whatshot-mcp

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v0.1.0
Disambiguation5/5
Each tool targets a distinct aspect: source schema, current fetch, history query, source listing, history search, trend series, and storage stats. The two history-related tools (query_history and search_history) are clearly separated by their operation styles (pagination vs. text search with evidence).
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern in snake_case (e.g., get_source_schema, fetch_current, query_history, list_sources). The verbs are semantically appropriate for each action, and there are no camelCase or mixed conventions.
Tool Count5/5
Seven tools is well within the ideal range for a focused server. Each tool addresses a core need in the domain without redundancy or bloat, making the set easy to navigate.
Completeness4/5
The server covers a comprehensive read-only workflow: discover sources, understand schemas, fetch current data, query/search history, retrieve trends, and monitor storage. The only minor gap is the absence of a tool to explicitly persist new history captures, but this may be handled externally or by design.
Average 3.6/5 across 7 of 7 tools scored. Lowest: 3/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 4 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.
If the license does not appear after some time, you can manually trigger a new scan using the MCP server admin interface.
MCP servers without a LICENSE cannot be installed.
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.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds the behavioral detail of 'cursor pagination' and 'persisted' items, which is useful context but not extensive; it does not mention return format, cursor lifecycle, or other behavioral constraints.
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 a single, clear sentence that immediately states the tool's purpose and a key feature. There is no redundant information, and the structure is appropriately 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?
Despite having an output schema and annotations, the description lacks context needed for a tool with 7 parameters and sibling query tools. It does not explain what 'historical items' are, how filters interact, or how cursor pagination behaves, leaving significant gaps for the agent.
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 schema has 7 optional parameters with 0% description coverage, so the description must compensate but fails to do so. The only hint is 'cursor pagination' which vaguely relates to the cursor parameter, but there is no explanation of kind, site, limit, since, until, or board_key.
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 uses a specific verb ('Query') and resource ('persisted historical items'), making the core function clear. However, it does not explicitly distinguish this tool from sibling tools like search_history, which likely also queries history, so it falls short of a 5.
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 such as search_history or fetch_current. There is no mention of context, prerequisites, or exclusions, leaving the agent to infer usage from the name alone.
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=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds that the response includes boards and accepted parameters, but does not disclose error behavior, response format, or any side effects—adequate but not rich.
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 a single concise sentence, front-loading the verb and object with no filler or redundant information. Every word contributes to the meaning.
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 one-parameter read-only tool with an output schema, the description covers the core return elements (boards, accepted parameters) and is adequate. It could mention how to specify a specific source or handle missing sources, but the output schema fills in return structure.
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 must compensate, but it does not explain the 'site' parameter. It only says 'one source', implying the parameter identifies the source, but leaves meaning entirely to the parameter name.
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 uses the specific verb 'Describe' with the resource 'source' and specifies that it returns 'boards' and 'accepted parameters', clearly distinguishing it from sibling history/fetch tools. The content is more detailed than a generic 'Get schema'.
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 only states what it does without context, prerequisites, or exclusions. Any usage is implied solely by the name and sibling list.
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?
The annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds a scope constraint ('one historical item') and specifies the metrics ('rank and hot-value'), but it does not disclose any additional behavioral traits such as authentication requirements, rate limits, or data handling. This is acceptable given the annotations, but the description itself provides only marginal extra 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 a single sentence that is front-loaded with the action and subject. There is no wasted words or redundancy. It is appropriately concise for a straightforward getter tool.
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?
Despite having an output schema (which reduces the need to describe return values) and rich annotations, the description is incomplete for a tool with 6 parameters. It does not explain how the parameters interact (e.g., that since/until define the time range and bucket controls granularity), nor does it clarify what 'historical item' implies about required identifiers. The description is too minimal to fully guide correct invocation.
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%, meaning the schema provides no descriptions for parameters. The description must compensate but does not. It only mentions 'rank and hot-value trends,' which relates to the output, not the meaning of parameters like site, board_key, since, until, and bucket. The agent is left to infer parameter semantics from names and defaults, which is insufficient for a 6-parameter tool.
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's function: 'Get rank and hot-value trends for one historical item.' The verb 'Get' is specific, the resource ('rank and hot-value trends') is concrete, and the scope ('for one historical item') differentiates it from sibling tools like query_history or search_history, which likely handle broader queries.
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 a use case (retrieving trends for a single item) but provides no explicit 'when to use this vs alternatives' guidance. It does not name any sibling tools or describe when this tool would be preferred over others like fetch_current or query_history. The usage context is only implied by the phrase 'historical item,' which is a weak form of guidance.
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 a useful behavioral trait: results are attributable evidence, not free-form summaries, and the search covers persisted content. This complements the annotations (readOnly, idempotent) without contradicting them, though it does not mention pagination or rate limits.
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 a single sentence with two clauses, front-loaded with the verb and target. Every word earns its place, and there is no redundant or vague language.
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?
Despite having an output schema and annotations, the description fails to compensate for the complete lack of parameter descriptions. For a tool with 7 parameters and overlapping siblings, the description is too sparse for reliable tool selection and invocation.
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 schema description coverage at 0%, the description must compensate by explaining parameter meanings, but it only implies that the keyword searches the listed content types. It fails to clarify site, limit, since, until, cursor, or board_key, leaving a significant 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 action ('Search') and the specific resources (persisted titles, descriptions, and newsflash content). It also distinguishes itself by noting it returns attributable evidence, not free-form summaries, which separates it from summarization tools.
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 siblings like query_history or fetch_current. It does not mention exclusions or specify scenarios where this tool is preferred.
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 the specific behavioral detail that the tool 'may access the upstream website but never persists a history capture.' This goes beyond the annotations (readOnlyHint, openWorldHint) by disclosing the non-persistence side effect, which is valuable for understanding the tool's impact.
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 concise, containing two sentences that front-load the primary purpose and add one critical behavioral caveat. Every word earns its place without unnecessary detail.
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 presence of rich annotations and an output schema reduces the need for the description to cover safety and return values. The description adds the key non-persistence distinction, but the lack of parameter guidance and vague 'board' terminology leave moderate gaps in fully understanding the tool's invocation requirements.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides no explanation of the four parameters (site, limit, params, path_type). Since the schema has zero descriptions, the agent must rely solely on parameter names, which is inadequate for the ambiguous 'params' and 'path_type' fields.
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's purpose with a specific verb and resource: 'Fetch a current board.' The word 'current' distinguishes it from sibling history tools like query_history and search_history, making the tool's role explicit.
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 for current data (as opposed to historical) by stating it 'never persists a history capture,' but it does not explicitly name alternatives or provide direct when-to-use versus when-not-to-use guidance. The distinction from history tools is suggested rather than stated.
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?
Annotations already declare readOnlyHint and idempotentHint, so the safety profile is known. The description adds no extra behavioral context such as the meaning of 'freshness', performance implications, or permissions. It does not contradict annotations, but it also does not enrich what the agent already knows.
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 a single sentence of seven words, front-loaded with the verb 'Return'. It is concise, informative, and contains no filler, making it easy to parse and act on immediately.
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 stats tool, the description is mostly complete. It does not elaborate on what 'freshness' means or the exact return format, but the output schema is present and likely covers these details. With no parameters and strong annotations, this level of description is sufficient.
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 tool has no parameters, and the schema is empty with 100% coverage. The description implicitly conveys that no arguments are required, and there is nothing to explain about parameters. This is a perfect score for parameter semantics as there is no burden.
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 storage counts and freshness for local history, using a specific verb ('Return') and resource ('local history storage counts and freshness'). This distinguishes it from sibling tools that focus on fetching or querying data, making its purpose unambiguous.
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 is provided on when to use this tool versus alternatives. It does not mention contexts, exclusions, or contrast with sibling tools like query_history or list_sources. The description is purely functional and offers no decision-making support.
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 readOnly, idempotent, non-destructive. The description adds the behavioral trait that this operates 'without network access', which is not covered by annotations and is meaningful for an agent deciding to call it in an offline environment. It also hints that only 'discoverable' sources are included, adding nuance about the result scope.
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 a single sentence, front-loaded with the verb 'List', and every word earns its place. It conveys the action, resource, scope qualifier, and a key operational constraint without any filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list operation with no parameters, an output schema present, and strong annotations, the description is complete. It provides the essential operational context (offline, discoverable sources) without needing to explain return values or error behavior, which the output schema would cover. The complexity is low, so the description fully satisfies what an agent needs.
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?
This tool has zero parameters, so the schema is empty and description coverage is trivially 100%. Per the scoring guide, a 0-parameter tool scores a baseline of 4 because no parameter explanation is needed. The description doesn't need to add anything, and it doesn't.
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') and the resource ('all discoverable WhatsHot sources'), with a specific qualifier 'without network access' that adds meaning beyond a generic list operation. It distinguishes from siblings like fetch_current or get_source_schema, which target different actions.
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 implies when to use this tool: when you need to enumerate all discoverable sources, particularly in an offline context ('without network access'). While it doesn't explicitly name alternatives, the sibling tools clearly serve different purposes, so the usage context is evident. The lack of an explicit 'use instead of X' prevents a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![whats-hot-api MCP server](https://glama.ai/mcp/servers/RayLLLU/whats-hot-api/badges/card.svg)](https://glama.ai/mcp/servers/RayLLLU/whats-hot-api)

Score Badge

Copy to your README.md:

[![whats-hot-api MCP server](https://glama.ai/mcp/servers/RayLLLU/whats-hot-api/badges/score.svg)](https://glama.ai/mcp/servers/RayLLLU/whats-hot-api)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
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/RayLLLU/whats-hot-api'

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