# Sensors Data MCP for AI Agents AI Agent Connect > Sensors Data MCP connects your AI agent to the Sensors Data big data analytics platform. Use it to query user behavioral sequences, analyze conversion funnels, and monitor data ingestion health in real-time. It turns complex data queries into natural language conversations for analysts and product managers who need to see what users are actually doing. ## Overview - **Category:** productivity - **Price:** Free - **Endpoint:** https://edge.vinkius.com/vk_preview_T2xX3WQBTquyNuo5UxCXOFQhIkDbbooC2Gc9ABSM/ai-agent-connect - **Tags:** sensors-data, big-data, user-behavior, event-tracking, data-ingestion, behavioral-analytics ## Description This Sensors Data MCP connects your AI agent to the Sensors Data big data analytics platform. You're often stuck jumping between different tabs to piece together a user's journey. You see a drop-off in a conversion funnel and have to dig through logs to figure out why. This changes that by giving your AI agent a direct line into your analytics. Instead of writing complex queries or manual exports, you can just ask your agent what's happening. It can pull up specific user profiles to see their recent activity, check if your data pipeline is actually healthy, or run a retention analysis on the fly. It's about getting the 'why' behind the numbers without the manual heavy lifting. Because Vinkius makes it so easy to manage your connections, you can keep your focus on making product decisions rather than wrestling with data access. You get a clear view of user behavior, real-time health checks, and project configurations right in your chat interface. Imagine being able to ask about a specific user's behavior sequence and getting a chronological list of every click they made. Or ask about a specific project's metadata to see how many events are being tracked without opening a browser. This setup removes the friction of data retrieval, allowing you to move from a question to an answer in seconds. You can see if your ingestion rates are steady, identify where users are getting stuck in your sign-up flow, and understand your high-value customers better than ever before. It turns your big data into a conversational resource. ## Tools ### list_events List all defined event names in your schema. This gives your agent a menu of what it can actually track. ### get_user_behavior_sequence Get the chronological order of events for any specific user. This helps you see the exact path a customer took. ### list_user_properties List all defined user profile properties. Use this to see what data you're collecting on your users. ### lookup_user Get the full profile information for a specific user ID. This is perfect for deep-diving into individual behaviors. ### query_behavior_list Retrieve a list of user behaviors and events. Use this to scan for general activity patterns. ### analyze_events Run complex analysis on your event data. This is useful for spotting trends across different user actions. ### analyze_funnel Calculate conversion metrics for your sales or sign-up flows. It shows you exactly where people are dropping off. ### analyze_retention Calculate how many users stay active over time. Use this to measure the long-term value of your product. ### get_event_schema Retrieve the property schema for a specific event. This helps your agent understand what data points are available. ### get_project_info Retrieve metadata for your Sensors Data projects. Use this to quickly check project names and settings. ## Prompt Examples **Prompt:** ``` Show me the top 5 events by volume in project 'MainApp' for today. ``` **Response:** ``` Retrieving event statistics for 'MainApp'... The top 5 events today are: 1. **page_view** (1.2M) 2. **item_click** (450K) 3. **user_login** (120K) 4. **add_to_cart** (85K) 5. **purchase_complete** (12K) Would you like to see the conversion rate between these? ``` **Prompt:** ``` Get the behavioral attributes for user ID 'user_sensors_777'. ``` **Response:** ``` Querying user profile... User **'user_sensors_777'** is categorized as a **'High-Value Customer'** with 15 purchases in the last 30 days. * **Preferred category:** Electronics * **Last active:** 10 minutes ago ``` **Prompt:** ``` Is the data ingestion pipeline healthy for project 'AnalyticsBeta'? ``` **Response:** ``` Checking pipeline health for 'AnalyticsBeta'... * **Current status:** Healthy * **Ingestion rate:** 15K events/sec * **Errors:** Zero reported errors in the last hour Connectivity to the Sensors Data cluster is stable. ``` ## Capabilities ### Get user behavior sequences See the exact order of events a user took to reach a specific action. ### Analyze conversion funnels Calculate how many users move from one step to the next in a specific flow. ### Check data ingestion health Monitor your data pipeline to ensure events are flowing correctly into the platform. ### Look up user profiles Pull specific attributes and behaviors for a single user ID to see their history. ### List project configurations View your project names and token settings quickly without opening the dashboard. ### Analyze retention rates Get a clear picture of how many users stay active over time across your product. ## Use Cases ### Identifying a drop-off in the sign-up flow A PM notices a drop-off and asks the agent to `analyze_funnel` for the 'Registration' project to see which step has the highest friction. ### Understanding high-value user behavior A growth engineer uses `lookup_user` to see what the top 1% of customers do differently compared to average users. ### Checking data pipeline reliability An engineer asks the agent to check the ingestion rate for 'AnalyticsBeta' to ensure no data is being lost during a peak period. ### Rapid behavior auditing An analyst uses `list_events` and `get_event_schema` to see what data points are available for a new feature before they start building dashboards. ## Benefits - Stop manual data exports by using `analyze_funnel` to see conversion drops instantly. - Get deeper insights into user journeys by pulling chronological sequences with `get_user_behavior_sequence`. - Keep your data pipeline running smoothly by monitoring ingestion health with `query_behavior_list`. - Understand your most loyal customers faster by pulling profiles with `lookup_user`. - Save time on setup by quickly viewing project metadata with `get_project_info`. - Make data-driven product decisions by running retention checks with `analyze_retention`. ## How It Works The bottom line is that the Sensors Data MCP provides a conversational interface for your big data analytics. 1. Subscribe to the Sensors Data MCP and grab your Project Name and API Key from your dashboard. 2. Plug your credentials and Base URL into your AI client. 3. Ask your agent to analyze a specific funnel or pull a user's behavior sequence. ## Frequently Asked Questions **What can the Sensors Data MCP do for my team?** It lets your AI agent directly query user behavior, analyze conversion funnels, and monitor your data health in one place. **Can I use the Sensors Data MCP to see why users are leaving?** Yes, you can ask your agent to analyze specific funnels to find out exactly where people are dropping off. **Does the Sensors Data MCP work with my current analytics?** It works specifically with the Sensors Data (神策数据) platform to pull your existing user profiles and events. **How does the Sensors Data MCP help with data quality?** You can ask your agent to check the ingestion rates and health of your data pipelines in real-time. **Can I get a history of what a specific user did?** Yes, you can ask the agent to pull the chronological behavior sequence for any specific user ID. **Is the Sensors Data MCP good for product managers?** It's perfect for PMs who need to see real-time feature adoption and retention without writing SQL. **How do I connect my Sensors Data account?** You'll need your Project Name and API Key from your Sensors Data dashboard to link it to your AI client. **Can I automatically retrieve the behavioral profile for a specific user ID?** Yes! Use the `get_user_profile` tool with the specific User ID. Your agent will return all recorded attributes and recent behavioral events associated with that user. **How do I monitor the data ingestion status via the AI agent?** Use the `get_ingestion_health` tool. The agent will retrieve real-time statistics on data volume, successful ingestions, and any flagged errors in your pipeline. **Can I list all events tracked in a specific project?** Yes! Use the `list_events` tool. Your agent will return a list of all event names and their associated metadata currently configured in your Sensors Data project.