UK Environment Agency MCP for AI. Get Real-Time Flood and Sensor Data
Gemini Works with every AI agent you already use
…and any MCP-compatible client
Connect to your AI in seconds.
UK Environment Agency MCP Server pulls real-time flood monitoring, sensor readings, and water levels directly from DEFRA's open data hub.
It gives your AI agent immediate access to critical hydrological network data, allowing you to query active flood warnings (`list_floods`), check specific station metrics (`get_station`), or read continuous sea/river height archives without manual authentication.
What your AI can do
Get flood
Retrieves specific, immediate information regarding a single flood warning location or area.
Get hydrology station
Fetches explicit technical parameters for tracking a specific hydrology trace or measurement line.
Get measure
Grabs targeted details about how specific environmental measurements are configured to be tracked by the EA.
Run list_floods to retrieve a full list of all currently active flood alerts in the UK region.
Use get_station or list_stations to pull deep information about specific monitoring points, including their location and parameters.
Execute list_station_readings to get the actual, time-stamped measurements (like water level or flow rate) for any given station.
Access hydrology metadata using get_hydrology_station or list_measures to understand what data points are being tracked across the entire system.
Ask an AI about this
Waiting for input…
9 Tools for UK Environmental Data Retrieval
Use these nine specialized tools to query every aspect of the UK's hydrology network, from active flood alerts to granular sensor readings.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using UK Environment Agency on VinkiusGet Flood
Retrieves specific, immediate information regarding a single flood warning location or area.
Get Hydrology Station
Fetches explicit technical parameters for tracking a specific hydrology trace or...
Get Measure
Grabs targeted details about how specific environmental measurements are configured...
Get Station
Retrieves comprehensive, detailed data points for one specific flood monitoring...
List Floods
Gathers and returns a complete list of all currently active flood warnings across...
List Hydrology Stations
Reads and returns a global list of available, saved hydrology measurement stations within the system.
List Measures
Returns a list of all types of available metrics or measurements that the Environment Agency tracks.
List Station Readings
Pulls the actual, latest sensor readings associated with an individual monitoring...
List Stations
Gathers and returns a list of all currently active physical flood-monitoring...
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
Claude AI
Open Claude Settings
Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.
Add Custom Connector
Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:
https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp
Replace [YOUR_TOKEN_HERE] with your token
from cloud.vinkius.com. For OAuth-protected servers, expand
Advanced settings to add credentials.
Start a conversation
Open a new chat. The UK Environment Agency integration is available immediately — no restart needed.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with UK Environment Agency, then connect any of our 5,100+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,100+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by UK Environment Agency. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
VINKIUS INFRASTRUCTURE
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on every call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This connection provides 9 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.
Getting current flood status shouldn't take half an hour and three different web tabs.
Today, checking a region for active alerts means bouncing between the DEFRA site, finding the correct map layer, then manually filtering by severity. You copy names, you cross-reference dates, and you spend time just confirming that 'active' means what everyone agrees it means.
With this MCP server, your agent does all of that in a single query. Running `list_floods` returns the status—the active warnings, their scope, and when they were issued—in structured data instantly. You get the answer, not five links to click.
The `list_station_readings` tool gives you raw sensor data, period.
Before, pulling a full report meant logging into station A's portal for its flow rate, then logging into station B’s portal for its water depth. You were constantly repeating login credentials and formatting the output manually.
Now, you just tell your agent to run `list_station_readings` across several IDs. It pulls the raw, time-stamped numbers from every source and gives them back in one clean data object. Simple.
What your AI can actually do with this
Yo, listen up. This MCP Server connects your AI client straight into DEFRA and the UK Environment Agency’s open data hub. You're getting immediate access to real-time hydrological network data—no manual authentication needed for the whole mess. It lets you manage complex water monitoring workflows with nothing but a few simple commands.
Checking Flood Status:
You need to know if there’s trouble? Run list_floods and you get a complete rundown of every active flood warning across the UK region. If you're looking for specifics—say, just one area—you use get_flood to retrieve immediate details about that single warning location or zone.
Monitoring Stations:
To see what’s physically monitoring the water, first run list_stations. This gives you a list of every active physical flood-monitoring station in the network. Once you've got an ID, you use get_station to pull deep data points about that specific monitoring point, including its exact location and parameters. If you only need the raw numbers right now, executing list_station_readings pulls the actual, time-stamped measurements—like water level or flow rate—for any station ID.
Diving into System Parameters:
Want to know what data is even being tracked? You start by running list_measures, which returns a list of every type of metric the Environment Agency tracks. If you need to understand how a specific environmental measurement works, you use get_measure to see exactly how that metric is configured for tracking.
For mapping out the whole system, run list_hydrology_stations to get a global roster of available saved hydrology measurement stations within the entire network. You can then drill down with get_hydrology_station to fetch explicit technical parameters for tracing any specific measurement line or hydrology trace.
The Bottom Line:
You're dealing with three core data sets here: 1) Alerts, which you nail down using the flood tools. 2) Physical Hardware, where list_stations, get_station, and list_station_readings give you everything from location to the last second reading. 3) The Data Schema Itself, which involves list_measures, list_hydrology_stations, and their corresponding 'get' functions, allowing your agent to understand the entire system’s structure.
This means you can get a full picture—from running list_floods for immediate alerts, checking station metadata with get_station, and pulling raw readings via list_station_readings all in one go. It's pure data access; it doesn't mess around with fluff.
019d7617-f204-722b-a095-93bf5cffdc70 
Here's how it actually works
The bottom line is: your AI client runs the environmental queries, bypassing the need to manually interact with complex external web forms.
Subscribe to this server on Vinkius. Open your AI client (Claude, Cursor, etc.).
Directly instruct your agent what data you need—for instance, 'List all flood warnings for the Thames Valley.'
The agent executes the appropriate tool (e.g., list_floods) and returns structured data containing real-time water levels or alerts.
Who is this actually for?
Environmental analysts who spend too long cross-referencing multiple public APIs are the primary users. If you're a logistics coordinator who needs immediate flood risk data for route planning, this is for you. It’s built for anyone whose job depends on accurate, real-time UK hydrological readings.
Needs to cross-check local river parameters instantly by comparing output from list_hydrology_stations against specific reading data using get_measure.
Requires monitoring active flood warnings (list_floods) to adjust delivery routes before dispatching teams, eliminating manual map checks.
Builds automated dashboard alerts directly into their IDE by scripting calls to list_stations and list_station_readings for continuous monitoring.
What Changes When You Connect
Stop sifting through web dashboards. Using list_floods instantly gives you a compiled list of every active flood warning, regardless of severity level.
Need to know what data is available? Running list_measures shows you all the specific metrics (like flow rate or water temperature) that the EA tracks—it saves time figuring out the right API call.
Instead of guessing a station ID, use list_stations to get a definitive list of active monitoring points. Then, pass those IDs to list_station_readings for the latest data batch.
The network parameters aren't clear? Use get_hydrology_station and get_measure together. This lets you understand exactly what physical river or sea segment is being monitored and how the measurements are calculated.
It works across all your preferred AI clients—Claude, Cursor, VS Code, etc.—meaning you get real-time sensor data right where you're coding or writing reports.
See it in action
Assessing immediate flood risk for a region.
A disaster response team needs to know if there are any critical alerts. They ask their agent: 'What floods are active?' The agent runs list_floods, returning all current warnings immediately, letting the team focus on rescue rather than data gathering.
Validating a new sensor location.
A developer needs to build an alert dashboard for a brand-new station. They run list_stations to get the available IDs, then use get_station on a specific ID to pull all metadata required for their validation script.
Comparing historical measurements.
An environmental analyst wants to see if recent river levels are anomalous. They run list_hydrology_stations, select the relevant trace, and use get_measure to pull the required parameters for comparison.
Generating a status report on multiple points.
The ops team needs to know the water levels at ten different spots. They run list_stations, iterate through the resulting IDs, and call list_station_readings for each one to build a single, comprehensive report.
The honest tradeoffs
Confusing station list with actual data.
Asking 'Show me the flood data at Station XYZ.' The agent might incorrectly run get_station, which only provides metadata, not the current water level reading.
To get the actual readings, you must use list_station_readings(station_id=XYZ). Use get_station only when you need technical details about the station itself.
Calling multiple listing tools redundantly.
Running both list_stations and list_floods when all you want is to know the current alerts. This wastes time and makes the agent run unnecessary queries.
If your goal is simply active warnings, stick to list_floods. If you need the list of all physical monitoring spots regardless of flood status, use list_stations.
Assuming a single tool covers all network info.
Asking 'What is happening in the hydrology network?' and expecting one function to provide everything. This will fail because data comes from multiple sources.
You need a sequence: First, use list_hydrology_stations to see what's available; then, use get_measure or get_hydrology_station to pull the specific technical details you want.
When It Fits, When It Doesn't
Use this server if your core task involves real-time UK hydrological data: monitoring flood warnings, tracking water levels from defined sensors, or reading official environmental metrics. If your question is 'What's the current river height at station 123?'—use list_station_readings. If you need to know which type of metric (like flow rate vs. depth) is available across the whole system—run list_measures. Don't use this server if your query relates to general environmental policy, historical non-hydrological data, or any location outside of the UK Environment Agency’s monitored zones.
Questions you might have
How do I get started? +
Subscribe to the server and you're ready. The UK Environment Agency API is entirely public open data. No code, no setup, no webhooks — just connect and start querying through your AI agent.
Can my AI agent check for active flood warnings in specific areas? +
Yes. Your agent queries the live flood alert endpoints, giving you precise warnings, severity levels, and regional bounds instantaneously. It handles the whole diagnostic flow directly from your prompt.
What happens when I need to check exact river depth history? +
Just tell your AI agent. It targets individual measurement stations and reads their active water flow and level records, saving you from navigating complex CSV government databases.
Can I monitor multiple geographic metrics simultaneously? +
Absolutely. Combine requests for hydrology network grids, list all active flood stations across county borders, and map their measures. Perfect for logistics teams, civic planners, and researchers parsing country-wide status loops.
When I call list_stations, do I need to worry about authentication? +
No, you don't need any credentials. The server connects directly to the open data hub, meaning your AI agent handles the connection without requiring API keys or complex setup.
If a sensor fails, how does list_station_readings show me the error? +
The response structure includes specific status codes and detailed JSON objects describing the failure. This lets your agent distinguish between missing data and an actual system error.
What is the best way to check for all available metrics using list_measures? +
The tool returns a comprehensive list of every measurable parameter (like flow rate or temperature). This structure includes standardized units, so you know exactly what your agent is interpreting.
Is there a limit when I query get_hydrology_station repeatedly? +
The service manages standard querying rates. For high-volume data pulls or continuous monitoring, schedule the queries in an autonomous pipeline rather than running them individually.
We've already built the connector for UK Environment Agency. Just plug in your AI agents and start using Vinkius.
No hosting. No infrastructure. No complex setup.
All 9 tools are live and waiting.
You're up and running in seconds.
Gemini Vinkius gives your AI agents access to the full catalog of app connectors, all fully managed, secure, and enterprise-ready. One subscription, every tool you need.
Built, hosted, and secured by Vinkius. You just connect and go.