follow the returned auth link to complete Segment authentication
4. Confirm connection status shows ACTIVE before running any workflows

Core Workflows

1. Track Events

When to use: User wants to send event data to Segment for downstream destinations

Tool sequence:

1. SEGMENT_TRACK - Send a single track event [Required]

Key parameters:

• userId: User identifier (required if no anonymousId)
• anonymousId: Anonymous identifier (required if no userId)
• event: Event name (e.g., 'Order Completed', 'Button Clicked')
• properties: Object with event-specific properties
• timestamp: ISO 8601 timestamp (optional; defaults to server time)
• context: Object with contextual metadata (IP, user agent, etc.)

Pitfalls:

• At least one of userId or anonymousId is required
• event name is required and should follow consistent naming conventions
• Properties are freeform objects; ensure consistent schema across events
• Timestamp must be ISO 8601 format (e.g., '2024-01-15T10:30:00Z')
• Events are processed asynchronously; successful API response means accepted, not delivered

2. Identify Users

When to use: User wants to associate traits with a user profile in Segment

Tool sequence:

1. SEGMENT_IDENTIFY - Set user traits and identity [Required]

Key parameters:

• userId: User identifier (required if no anonymousId)
• anonymousId: Anonymous identifier
• traits: Object with user properties (email, name, plan, etc.)
• timestamp: ISO 8601 timestamp
• context: Contextual metadata

Pitfalls:

• At least one of userId or anonymousId is required
• Traits are merged with existing traits, not replaced
• To remove a trait, set it to null
• Identify calls should be made before track calls for new users
• Avoid sending PII in traits unless destinations are configured for it

3. Batch Operations

When to use: User wants to send multiple events, identifies, or other calls in a single request

Tool sequence:

1. SEGMENT_BATCH - Send multiple Segment calls in one request [Required]

Key parameters:

• batch: Array of message objects, each with:
  • type: Message type ('track', 'identify', 'group', 'page', 'alias')
  • userId / anonymousId: User identifier
  • Additional fields based on type (event, properties, traits, etc.)

Pitfalls:

• Each message in the batch must have a valid type field
• Maximum batch size limit applies; check schema for current limit
• All messages in a batch are processed independently; one failure does not affect others
• Each message must independently satisfy its type's requirements (e.g., track needs event name)
• Batch is the most efficient way to send multiple calls; prefer over individual calls

4. Group Users

When to use: User wants to associate a user with a company, team, or organization

Tool sequence:

1. SEGMENT_GROUP - Associate user with a group [Required]

Key parameters:

• userId: User identifier (required if no anonymousId)
• anonymousId: Anonymous identifier
• groupId: Group/organization identifier (required)
• traits: Object with group properties (name, industry, size, plan)
• timestamp: ISO 8601 timestamp

Pitfalls:

• groupId is required; it identifies the company or organization
• Group traits are merged with existing traits for that group
• A user can belong to multiple groups
• Group traits update the group profile, not the user profile

5. Track Page Views

When to use: User wants to record page view events in Segment

Tool sequence:

1. SEGMENT_PAGE - Send a page view event [Required]

Key parameters:

• userId: User identifier (required if no anonymousId)
• anonymousId: Anonymous identifier
• name: Page name (e.g., 'Home', 'Pricing', 'Dashboard')
• category: Page category (e.g., 'Docs', 'Marketing')
• properties: Object with page-specific properties (url, title, referrer)

Pitfalls:

• At least one of userId or anonymousId is required
• name and category are optional but recommended for proper analytics
• Standard properties include url, title, referrer, path, search
• Page calls are often automated; manual use is for server-side page tracking

6. Alias Users and Manage Sources

When to use: User wants to merge anonymous and identified users, or manage source configuration

Tool sequence:

1. SEGMENT_ALIAS - Link two user identities together [Optional]
2. SEGMENT_LIST_SCHEMA_SETTINGS_IN_SOURCE - View source schema settings [Optional]
3. SEGMENT_UPDATE_SOURCE - Update source configuration [Optional]

Key parameters:

• For ALIAS:
  • userId: New user identifier (the identified ID)
  • previousId: Old user identifier (the anonymous ID)
• For source operations:
  • sourceId: Source identifier

Pitfalls:

• ALIAS is a one-way operation; cannot be undone
• previousId is the anonymous/old ID, userId is the new/identified ID
• Not all destinations support alias calls; check destination documentation
• ALIAS should be called once when a user first identifies (e.g., signs up)
• Source updates may affect data collection; review changes carefully

Common Patterns

User Lifecycle

Standard Segment user lifecycle:

1. Anonymous user visits -> PAGE call with anonymousId
2. User interacts -> TRACK call with anonymousId
3. User signs up -> ALIAS (anonymousId -> userId), then IDENTIFY with traits
4. User takes action -> TRACK call with userId
5. User joins org -> GROUP call linking userId to groupId

Batch Optimization

For bulk data ingestion:

1. Collect events in memory (array of message objects)
2. Each message includes type, userId/anonymousId, and type-specific fields
3. Call SEGMENT_BATCH with the collected messages
4. Check response for any individual message errors

Naming Conventions

Segment recommends consistent event naming:

• Events: Use "Object Action" format (e.g., 'Order Completed', 'Article Viewed')
• Properties: Use snake_case (e.g., 'order_total', 'product_name')
• Traits: Use snake_case (e.g., 'first_name', 'plan_type')

Known Pitfalls

Identity Resolution:

• Always include userId or anonymousId on every call
• Use ALIAS only once per user identity merge
• Identify before tracking to ensure proper user association

Data Quality:

• Event names should be consistent across all sources
• Properties should follow a defined schema for downstream compatibility
• Avoid sending sensitive PII unless destinations are configured for it

Rate Limits:

• Use BATCH for bulk operations to stay within rate limits
• Individual calls are rate-limited per source
• Batch calls are more efficient and less likely to be throttled

Response Parsing:

• Successful responses indicate acceptance, not delivery to destinations
• Response data may be nested under data key
• Check for error fields in batch responses for individual message failures

Timestamps:

• Must be ISO 8601 format with timezone (e.g., '2024-01-15T10:30:00Z')
• Omitting timestamp uses server receive time
• Historical data imports should include explicit timestamps

Quick Reference

When to Use

This skill is applicable to execute the workflow or actions described in the overview.

AGI Framework Integration

Adapted for @techwavedev/agi-agent-kit Original source: antigravity-awesome-skills

Memory-First Protocol

Cache workflow configurations and automation patterns. Retrieve prior pipeline designs to avoid re-building similar flows from scratch.

# Check for prior workflow/automation context before starting
python3 execution/memory_manager.py auto --query "automation patterns and workflow configurations for Segment Automation"

Storing Results

After completing work, store workflow/automation decisions for future sessions:

python3 execution/memory_manager.py store \
  --content "Workflow: automated data pipeline with retry logic, dead-letter queue, and Slack alerts on failure" \
  --type technical --project <project> \
  --tags segment-automation workflow

Multi-Agent Collaboration

Share workflow state with other agents so they can trigger, monitor, or extend the automation.

python3 execution/cross_agent_context.py store \
  --agent "<your-agent>" \
  --action "Workflow automation deployed — pipeline processing 1000+ events/day with 99.9% success rate" \
  --project <project>

Playbook Engine

Combine this skill with others using the Playbook Engine (execution/workflow_engine.py) for guided multi-step automation with progress tracking.