# Portable.io MCP > Portable.io MCP manages your entire data pipeline workflow directly through your AI agent. It lets you check complex integration flows, view execution history for specific sync runs, and monitor destination details across platforms like Snowflake or BigQuery—all without leaving your chat window. ## Overview - **Category:** developer-tools - **Price:** Free - **Tags:** etl, data-pipeline, saas-integration, data-sync, warehouse-management, data-engineering ## Description Need to know why the sales data didn't make it into BigQuery this morning? You don't have to open five different tabs to figure it out. This MCP connects your Portable.io account, letting you talk to your agent about complex ETL pipelines using natural language. Instead of digging through dashboards and API documentation, you ask questions like, 'What were the sync runs for HubSpot yesterday?' Your agent retrieves that history instantly, showing row counts and pinpointing failure logs so you know exactly what went wrong. You can also check account limits or list every data warehouse destination authorized to receive writes. It's a massive time saver. When working with thousands of available tools, Vinkius makes it simple to find the exact data pipeline control you need. ## Tools ### list_flows Retrieves a list of all integration flows set up in Portable. ### get_flow Fetches the complete configuration details for one specific data flow. ### list_runs Shows historical execution records and results for a particular data flow. ### list_connectors Lists all available pre-built API connectors used as data sources. ### list_destinations Retrieves a list of authorized data warehouses and targets for receiving raw data writes. ### get_account Provides the exact billing details, workspace bounds, and account status limits. ## Prompt Examples **Prompt:** ``` List all active ETL flows running in my Portable workspace. ``` **Response:** ``` I found 3 active flows. 'Stripe to Snowflake' runs every hour. 'Hubspot to BigQuery' runs daily. 'Shopify Orders' is paused. Would you like to view the recent execution runs for the Stripe sync? ``` **Prompt:** ``` Show the recent runs for flow ID 4087 and tell me if any failed. ``` **Response:** ``` For flow 4087, the last 4 runs were successful, processing exactly 12,045 rows. However, the run on Tuesday at 4 AM failed with 'API Rate Limit Exceeded' from the source connector. Should I pull the destination configuration details? ``` **Prompt:** ``` What destinations are currently configured to receive data? ``` **Response:** ``` You have 2 active destinations connected: 'Production Warehouse' (BigQuery) and 'Analytics Replica' (Snowflake). Connecting new flows will write directly into the authorized schemas on these platforms. ``` ## Capabilities ### Inventory all configured data flows List every integration flow currently set up within your Portable workspace. ### Inspect specific flow configurations Get the full setup and mapping details for one chosen data synchronization flow. ### Review historical run results Track execution history, checking successful row counts or identifying failure logs for a given flow. ### List connected data targets See all the data warehouses and SaaS extractors authorized to receive raw data from your flows. ### Check account usage limits Instantly retrieve your workspace boundaries and billing execution limits for peace of mind. ## Use Cases ### A critical data load failed overnight. An analytics manager notices missing sales records in Snowflake. They prompt their agent: 'Show me the recent runs for the Stripe sync flow and tell me if any failed.' The agent uses `list_runs`, immediately showing that the run from 3 AM failed due to an API rate limit, solving the mystery instantly. ### Setting up a brand new data source. A data engineer needs to integrate a niche SaaS tool. They use `list_connectors` to see if Portable has a pre-built connector for it. If not, they check the documentation and then confirm connectivity by running a small test flow. ### Troubleshooting destination writes. An ops manager is setting up a new replica database. They first use `list_destinations` to see which targets are already configured (like BigQuery and Snowflake). This confirms the correct write permissions before deploying any new data flows. ### Checking resource capacity. A team wants to run a massive, multi-day ETL job. Before committing resources, they use `get_account` to check their current billing status and ensure the workspace has enough allocated execution time for the entire project. ## Benefits - Stop context switching. Instead of opening a dozen tabs to check sync status, ask for the `list_runs` history directly. You get immediate failure logs and row counts without leaving your chat. - Verify system boundaries instantly. Use `get_account` to check if you're hitting execution limits or need more workspace capacity before launching a major migration. - Quickly audit data sources. If you aren't sure what APIs feed your pipelines, use `list_connectors`. You can quickly see every pre-built source available for mapping. - Know where the data lands. Before running a new flow, call `list_destinations` to confirm which specific Snowflake or BigQuery schemas are authorized to accept writes. - Deep dive into setups. Need to check if a specific sync is configured correctly? Use `get_flow` for full configuration details instead of guessing through the UI. ## How It Works The bottom line is that you get full control over complex data movement and syncing without ever leaving your chat interface. 1. Subscribe to this MCP and provide your Portable API key. 2. Your AI client authorizes access, connecting the agent to your data pipeline account. 3. You simply ask your agent a question—like 'Show me the run history for last week's Shopify sync'—and it delivers the answer. ## Frequently Asked Questions **How does Portable.io MCP check data flow status?** It checks by allowing your agent to use `list_runs` to retrieve historical execution records for a specific flow, showing if the last run succeeded and how many rows were processed. **Can I see what destinations Portable.io MCP writes data to?** Yes, you can call `list_destinations` to retrieve all configured data warehouses authorized to receive raw data from your active flows. **What is the purpose of list_connectors in Portable.io?** The `list_connectors` tool shows you every available, pre-built API source connector that can be used as a starting point for a data pipeline. **Does Portable.io MCP help with billing limits?** It does. You use the `get_account` tool to instantly retrieve your workspace bounds and current execution limits, ensuring you don't overspend or hit capacity ceilings. **How do I check all my data pipelines with Portable.io MCP?** You start by asking the agent to run `list_flows`, which retrieves a complete list of every integration flow configured in your account.