NASA DONKI MCP. Track solar activity across multiple physics domains.
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NASA DONKI — Space Weather Intelligence delivers real-time data on critical space phenomena. This MCP Server provides seven specialized tools: check for Coronal Mass Ejections (CMEs), analyze solar flare classes (X, M, C), monitor geomagnetic storms and Kp indices, track interplanetary shocks, map radiation belt enhancements, identify Solar Energetic Particles (SEPs), and get a unified feed of all DONKI notifications.
It's the deep-dive data source for mission planning.
What your AI agents can do
Get cme
Retrieves Coronal Mass Ejection events. This data shows massive solar wind bursts that can trigger major geomagnetic storms, defaulting to the last 30 days.
Get donki notifications
Pulls a unified feed of all recent space weather alerts, combining information on CMEs, flares, shocks, and radiation events for a quick status check.
Get geomagnetic storms
Gets geomagnetic storm data, including the critical Kp index. This is essential for understanding impacts to GPS and power grids.
You get historical and near-real-time data on CMEs, showing their potential impact on Earth's magnetic field.
This tool pulls a unified feed of all DONKI events—flares, shocks, storms, etc.—for a rapid overview of recent solar activity.
You access data including the Kp index to measure the severity of geomagnetic disturbances, affecting everything from GPS to power grids.
This provides records of shock waves that propagate through the solar wind, often signaling an incoming major event.
You retrieve data on enhancements to the Van Allen radiation belts, crucial for planning satellite missions in MEO.
This tool provides information about dangerous SEPs, which can damage sensitive electronics and pose risks to crewed missions.
You get detailed records of solar flares by class (C, M, X), including their peak times and active region identifiers.
Ask AI about this MCP
Supported MCP Clients
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NASA DONKI — Space Weather Intelligence: 7 Tools
Monitor the full spectrum of space activity—from solar flares to radiation belts—by accessing seven specialized NASA tools via your AI client.
019d75dbget cme
Retrieves Coronal Mass Ejection events. This data shows massive solar wind bursts that can trigger major geomagnetic storms, defaulting to the last 30 days.
019d75dbget donki notifications
Pulls a unified feed of all recent space weather alerts, combining information on CMEs, flares, shocks, and radiation events for a quick status check.
019d75dbget geomagnetic storms
Gets geomagnetic storm data, including the critical Kp index. This is essential for understanding impacts to GPS and power grids.
019d75dbget interplanetary shocks
Retrieves records of shock waves in the solar wind. These shocks frequently precede major geomagnetic storms, giving advance warning.
019d75dbget radiation belt
Checks for enhancements to the Van Allen radiation belts, which is vital when planning satellite passes through Medium Earth Orbit (MEO).
019d75dbget solar energetic particles
Provides details on Solar Energetic Particle events. These particles are hazardous to electronics and human life in space.
019d75dbget solar flares
Retrieves solar flare data, categorized by class (C, M, X). The X-class flares are the most severe and can cause radio blackouts.
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What you can do with this MCP connector
NASA DONKI: Space Weather Intelligence.
This MCP Server gives your AI client deep-dive data on solar and space physics events. It’s built around seven specialized tools that track everything from massive coronal mass ejections to subtle radiation enhancements. You're looking at the full spectrum of threats, so you don't gotta juggle a bunch of different feeds.
Monitoring Large Solar Eruptions:
The get_solar_flares tool lets you query detailed records of solar flares by class: C, M, and X. Remember, an X-class flare is the big one; it's the most severe kind and can cause radio blackouts that mess up comms across huge areas. The data gives you peak times and active region identifiers so you know exactly what to look out for when planning ground operations.
You also get a read on get_cme, which retrieves Coronal Mass Ejection events. These aren't just little puffs; they're massive solar wind bursts that can trigger serious geomagnetic storms, and the tool defaults to showing you everything from the last 30 days so you’ve got historical context.
Tracking Storm Dynamics and Warnings:
The get_interplanetary_shocks function pulls records of shock waves moving through the solar wind. These shocks are often what signal a major event is coming, giving you advance notice that something big's brewing out there. When you run get_geomagnetic_storms, you get data that includes the critical Kp index. This metric tells you how bad the geomagnetic disturbance is—it’s essential for understanding potential impacts on everything from GPS signals to local power grids.
For a quick status check, use get_donki_notifications; this single feed pulls together alerts on flares, shocks, storms, and CMEs, giving your agent an immediate overview of recent solar activity.
Assessing Particle Hazards:
Space isn't just about magnetic fields; it’s also about dangerous particles. get_solar_energetic_particles provides details on SEPs. These are high-energy particles that can seriously damage sensitive electronics and pose real risks to people in crewed missions. You also need to keep an eye on the Van Allen radiation belts using get_radiation_belt.
This tool checks for enhancements to these belts, which is absolutely vital when you're planning a satellite pass through Medium Earth Orbit (MEO) because it tells you exactly where you might run into dangerous levels of radiation. These seven tools cover every angle so you can plan your mission knowing what the space environment’s gonna throw at you.
How NASA DONKI MCP Works
- 1 Tell your agent what specific event you need to track (e.g., 'latest CMEs' or 'X-class solar flares').
- 2 The agent calls the appropriate tool (like
get_cmeorget_solar_flares) and receives structured, historical data from NASA DONKI. - 3 Your AI client processes this raw space physics data into a clear report detailing severity, timing, and potential impact.
The bottom line is that you get actionable, scientifically vetted solar activity reports without needing to visit multiple NASA websites or parse disparate datasets.
Who Is NASA DONKI MCP For?
This server is built for mission control specialists and aerospace engineers. It's for the ops engineer who needs continuous monitoring of orbital assets and power grid stability—not just a nice dashboard, but structured data that drives immediate decisions.
Runs checks on get_radiation_belt and get_interplanetary_shocks to determine if current orbital paths risk radiation damage or unexpected atmospheric drag.
Uses get_solar_flares and get_cme to correlate historical flare data with specific solar active regions for research papers.
Monitors get_geomagnetic_storms readings (especially Kp index) to preemptively flag potential grid instability or communication blackouts.
What Changes When You Connect
- Immediate risk assessment: Don't wait for dashboards. By calling
get_geomagnetic_storms, you get the current Kp index, giving an immediate measure of how hard Earth's magnetosphere is being hit, which is better than waiting for a manual report. - Deep event correlation: Instead of just getting a list of flares, your agent can link data. It can check
get_solar_flaresand then use that time stamp to callget_cme, showing if the flare was caused by a CME—that’s key context. - Unified monitoring: Forget checking seven separate NASA sites. The
get_donki_notificationstool aggregates CMEs, flares, shocks, and storms into one stream. It's a single call for total situational awareness. - Mission planning certainty: Planning an orbital pass? You run
get_radiation_beltalongside the mission trajectory data to predict if you’ll cross through high-risk radiation zones before committing to launch windows. - Preemptive warning system: Interplanetary shocks often signal major upcoming events. Running
get_interplanetary_shocksgives your team a lead time, allowing them to put assets into safe mode hours before the main storm hits.
Real-World Use Cases
Responding to an X-class flare.
A major solar flare is reported. Instead of manually searching multiple databases, your agent runs get_solar_flares (to confirm the class and time) and then immediately calls get_interplanetary_shocks. This tells you if the flare was accompanied by a shock wave, which dictates whether high-frequency radio blackouts are imminent.
Scheduling an international satellite pass.
An engineer needs to route a satellite through MEO. They first call get_radiation_belt for the current date/time. If the output shows high enhancement, they know to reschedule or activate shielding protocols before launching.
Analyzing historical grid failures.
A reliability analyst needs to understand a blackout from five years ago. They use get_geomagnetic_storms for that date range to see the Kp index. This data helps them correlate past storm severity with modern grid vulnerability, making their report scientifically sound.
Investigating an unexpected particle spike.
A remote asset reports unusual sensor readings. Your agent runs get_solar_energetic_particles to check for recent SEP events. This quickly determines if the anomaly is due to a known space weather threat, allowing the team to rule out solar causes immediately.
The Tradeoffs
Checking data sequentially.
A developer runs get_cme, then waits for it to finish before running get_solar_flares. They treat the tools like separate, unrelated API calls.
→
Don't call them one after another. Use your agent to run related tools together—for example, calling both get_cme and get_geomagnetic_storms simultaneously. This allows you to correlate a CME event with its resulting storm index in one pass.
Ignoring the unified feed.
The team relies only on checking flares (get_solar_flares) because it's easy to query, missing other concurrent threats like radiation boosts or shocks.
→
Always start with get_donki_notifications. This single call acts as a comprehensive checklist, ensuring you don't miss smaller but equally critical events happening simultaneously.
Assuming all data is current.
Treating historical data from get_cme (which defaults to 30 days) as if it were a real-time forecast, leading to mismanaged operational readiness.
→ Always check the timestamps and explicit limitations of each tool. If you need a prediction beyond the last 30 days, recognize that this data is observational history, not prophecy.
When It Fits, When It Doesn't
Use this MCP Server if your work requires understanding the relationship between different space weather phenomena. You need to know: 'Did the CME cause the shock wave, and did the resulting storm affect the radiation belts?' This tool is for systems engineering and mission planning that relies on correlated, high-stakes data.
Don't use it if your goal is simply general knowledge about solar physics; in those cases, academic journals or Wikipedia suffice. Also, don't rely solely on any single tool—for example, relying only on get_solar_flares without checking the Kp index via get_geomagnetic_storms leaves you blind to potential grid impacts. When making a decision, always check for the whole picture by running multiple tools in sequence.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by NASA. 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.
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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 server provides 7 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Figuring out space weather used to be an exercise in cross-referencing ten different dashboards.
Remember manually checking NOAA's site, then jumping to a solar flare catalog, and finally running separate queries just to check the current Kp index? You spend hours copy-pasting data points—a CME event here, an X-class flare there. It’s slow, siloed, and prone to human error.
With this MCP Server, you ask your agent one question: 'What is the current threat level?' The system executes multiple tools—`get_cme`, `get_solar_flares`, `get_geomagnetic_storms`—and returns a single, structured data object. You get an immediate risk assessment.
The NASA DONKI — Space Weather Intelligence MCP Server delivers full situational awareness.
Previously, getting a complete picture meant manually piecing together the blast radius from a CME (using `get_cme`), correlating it with the resulting shock wave (`get_interplanetary_shocks`), and then checking its maximum impact severity using `get_geomagnetic_storms`. It was a multi-day process.
Now, you trigger one prompt. The system runs all necessary checks in parallel. You instantly know the event's origin, its path, and its predicted severity level—all from your chat interface.
Common Questions About NASA DONKI MCP
How do I check if a solar flare caused a geomagnetic storm using get_solar_flares and get_geomagnetic_storms? +
You need to correlate the timelines. First, use get_solar_flares to identify the peak time of an X-class event. Then, run get_geomagnetic_storms for that same period. A strong overlap suggests the flare triggered the storm.
Is get_donki_notifications better than checking all the other tools individually? +
Yes, it's faster. get_donki_notifications acts as a unified summary feed of activity across CMEs, flares, shocks, and storms in one call. It gives you a high-level overview without needing to run seven separate queries.
What is the difference between get_cme and get_interplanetary_shocks? +
CMEs are the massive bursts of solar wind that cause the disturbance. Interplanetary shocks are the resultant wave front, propagating through the solar wind and often arriving at Earth first.
Can I use get_radiation_belt to plan a satellite orbit? +
Absolutely. Running get_radiation_belt helps you map out areas of enhanced radiation in Medium Earth Orbit (MEO). This is critical for adjusting orbital paths or planning safe operational windows.
How can I get detailed timing information using `get_solar_flares`? +
The tool provides full event timelines, not just a class rating. You get the begin time, peak time, and end time for each flare event. This data is crucial for planning communication blackouts or satellite passes.
What specific risks does `get_solar_energetic_particles` track? +
It tracks Solar Energetic Particles (SEPs), which pose direct hazards to astronauts and sensitive electronic equipment. Seeing an SEP event means you need to evaluate potential damage risk for orbital assets.
If I see data from `get_interplanetary_shocks`, what should I expect regarding geomagnetic activity? +
Interplanetary shocks often precede major magnetic disturbances. Think of them as a precursor; the shock wave itself indicates that significant geomagnetic storm activity is likely approaching.
Does `get_donki_notifications` cover all seven event types, or just the big ones? +
It provides a unified feed covering every listed event type: CMEs, flares, storms, shocks, SEPs, radiation belt events, and all general notifications. It's built for a complete situational overview.
What is the difference between DONKI and SWPC? +
DONKI is NASA's historical database of space weather events with detailed analysis. SWPC (Space Weather Prediction Center, under NOAA) focuses on real-time monitoring and forecasting. They complement each other.
What happens during a Geomagnetic Storm? +
Geomagnetic storms, triggered by solar activity, can cause auroras, disrupt satellite communications, affect GPS accuracy, and in extreme cases, induce currents that trip electrical grids.
How long does it take for a CME to reach Earth? +
Coronal Mass Ejections typically take 1 to 5 days to reach Earth, depending on their speed, which can range from 250 km/s to over 3,000 km/s.
Use it with your favorite AI tools
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