PRO Annual — 50 users, $106.80/year
When Claude has the Adafruit IO MCP, it turns raw sensor readings into actionable project updates right inside GitScrum. You'll stop hopping between dashboards and start making decisions based on real-time data feeds.
Claude
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task.delegate()
You assign the task to Claude, asking it to pull status updates by listing all active Adafruit IO feeds and identifying which ones are failing or reporting anomalies.
Claude autonomously invokes the `list_feeds` and `get_data` tools, gathering structured data points from your entire IoT infrastructure via the MCP standard.
The result is a clean, summarized report directly appended to the ticket, listing which sensors are green and which require immediate attention for the next sprint cycle.
task.create()
Copy. Paste into a Claude-aware GitScrum task. Done.
I need a status report on all hardware deployed in the field to determine if we can close out testing phase 3.
Claude, please use the Adafruit IO MCP. First, list all available feeds. Then, pull the latest data point for each feed and generate a concise summary of overall system health status that I can copy into our sprint review ticket.
The client thinks our monitoring dashboards aren't showing the right data for their next meeting, and I need to prove which groups are missing feeds.
Using the Adafruit IO MCP, run a check: list all available groups, then specifically get details on any dashboard related to 'Project Alpha'. Summarize what is visible versus what we expected to monitor in that group.
A developer reports intermittent failures, and I need historical data on a specific sensor reading over the last hour.
Claude, use the Adafruit IO MCP to retrieve all recorded data points for the 'temperature' feed within the 'HVAC Group'. Format this into a simple time series table that highlights any sudden drops or spikes. This is for a critical bug ticket.
If your project involves monitoring anything physical, you know the pain. You spend hours jumping between Adafruit IO dashboards, digging through raw data feeds, and manually cross-referencing status changes across multiple spreadsheets just to write one coherent sprint update.
The new workflow lets Claude read that complex sensor environment via this MCP. Instead of manual copy-pasting or dashboard hopping, Claude reads the source data, analyzes it against your project goal, and writes a clean, summarized report directly into GitScrum.
Open this workflow in GitScrum →Manual triage means checking if the data supports the ticket's claim. Are the error logs actually spiking? Is the sensor reading confirming the failure mode described in the backlog item? It’s time-consuming, guess-work prone work.
Now, Claude can connect Adafruit IO to GitScrum. You simply ask it to compare the current data feeds against a specific bug report's criteria. The system gives you an immediate 'Go/No-Go' status based on real metrics.
claude.ask()
Claude, I'm reviewing our hardware monitoring tasks in GitScrum. Can you use the Adafruit IO MCP to list all active triggers and tell me which ones are currently armed? Keep the output bulleted.
Using the Adafruit IO MCP, fetch data for a specific group of sensors related to battery life. Then, advise Claude on the top three potential failure points based solely on the current readings.
I've linked my Adafruit IO account via the MCP. Please list all available dashboards and organize them by function (e.g., power, temperature, flow).
Claude, I need to verify if we have data for a specific feed name across multiple groups. Use the `get_feed` tool and report back any discrepancies you find.
tools.list()
Each tool is one operation Claude runs on your behalf.
| tool_name | operation |
|---|---|
| get_dashboard | Claude can use the Adafruit IO MCP to retrieve details and metadata for a specified dashboard, helping an AI agent understand overall project monitoring views. |
| get_data | This function allows Claude to fetch the most recent specific data point from any given feed, which is critical for generating current status reports in GitScrum. |
| get_feed | Claude uses this tool to gather detailed information about a particular sensor feed. An AI agent can check if a required monitoring source is available for a ticket. |
| get_group | This MCP function lets Claude retrieve details on an entire group of related feeds, useful when reviewing system health or grouping related hardware components in GitScrum. |
| get_trigger | This MCP function lets Claude retrieve details and metadata for a specified dashboard, helping an AI agent understand overall project monitoring views. |
| list_dashboards | An AI agent can call this function, allowing Claude to list every available dashboard name within your Adafruit IO account so you know where to look for project status. |
| list_data | Claude runs this tool to generate a comprehensive list of recorded data points for a specific feed. This is the core function for generating historical trend analysis in GitScrum. |
| list_feeds | This MCP allows Claude to programmatically list every single sensor feed available on your Adafruit IO account, giving you a complete inventory for auditing project scope. |
| list_groups | Claude uses this tool to get a full listing of all existing data groups. This helps an AI agent structure status reports by physical location or functional subsystem. |
| list_triggers | List all triggers |
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