Globalpulse-MCP

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool targets a distinct domain (World Bank, weather, disasters, aviation, trade, countries) with clear, non-overlapping purposes. Even related tools (e.g., forecast vs. historical, active vs. by country) have distinct roles.
Naming Consistency5/5
All tools follow a consistent pattern: globalpulse_<domain>_<action> in snake_case. Verbs are primarily 'get' with qualifiers, e.g., 'get_live_flights', 'get_by_country', making the naming predictable and easy to navigate.
Tool Count5/5
With 11 tools covering six diverse domains, the count is well-scoped for a general-purpose global data server. Each tool provides necessary functionality without redundancy, and the number is comfortable for both selection and maintenance.
Completeness4/5
The tool surface covers major areas (indicators, weather, disasters, aviation, trade, country info) with essential operations. Minor gaps exist, e.g., no tool to list trade commodity codes or search indicators beyond a predefined list, but these do not critically hinder typical workflows.
Average 3.8/5 across 11 of 11 tools scored. Lowest: 2.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds no additional behavioral context such as data freshness, pagination behavior, or rate limits. It merely restates the basic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short and front-loaded with the core purpose. However, the 'Args' line is somewhat redundant given the schema and misses opportunities to provide helpful context. Still, it avoids unnecessary verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 4 parameters and no output schema, much is left unsaid. No description of return format, pagination, sorting, or how to interpret the data. Lacks comparison to similar tools like globalpulse_disasters_get_active, leaving the agent underinformed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description should compensate but only lists parameter names and gives an example for country. Enum values (e.g., EQ, TC) are unexplained, and defaults or constraints are not described. Minimal value added over the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves disaster history for a specific country from UN GDACS. This verb-resource combination is specific and distinguishes it from sibling tools like globalpulse_disasters_get_active, which returns active disasters.
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?
No guidance on when to use this tool versus alternatives. It does not mention the sibling tool for active disasters or provide context for when history vs. active data is appropriate. Only a list of arguments is given without any 'when to use' information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds little beyond the annotations which already indicate read-only and open-world. It mentions 'live' and 'airborne', but does not disclose data freshness, rate limits, or other behaviors. The bar is low due to annotations, but the description provides minimal added context.
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 extremely concise with one sentence stating the purpose followed by a parameter list. No unnecessary words, and the purpose is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 parameters with no schema descriptions, no output schema, and several siblings, the description does not cover return values, pagination, or how to interpret results. Significant gaps remain despite the concise format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists parameters and gives an example for 'country', but does not explain 'limit' or 'response_format' beyond their names. The schema already provides constraints, so the description adds moderate value.
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 returns 'All live airborne flights from a specific country', which is a specific verb+resource. However, it does not distinguish from the sibling 'globalpulse_aviation_get_live_flights', which likely returns all flights without country filter.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you need flights filtered by country, but it does not explicitly mention when not to use it or suggest alternatives like the unfiltered sibling tool. Context is clear but lacks exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate read-only and non-destructive behavior. The description adds that tracking is real-time and covers position, altitude, speed, and heading, and mentions optional filters like on_ground_only and response_format. No contradictions, but could mention data source limitations (ADS-B coverage).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with a clear purpose sentence followed by argument list and practical examples. The examples add useful context but slightly increase length; overall well-structured.
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?
With 7 parameters and no output schema, the description provides usage examples but does not describe the return format or fields beyond listing altitude, speed, etc. It lacks details on pagination or data completeness, leaving the agent partially uninformed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage. The description lists parameter names and provides example bounding box values, which adds some meaning but does not explain each parameter's specific purpose or constraints (e.g., limit maximum, on_ground_only effect).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool provides live ADS-B flight tracking for a geographic bounding box, with specific data fields. It distinguishes itself from the sibling tool 'get_flights_by_country' which focuses on country-level filtering.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes example bounding boxes for India and Europe, implying usage for regional tracking. However, it does not explicitly state when to prefer this tool over alternatives like 'get_flights_by_country' or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the tool as readOnlyHint, idempotentHint, openWorldHint, and non-destructive. The description adds context about the data returned (population, area, capital, currencies) and mentions subregions, but does not detail behavior like pagination or output limits. It does not contradict annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: two sentences and a list of arguments. It front-loads the purpose and key details. However, the second sentence is a bit cluttered with 'Args:' and enums, and could be more structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (4 parameters, no output schema) and rich annotations, the description provides a coherent overview: it states what the tool does, what fields are returned, and lists main arguments. It is missing explicit detail on limit and response_format behavior, but overall it is informative enough for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must compensate, but it only lists parameter names and enums without explaining semantics. For example, 'limit' and 'response_format' are not described beyond their possible values. The agent gains little additional meaning beyond the schema's defaults and enum constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List all countries') and the resource ('in a region'), and provides specific details like the fields returned (population, area, capital, currencies) and example regions. It distinguishes itself from sibling tools like globalpulse_countries_get_profile, which focuses on a single country.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description lists valid regions and subregions, and enumerates arguments, but does not explicitly compare this tool to siblings or state when to use it versus alternatives. The context implies it's for listing countries by region, but lacks explicit when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint, idempotentHint, openWorldHint. Description adds 'No API key' and data source (ERA5), which are useful but not comprehensive. No mention of rate limits, response size, or behavior on invalid coordinates.
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?
Description is two sentences plus an args list, no redundancy. Purpose is front-loaded, and each sentence adds value. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With six parameters and no output schema, description lacks details on what climate variables are returned, data units, or response structure. It fails to fully prepare the agent for interpreting the output, especially given the complexity of historical climate data.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so description must compensate. Description lists all six parameters and gives date format hint (YYYY-MM-DD), but does not explain latitude/longitude bounds, timezone effect, or response_format options beyond naming them.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it provides historical daily climate data back to 1940 using ERA5 reanalysis, and explicitly says no API key. The verb 'get' is implied but the title and description distinguish from sibling 'get_forecast' by specifying historical range.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Description implies use for historical data via 'Historical' and 'back to 1940', but does not explicitly exclude the forecast sibling tool. It lists required arguments, providing clear context for invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already show readOnlyHint, openWorldHint. Description adds context on alert levels but doesn't disclose any behavioral traits beyond what annotations provide.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Concisely covers tool purpose, supported event types, alert levels, and parameters in a few sentences. Could be more structured but no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequately explains the tool's purpose and parameters. Without an output schema, describing the return format would improve completeness, but current description is sufficient for understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 0% schema description coverage, the description lists all parameters with allowed enum values, adding meaning beyond the schema alone. However, 'limit' and 'response_format' are only named without details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it provides live disaster alerts from the UN GDACS system, listing disaster types and alert levels. Distinguishes from sibling 'globalpulse_disasters_get_by_country' by focusing on global active alerts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implied use for accessing global active alerts, but no explicit guidance on when to use this tool over siblings like the country-specific one.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the description's burden is lower. It adds that the data comes from UN Comtrade and involves HS codes, but no additional behavioral details (e.g., rate limits, pagination, data freshness) are provided.
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 two sentences plus a compact argument list, front-loading the core purpose and examples. No wasted words; every element serves a purpose.
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?
The description covers parameters well but lacks details on the response format beyond the 'response_format' parameter. Without an output schema, more context on the returned data structure (e.g., columns, pagination) would be beneficial for a data retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists all seven arguments with defaults and valid ranges (e.g., year 2000-2023, flow enums, common HS codes). Missing explanation of what 'reporter' and 'partner' accept (e.g., country names vs. codes), but the provided info is largely sufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it returns bilateral trade data from UN Comtrade, with imports/exports by country pair and HS commodity code. The title and first sentence make the purpose unmistakable, and no sibling tools overlap in functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Description provides useful examples of common HS codes but does not explicitly state when to use or avoid this tool versus alternatives. There are no sibling trade tools, so implied usage is clear, but the lack of explicit guidance on prerequisites or contexts limits the score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint as false, so the description needs only to add context. It adds value by detailing data scope (10,000+ indicators, 1960–present) and examples, without contradicting annotations. No mention of rate limits or pagination, but acceptable for a read-only tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is moderately sized with a front-loaded purpose statement. It uses bullet points within text and a clear Args list. Some redundancy (e.g., date range repeated), but overall efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of 5 parameters, 2 required, and no output schema, the description covers the tool's purpose, parameter details, and data scope. It provides enough context for an agent to use the tool effectively, though lacking return format details (acceptable without output schema).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 40% (only country_code and indicator have descriptions). The description compensates by explaining all parameters: country_code format, indicator as 'World Bank indicator code', start_year/end_year defaults and ranges, and response_format options. It adds meaning beyond the schema, especially for parameters without schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Fetch World Bank macroeconomic indicator data for any country', specifying the verb (Fetch), resource (World Bank macroeconomic indicator data), and scope (any country). It also lists example indicators and a date range, distinguishing it from sibling tools like list_indicators or weather/disasters tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides common indicator codes and explains the tool's data coverage, implying when to use it. However, it does not explicitly state when not to use or mention alternatives like globalpulse_worldbank_list_indicators for finding indicator codes, which would help an agent decide.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnly, idempotent, etc., but the description adds that there is no API key required and no rate limit, which are important behavioral traits not captured in annotations. This adds value beyond the structured data.
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?
Two sentences only, both front-loaded with key information: first sentence tells what the tool does, second explains arguments. No extraneous text. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only tool with two parameters and no output schema, the description is almost complete. It explains input well and mentions the output fields. It could perhaps mention that the output is a rich JSON or markdown object, but the list of fields implies the structure. Overall, it's sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description adds significant value by explaining the 'country' parameter accepts names, ISO alpha-2, or alpha-3 codes with examples. The 'response_format' is clear from its enum and default. This compensates for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a full country profile listing specific fields (capital, region, etc.). The name and title also help. It distinguishes from siblings like globalpulse_countries_get_by_region which is a different operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides some usage context like 'No API key, no rate limit', but does not explicitly state when to use this tool over alternatives. The implied usage is for fetching a detailed profile of a single country, but no exclusionary guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds context that the tool returns the 'most commonly used' codes, not all codes, which is useful behavioral information beyond the annotations (readOnlyHint, idempotentHint, destructiveHint). However, it does not detail the response structure or error handling, but given the annotations already cover safety and idempotency, the description adds sufficient value.
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 extremely concise with two sentences, no redundant information, and front-loads the core purpose in the first sentence followed by usage guidance.
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?
For a simple tool with one optional parameter and no output schema, the description covers purpose and usage well but omits the parameter entirely. Given that the parameter is optional with an enum, this is a noticeable gap, making it adequate but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not mention the response_format parameter, which has 0% schema description coverage. With only one optional parameter controlling output format (json/markdown), the description should have at least indicated its existence to help the agent use the tool effectively.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'list', the resource 'World Bank indicator codes', and the scope 'most commonly used'. It also distinguishes itself from the sibling tool globalpulse_worldbank_get_indicator by indicating its role as a precursor for discovering codes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use this to discover codes before calling globalpulse_worldbank_get_indicator', providing clear guidance on when to use this tool versus the sibling tool for fetching specific indicator data.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate this is a safe, read-only, idempotent operation. The description adds value by stating there are no API key or rate limit constraints, which is useful behavioral context beyond what annotations provide.
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 extremely concise with two clear sentences and a line for arguments and examples. No filler, every sentence is informative.
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?
While the description covers purpose and parameters, it does not describe the return format or what data the forecast contains (e.g., temperature, precipitation). No output schema exists, so this gap affects completeness for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists all parameters with clarifications: latitude, longitude, timezone (with IANA example), and response_format. Examples for Mumbai and London add concrete meaning to values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool provides a 7-day daily weather forecast for any location, which is a specific verb+resource. It distinguishes from sibling tools like historical weather by specifying 'forecast' and '7-day'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description notes 'No API key, no rate limit,' implying ease of use and suggesting it's the go-to for quick forecasts. However, it does not explicitly state when not to use or compare to alternatives, but examples provide practical guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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By Om-Shree-0709 on June 30, 2026.
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Prompt Injection
WebAssembly

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/gpavan1992/Globalpulse-MCP'

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