Forecasts, climate history, severe alerts by location — for outdoor-event planners.
Get current weather and forecast for a location. Returns conditions, temperature, humidity, wind, and multi-day forecast.
Args: location: City name or coordinates (e.g. 'London, UK', 'New York, NY', '37.7749,-122.4194')
| Name | Required | Description | Default |
|---|---|---|---|
| location | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations include readOnlyHint=true, so the description does not need to re-state safety. It adds value by disclosing the return data (conditions, temperature, humidity, wind, forecast), which is especially important since there is no output schema. It does not mention potential limitations like units or availability, but the safety profile is already covered by annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: one sentence for the main purpose and a clear Args section with a single parameter. Every word is informative, no fluff or redundancy. The structure is front-loaded with the main action, making it easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema, no siblings), the description covers the essential aspects: what it does, what it returns, and how to specify the location. It does not mention unit systems or potential errors, but these are minor for a basic weather tool. The existing coverage is strong enough for an agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero description coverage (0%), so the description must fully explain the parameter. It does so effectively by providing the type (city name or coordinates) and concrete examples (e.g., 'London, UK', '37.7749,-122.4194'). This is exactly what the parameter needs for correct invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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 current weather and forecast for a location.' This is a specific verb+resource pair that accurately describes the functionality. It also lists the return fields (conditions, temperature, humidity, wind, multi-day forecast), further clarifying what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by stating it retrieves current weather and forecast, which is clear context. There are no sibling tools to differentiate from, so explicit alternatives are not applicable. However, it does not explicitly state when not to use the tool or mention any exclusions, so a score of 4 is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as io.github.alice/server, link the matching GitHub user or an account that owns the GitHub organization, then choose Claim with GitHub.
HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at /.well-known/glama.json on the same origin as the connector, then choose Check HTTP challenge.
DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
No comments yet. Be the first to start the discussion!
Weather data, forecast API, climate data, historical weather, alerts, agricultural & travel weather.
Historical weather and climate: 100+ years of station data, normals, extremes, and trends.
Smarter Weather MCP: forecasts, alerts, outlooks, observations, AQI, grids, and map imagery.
Get US weather forecasts, active alerts, and current observations.
Add one secure layer between your agents and this server.
Only one tool exists, so there is no possibility of confusing it with another. The tool's purpose is clearly described and distinct.
The single tool name 'get_weather' follows the conventional verb_noun pattern. With only one tool, consistency is trivially achieved, and the name is clear and descriptive.
A single tool feels thin for a weather server, but it covers both current conditions and forecast, so it is not a trivial tool. This is borderline in terms of count, but not extreme.
The tool covers the core weather use cases (current conditions and multi-day forecast). Minor gaps exist, such as lack of separate current/forecast endpoints or geocoding support, but these can be worked around since the tool accepts city names and coordinates directly.