# Segment MCP > Segment MCP gives your AI agent read access to your entire customer data infrastructure. Audit every source, destination, and tracking plan conversationally. You can map out complex pipelines, verify event schemas for development, and list connected data warehouses—all without leaving the chat window. ## Overview - **Category:** growth-engine - **Price:** Free - **Tags:** customer-data-platform, data-pipelines, event-tracking, data-governance, schema-management, data-warehousing, api-integration, analytics ## Description Connecting your Segment CDP through this MCP lets your AI agent talk directly to your customer data pipeline. Forget clicking through slow admin dashboards just to check if a source is routing correctly or what schema an event needs. Now you can simply ask your agent to audit your entire setup, and it pulls the details in real time. Need to write new tracking code? Tell the agent to pull the specific event tracking plan for 'Checkout Started'. It hands back the required properties, so you know exactly what data structure your frontend needs. If a developer asks where all their data lands, the agent lists every active data warehouse hooked into the workspace. This means you can map pipelines and verify complex routing schemas instantly. Vinkius helps consolidate these critical operations, allowing your agent to act as your single source of truth for data governance. It’s about getting verifiable answers on connections, event structures, and sources without ever touching a dashboard. ## Tools ### get_source Retrieves detailed information for a specific data source in your workspace. ### get_tracking_plan Pulls the full structure and rules for a particular event tracking plan. ### get_workspace Retrieves general information about your current Segment workspace setup. ### list_destinations Lists all the configured destinations that receive data from a specified source. ### list_sources Provides a list of every active data source available in your Segment workspace. ### list_tracking_plans Generates a list of all existing event tracking plans within the workspace. ### list_warehouses Lists every data warehouse connected and authorized to receive data from your setup. ## Prompt Examples **Prompt:** ``` List all active Workspaces configured in the environment. ``` **Response:** ``` I've queried the workspace configurations. Your primary environment is currently named 'Global Operations (vinkius_corp)' containing 12 active sources and maintaining a stable 30-day API limit threshold. ``` **Prompt:** ``` Lookup the Tracking Plan mapped to ID 'tp_123' to see the exact structure required for the Checkout Started event. ``` **Response:** ``` The Tracking Plan requires the 'Checkout Started' event to pass an array of product mappings. Essential properties include: `cart_id` (string), `total_value` (float), and `currency` (string, ISO 4217). Knowing this, I can draft the necessary React context hook for you. ``` **Prompt:** ``` Identify all data Warehouses we have feeding from this Segment workspace. ``` **Response:** ``` I've located 2 active warehouses attached to this workspace. First is a Snowflake cluster stationed securely behind VPC ('snowflake_eu_prod'). Second is an Amazon Redshift instance ('redshift_analytic_db'). Both register with healthy ping statuses according to Segment. ``` ## Capabilities ### List all connected data origins The agent retrieves comprehensive lists of every active data source (like Web or iOS) running in your workspace. ### Detail specific data sources You can get deep information about a single source to understand its capabilities and configuration. ### Map destination connections The agent lists all the destinations that receive data from a specified source, helping you track pipelines. ### Audit event tracking schemas You can pull precise details on any specific 'Tracking Plan' to verify payload structures needed for events. ### List all data warehouses The agent lists every authorized data warehouse connected to the workspace, confirming downstream compliance. ### Get workspace information You can retrieve general metadata about your entire Segment workspace environment. ## Use Cases ### Verifying a new payment flow's event structure A developer needs to ensure the 'Purchase Completed' event captures all necessary financial data points. They ask their agent, which uses `get_tracking_plan`, and immediately receive confirmation that essential properties like currency and total value are required. ### Checking for orphaned data pipelines A RevOps team member suspects a key SaaS app source isn't connected to its primary analytics destination. They ask the agent, which runs `list_destinations`, and see exactly which tools are missing or left behind. ### Auditing data compliance for a merger An analytics team member needs proof of every connected data reservoir before an audit. They run the agent to list all warehouses, confirming connections to both Snowflake and Redshift. ### Diagnosing a missing data source connection A growth marketer notices some web traffic data is missing from the warehouse. They ask the agent to list sources and check `get_source` details, identifying an inactive or misconfigured data origin. ## Benefits - You get instant visibility into data flow. Instead of navigating multiple tabs to see what sources connect where, you just ask the agent to list destinations for a given source. - Schema validation is immediate. Need to write code for 'Checkout Started'? Using `get_tracking_plan` gives you the exact properties needed—like `cart_id` and `total_value`—without consulting API docs first. - Audit your entire data stack at once. The agent can list all data warehouses, confirming that every critical source is properly feeding into its intended destination. - Data governance queries are fast. You query unique namespace IDs directly using the Public API, skipping slow navigation through dashboard settings entirely. - Source management is straightforward. Use `list_sources` and `get_source` to quickly audit all active data origins and understand their configuration details. - The whole process happens inside your chat interface, letting you verify complex tracking schemas without leaving your development workflow. ## How It Works The bottom line is you get instant, conversational visibility into your entire customer data flow without needing to navigate through slow dashboard interfaces. 1. First, subscribe to the integration and provide a 'Public API Token' from your Segment admin panel. 2. Next, start commanding your agent using your preferred MCP terminal or AI client. 3. The agent executes the query against your live data infrastructure and returns the raw details in conversation. ## Frequently Asked Questions **How does Segment MCP help with data governance?** It gives you programmatic access to audit unique namespace IDs and list all connected data warehouses. This confirms your entire data routing ecosystem is compliant without manual dashboard checks. **Can I use Segment MCP to see which sources exist?** Yes, running the `list_sources` tool gives you a comprehensive roster of every active source in your workspace. You can then use `get_source` for details on any one. **Is Segment MCP only for data engineers?** No. RevOps and Analytics teams use it too. Growth managers, for example, use it to ensure all destination connections are active after a platform update. **What if I want to check a specific event schema? Do I need the full plan?** You can use `list_tracking_plans` to find the right plan ID, and then `get_tracking_plan` with that ID. This gives you the exact payload structure you need. **Does Segment MCP support multiple environments?** The agent retrieves information about the current workspace (`get_workspace`), allowing you to confirm which environment you are auditing before running any data mapping tools.