Skip to main content
Glama

get_geomagnetic_storm

Retrieve geomagnetic storm data from NASA to monitor space weather conditions and assess potential impacts on Earth's magnetic field.

Instructions

Get geomagnetic storm (GST) data.

Args: start_date: Start date in YYYY-MM-DD format. Defaults to 30 days before current date. end_date: End date in YYYY-MM-DD format. Defaults to current date.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
start_dateNo
end_dateNo

Implementation Reference

  • The primary handler function for the 'get_geomagnetic_storm' tool. It is registered via the @mcp.tool() decorator. Fetches geomagnetic storm data from NASA's DONKI/GST API endpoint using the shared make_nasa_request helper, handles errors, and formats the response using the format_donki_results helper.
    async def get_geomagnetic_storm(start_date: str = None, end_date: str = None) -> str:
        """Get geomagnetic storm (GST) data.
        
        Args:
            start_date: Start date in YYYY-MM-DD format. Defaults to 30 days before current date.
            end_date: End date in YYYY-MM-DD format. Defaults to current date.
        """
        params = {}
        if start_date: params["startDate"] = start_date
        if end_date: params["endDate"] = end_date
        
        url = f"{NASA_API_BASE}/DONKI/GST"
        data = await make_nasa_request(url, params)
    
        if not data: 
            return "Could not retrieve GST data due to a connection error."
        
        # Check for error response (must be a dictionary)
        if isinstance(data, dict) and "error" in data:
            return f"API Error: {data.get('error')} - Details: {data.get('details', 'N/A')}"
        if isinstance(data, dict) and data.get("binary_content"):
            return f"Received unexpected binary content from GST API. URL: {data.get('url')}"
    
        try:
            # Ensure data is a list for format_donki_results
            if not isinstance(data, list):
                logger.error(f"Unexpected non-list response from GST API: {data}")
                return "Received unexpected data format from GST API."
                
            return format_donki_results(data, "Geomagnetic Storms", "gstID")
        except Exception as e:
            logger.error(f"Error processing GST data: {str(e)}")
            return f"Error processing geomagnetic storm data: {str(e)}"
  • Shared helper function used by multiple DONKI tools, including get_geomagnetic_storm, to format the list of events into a readable string summary, limiting display to 10 items.
    def format_donki_results(data: list, title_prefix: str, id_key: str) -> str:
        if not data: 
            return f"No {title_prefix.lower()} data for the specified period."
        
        result = [f"{title_prefix} found: {len(data)}"]
        display_limit = 10
        count = 0
    
        for item in data:
            if count >= display_limit:
                result.append(f"n... and {len(data) - display_limit} more entries.")
                break
            
            result.append(f"nID: {item.get(id_key, 'Unknown')}")
            # Add common fields if they exist
            if 'startTime' in item: result.append(f"Start Time: {item.get('startTime', 'Unknown')}")
            if 'eventTime' in item: result.append(f"Event Time: {item.get('eventTime', 'Unknown')}")
            if 'sourceLocation' in item: result.append(f"Source Location: {item.get('sourceLocation', 'Unknown')}")
            if 'note' in item: result.append(f"Note: {item.get('note', 'N/A')}")
            if 'link' in item: result.append(f"Link: {item.get('link', 'N/A')}")
            
            # Specific fields for different DONKI types can be added here if needed
            # Example for CME:
            if id_key == 'activityID' and 'cmeAnalyses' in item:
                analyses = item.get('cmeAnalyses', [])
                if analyses:
                    result.append("  Analyses:")
                    for analysis in analyses[:2]: # Limit analyses shown
                        result.append(f"    - Time: {analysis.get('time21_5', 'N/A')}, Speed: {analysis.get('speed', 'N/A')} km/s, Type: {analysis.get('type', 'N/A')}")
            
            # Example for GST:
            if id_key == 'gstID' and 'allKpIndex' in item:
                 kp_indices = item.get('allKpIndex', [])
                 if kp_indices:
                     result.append("  Kp Indices (first 2):")
                     for kp in kp_indices[:2]:
                         result.append(f"    - Time: {kp.get('observedTime', 'N/A')}, Index: {kp.get('kpIndex', 'N/A')}")
    
            # Linked Events
            linked_events = item.get('linkedEvents', [])
            if linked_events:
                result.append("  Related event IDs (first 5):")
                result.append("    " + ", ".join([le.get('activityID', 'N/A') for le in linked_events[:5]]))
    
            result.append("-" * 40)
            count += 1
            
        return "n".join(result)
  • Shared helper function used by all NASA API tools, including get_geomagnetic_storm, to make HTTP requests to NASA APIs, handle JSON/binary responses, errors, and include the API key.
    async def make_nasa_request(url: str, params: dict = None) -> Union[dict[str, Any], List[Any], None]:
        """Make a request to the NASA API with proper error handling.
        Handles both JSON and binary (image) responses.
        """
        
        logger.info(f"Making request to: {url} with params: {params}")
        
        if params is None:
            params = {}
        
        # Ensure API key is included in parameters
        if "api_key" not in params:
            params["api_key"] = API_KEY
        
        async with httpx.AsyncClient() as client:
            try:
                response = await client.get(url, params=params, timeout=30.0, follow_redirects=True)
                response.raise_for_status() # Raise an exception for bad status codes (4xx or 5xx)
    
                content_type = response.headers.get("Content-Type", "").lower()
                
                if "application/json" in content_type:
                    try:
                        return response.json()
                    except json.JSONDecodeError as json_err:
                        logger.error(f"JSON decode error for URL {response.url}: {json_err}")
                        logger.error(f"Response text: {response.text[:500]}") # Log beginning of text
                        return {"error": "Failed to decode JSON response", "details": str(json_err)}
                elif content_type.startswith("image/"):
                    logger.info(f"Received binary image content ({content_type}) from {response.url}")
                    # Return a dictionary indicating binary content was received
                    return {
                        "binary_content": True, 
                        "content_type": content_type,
                        "url": str(response.url) # Return the final URL after redirects
                    }
                else:
                    # Handle other unexpected content types
                    logger.warning(f"Unexpected content type '{content_type}' received from {response.url}")
                    return {"error": f"Unexpected content type: {content_type}", "content": response.text[:500]}
    
            except httpx.HTTPStatusError as http_err:
                logger.error(f"HTTP error occurred: {http_err} - {http_err.response.status_code} for URL {http_err.request.url}")
                try:
                    # Try to get more details from response body if possible
                    error_details = http_err.response.json()
                except Exception:
                    error_details = http_err.response.text[:500]
                return {"error": f"HTTP error: {http_err.response.status_code}", "details": error_details}
            except httpx.RequestError as req_err:
                logger.error(f"Request error occurred: {req_err} for URL {req_err.request.url}")
                return {"error": "Request failed", "details": str(req_err)}
            except Exception as e:
                logger.error(f"An unexpected error occurred: {str(e)}")
                return {"error": "An unexpected error occurred", "details": str(e)}
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes a read operation ('Get') and specifies date parameters with defaults, but doesn't cover critical aspects like data format, rate limits, authentication needs, error handling, or whether the tool is idempotent. For a data retrieval tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded. The first sentence states the core purpose, followed by a structured 'Args:' section that efficiently documents parameters without redundancy. Every sentence earns its place, and there's no wasted verbiage or unnecessary elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is partially complete. It excels in parameter documentation but lacks context on output format, data scope, or integration with sibling tools. Without annotations or output schema, the agent won't know what the returned data looks like or how to handle it, leaving gaps in overall usability.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds substantial meaning beyond the input schema, which has 0% description coverage. It explicitly documents both parameters ('start_date' and 'end_date'), their formats ('YYYY-MM-DD'), and default behaviors ('Defaults to 30 days before current date' and 'Defaults to current date'). This fully compensates for the schema's lack of descriptions, providing clear and complete parameter semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Get geomagnetic storm (GST) data.' It specifies the verb ('Get') and resource ('geomagnetic storm data'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_coronal_mass_ejection' or 'get_solar_flare', which likely retrieve related but distinct space weather data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools or contexts where geomagnetic storm data is preferred over other space weather data (e.g., solar flares or coronal mass ejections). The only implied usage is retrieving GST data within a date range, but no exclusions or prerequisites are stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/AnCode666/nasa-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server