Agent Newsstand
Server Details
Market data and web intelligence for AI agents, paid per call in USDC on Base via x402.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Available Tools
16 toolscalendarBInspect
Upcoming US economic release dates (FRED calendar, live-fetch)
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the tool is a 'live-fetch' (implying real-time data retrieval) and focuses on economic release dates. However, it omits behavioral details like whether the tool is read-only, rate limits, or what happens if no releases are found. The description is adequate but not comprehensive.
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 a single, front-loaded sentence that efficiently conveys the tool's core functionality and source. It is not verbose, and every part adds meaning, though it could be rephrased to include usage hints without increasing length.
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 has only 1 parameter, no required params, no output schema, and no nested objects, the complexity is low. The description sufficiently explains what the tool does (retrieve US economic release dates via FRED live-fetch). However, it lacks details on the output format (e.g., date range, fields returned) and does not specify that it only covers US data, which would be useful for completeness.
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?
Schema description coverage is 0%, so the description must compensate. The 'limit' parameter (default 25) is implicitly about controlling how many upcoming dates to return, but the description does not explain what 'limit' means in the context of calendar entries (e.g., number of days or events). The description adds minimal value beyond the schema's default value.
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 retrieves 'Upcoming US economic release dates' from the 'FRED calendar' and does a 'live-fetch', providing specificity about the source and functionality. It effectively distinguishes from siblings like 'earnings' (corporate earnings) and 'macro' (broader macro data), but could be slightly improved by noting the data is US-specific in the purpose.
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?
No guidance is provided on when to use this tool versus alternatives like 'macro' or 'candles'. It does not clarify limitations (e.g., only US economic releases) or scenarios where another tool would be more appropriate, leaving the agent to infer usage from the description alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
candlesBInspect
Daily OHLCV candles for a venue symbol
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | ||
| symbol | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It states 'Daily OHLCV candles' which implies read-only historical data without side effects. However, it does not clarify whether the data is live-delayed, if it requires authentication, or if there are any rate limits. Based on the context, a conservative 3 is appropriate as it covers the basic behavior but lacks depth.
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 a single line without filler, earning its place. However, it could be slightly more structured (e.g., specifying that it returns data for the last N days). It is front-loaded and concise but leaves some gaps that require expansion.
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 has no output schema, a more complete description could explain the return format (e.g., array of OHLCV objects). It only describes input behavior. With no annotations, it is minimally adequate for a simple 2-parameter tool but lacks details that would help an agent interpret results or handle errors.
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?
Schema description coverage is 0%, so the description must compensate for the two parameters but does not. It mentions 'daily' but doesn't connect to the 'days' parameter (e.g., how many days back). 'Symbol' is self-explanatory from the schema but the description adds no additional context. Since there are only 2 parameters and no compensated semantics, a baseline 3 is fair.
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 uses specific verbs ('OHLCV' implying open, high, low, close, volume) and a resource ('candles' for a venue symbol). It clearly states it provides daily data. However, it does not differentiate from sibling tools like 'history' which could also involve time-series data, so a 5 is not warranted.
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 for retrieving OHLCV candle data for a symbol. However, it provides no guidance on when to use this tool versus alternatives like 'history' or 'calendar', nor does it specify any prerequisites or exclusions (e.g., date range limitations, symbol format). Only implied context from the sibling names is available.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
contextCInspect
Full trading context for a tokenized asset
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | ||
| symbol | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It does not mention whether the tool is read-only, what data it returns, any side effects, permission requirements, or rate limits. This is a critical gap for a data retrieval tool.
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 extremely short (7 words) but lacks necessary detail. It is not a model of conciseness because it sacrifices comprehensiveness; multiple important aspects (params, usage, behavior) are absent. The single sentence does not front-load critical information.
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 has two parameters, no output schema, and no annotations, the description must be highly informative. It is not. It omits what the tool returns, how to interpret results, and any prerequisites or limitations. Completely inadequate for an agent to use 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?
With 0% schema description coverage, the description should explain parameter meanings beyond the schema. It adds that the asset is 'tokenized' and hints at 'trading context', but does not clarify the 'days' parameter (likely a lookback period) or the expected format of 'symbol'. Very minimal added value.
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 'Full trading context for a tokenized asset' gives a general idea but is vague. It implies retrieving market data for a tokenized asset but does not specify what 'context' includes (e.g., price, volume, fundamentals). It fails to distinguish from sibling tools like 'candles' or 'history' which may provide overlapping data.
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?
No guidance is given on when to use this tool versus alternatives. With many sibling data tools (calendar, candles, earnings, etc.), the agent has no criteria to decide that 'context' is the right choice for a given task.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
earningsBInspect
Next earnings date for a symbol, or a rolling calendar window
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | ||
| symbol | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description bears full burden. It hints at output (next earnings date, rolling window) but does not disclose whether it is read-only, rate limits, or what happens with null parameters.
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?
Single sentence with no filler. Every word contributes to the core purpose.
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?
Despite low complexity, the description omits output format, edge cases, and how the two parameters interact. More detail is needed for the agent to invoke 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?
Schema description coverage is 0%. The description loosely implies 'symbol' is a ticker and 'days' controls the window, but adds no precise meaning beyond parameter names. Does not explain defaults or behavior when omitted.
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 retrieves the next earnings date for a symbol or a rolling calendar window. It specifies the resource (earnings date) and distinguishes from sibling tools like calendar or candles.
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?
No guidance on when to use this tool versus alternatives. No mention of prerequisites, when not to use, or related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
feedbackAInspect
FREE feedback: tell us what you needed but didn't get (missing endpoint, wrong output shape, price objection, bug). No payment.
| Name | Required | Description | Default |
|---|---|---|---|
| wanted | Yes | ||
| contact | No | ||
| context | No | ||
| category | No | other |
Output Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully bears the transparency burden. It reveals the tool is free and non-payment-related, but does not disclose whether feedback is anonymous, how it gets processed, whether multiple submissions are allowed, or any rate limits. The lack of behavioral context (e.g., 'This is a one-way communication; no guaranteed response') leaves the agent under-informed.
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 two sentences long with no filler. Front-loaded with the key action 'FREE feedback', followed by a concise list of examples. However, the phrase 'No payment' repeats the concept of 'FREE' and could be removed for even tighter structure.
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 low complexity and presence of an output schema (which presumably handles return value documentation), the description covers the basic purpose and some affordances. However, the complete lack of parameter documentation and behavioral transparency makes it merely adequate, not complete.
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?
Schema description coverage is 0%, meaning the description must compensate for all four parameters. It only mentions 'wanted' implicitly via the feedback request and fully ignores 'contact', 'context', and 'category'. The agent has no guidance on format, constraints, or how to fill these fields beyond the schema's basic names.
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: collecting user feedback about missing endpoints, wrong output shapes, price objections, or bugs. The verb 'tell us what you needed but didn't get' is specific, and the examples disambiguate from the 16 sibling tools, none of which suggest feedback collection.
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 explicitly says 'FREE feedback' and 'No payment', which guides usage when to use it (free-form feedback) and hints at when not to (not for paid requests). However, it does not explicitly contrast with siblings or state exclusions like 'do not use for general support questions'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
filingsCInspect
Latest SEC filings for an equity symbol
| Name | Required | Description | Default |
|---|---|---|---|
| n | No | ||
| symbol | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full responsibility for disclosing behavioral traits. It only states the basic function, omitting details like how many filings are returned (controlled by n), authentication needs, or any side effects. This significant gap results in a score of 2.
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 a single concise phrase, front-loaded with the key action and resource. It contains no wasted words. While it could include more detail without losing conciseness, the current form is efficient and direct. Score 4 reflects good conciseness with room for slight structural improvement.
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 (2 parameters, no output schema, no annotations), the description is incomplete. It fails to explain the 'n' parameter or describe the return data format. A complete description would at least mention the result count and what a filing entry contains. This inadequacy yields a score of 2.
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?
Schema description coverage is 0%, so the description must add meaning. It adds 'equity' context to the symbol parameter but completely ignores the 'n' parameter (count of filings). The description does not compensate for the lack of schema descriptions, leading to a score of 2.
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 'Latest SEC filings for an equity symbol' clearly states the action (retrieve filings) and the resource (SEC filings for a symbol). It is specific but does not distinguish from sibling tools like earnings or history, which could be considered related. A 4 is appropriate due to the lack of sibling differentiation.
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?
No guidance is provided on when to use filings versus alternatives. There are no mentions of prerequisites, exclusions, or typical use cases. This scores a 2 as there is no usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
historyCInspect
Daily closes + range change for a symbol
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | ||
| symbol | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It states 'Daily closes + range change' but does not disclose whether this is a read-only operation, what happens on invalid symbols, rate limits, or any side effects. Minimal transparency.
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 short (6 words), which is concise, but it lacks structure and omits critical information. Every word could earn its place if it were more informative, but currently it is under-specified.
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 no output schema, annotations, and minimal schema descriptions, the description does not explain return format, pagination, or example usage. It is incomplete for an agent to understand what to expect or how to handle responses.
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?
Schema description coverage is 0%, so the description must compensate. It mentions 'symbol' implicitly but does not explain the 'days' parameter (default 30, meaning unclear). The description adds no semantic detail beyond what is inferrable from the name 'history'.
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 'Daily closes + range change for a symbol' gives a vague idea of output but lacks an explicit verb (e.g., 'get', 'retrieve'). It does not differentiate from the sibling 'candles' which likely provides similar price data, so purpose is ambiguous.
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?
No guidance on when to use this tool versus alternatives. No mention of prerequisites, contexts, or exclusions. The description does not help an agent decide between history and siblings like 'candles' or 'context'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
localCInspect
Location-targeted search with place-link extraction
| Name | Required | Description | Default |
|---|---|---|---|
| q | Yes | ||
| limit | No | ||
| country | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility for behavioral traits. It only states the action (search + extraction) without disclosing whether it is read-only, what permissions are needed, rate limits, or side effects. The description is too minimal to inform safe and accurate invocation.
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 a single, efficient sentence. However, it lacks structure (no breakdown of behavior or parameters) and is too sparse to be fully helpful. It is not verbose, but the conciseness comes at the cost of clarity and completeness.
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 no output schema, no annotations, and zero parameter descriptions, the description must provide comprehensive context. It only gives a high-level purpose (search + extraction) but omits return format, parameter usage, and example scenarios. The tool is underspecified for reliable agent use.
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?
Schema description coverage is 0%, so the description must add meaning to parameters. It mentions 'location-targeted' but does not explain which parameter controls location (likely 'country' or part of 'q'). No clarification on 'q' (search query), 'limit' (pagination), or 'country' (restriction). The description fails to compensate for the missing schema descriptions.
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 'Location-targeted search with place-link extraction' clearly identifies the tool as a search function with location targeting and extraction of place links. It distinguishes from sibling tools like 'search' (general search) and 'place' (likely place details). However, the exact meaning of 'place-link extraction' is slightly ambiguous.
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?
No guidance on when to use this tool versus alternatives like 'search' or 'place'. No prerequisites, exclusions, or context for deciding between siblings. The agent must 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.
macroAInspect
Latest US macro indicators (CPI/NFP/U3/oil) with release flags
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description indicates the tool returns latest data with release flags, suggesting it's read-only and time-sensitive. No annotations exist, so the description carries the full behavioral disclosure burden. It doesn't mention caching behavior, update frequency, data source, or whether historical data is accessible.
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 a single, concise sentence that front-loads the core purpose ('Latest US macro indicators') and adds specific examples and features ('release flags'). Every word is essential and earns its place with no wasted verbiage.
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?
For a zero-parameter tool with no output schema, the description provides reasonable completeness: it names the type of data (US macro indicators), gives examples (CPI/NFP/U3/oil), and mentions a key feature (release flags). However, it could be more complete by specifying whether data includes historical values, the time range covered, or units of measurement.
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?
With zero parameters and 100% schema coverage, the description correctly identifies that no input is needed. The description adds value by explaining what data the tool returns (CPI/NFP/U3/oil with release flags), which helps the agent understand the fixed output. Since there are no parameters, a 4 is appropriate for providing semantic context beyond the empty schema.
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 provides 'Latest US macro indicators' and lists specific examples (CPI/NFP/U3/oil) with 'release flags'. This is a specific verb-resource combination ('get indicators') with enough detail to distinguish from sibling tools like 'calendar' or 'earnings', though it doesn't explicitly differentiate from them.
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 this is for retrieving macro economic data with release date flags, which suggests use when needing up-to-date US economic indicators. However, it provides no explicit when-to-use or when-not-to-use guidance, and doesn't mention alternatives among the 14 sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
placeCInspect
Compound: local search + business website content
| Name | Required | Description | Default |
|---|---|---|---|
| q | Yes | ||
| country | No | ||
| max_chars | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must fully disclose behavior. It only mentions 'local search + business website content' without explaining whether it makes multiple API calls, rate limits, authentication needs, or output format. This is a critical gap.
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 extremely short (one phrase), but it is underspecified rather than concise. It fails to convey essential information, making it ineffective despite its brevity.
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?
With 3 parameters, no output schema, and no annotations, the description is drastically incomplete. Agents cannot understand what the tool returns, how to use parameters, or what to expect, making it nearly unusable for correct invocation.
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?
Schema description coverage is 0% (no parameter descriptions), and the tool description does not reference any parameters. The three parameters (q, country, max_chars) are completely unexplained, leaving the agent to guess their purpose and format.
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 'Compound: local search + business website content' clearly indicates the tool combines two functionalities, distinguishing it from siblings like 'local' or 'search'. However, it lacks an explicit verb (e.g., 'retrieve' or 'search'), reducing clarity slightly.
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?
No guidance is provided on when to use this tool versus alternatives. The description only states what it is a compound of, without specifying scenarios or exclusions. For example, it does not say 'use this when you need both local results and website text'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
readBInspect
Any public URL as clean Markdown
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It does not state whether the tool modifies anything (destructive behavior), requires authentication, has rate limits, handles errors for non-accessible URLs, or what happens with dynamic content. 'Clean Markdown' is vague and could mean different things.
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 extremely concise at 5 words, with no wasted text. It front-loads the core purpose immediately. Every word serves a purpose.
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 has 1 parameter, no output schema, and no annotations, the description is incomplete. It doesn't describe error behavior, output structure, or limitations (e.g., supported content types, size limits). For a simple tool, more context is needed to ensure correct agent usage.
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?
Schema description coverage is 0%, meaning the schema provides no parameter descriptions. The description does not add meaning to the 'url' parameter beyond its name and type. It doesn't specify URL format requirements (e.g., must include http/https), max length, or accepted protocols.
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 'Any public URL as clean Markdown' clearly states the verb (read/convert) and resource (public URL), and the output format (clean Markdown). It distinguishes itself from sibling tools like 'screenshot' and 'url_safety' by implying a text extraction function rather than image capture or security checking.
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 for converting public URLs to Markdown, but provides no guidance on when not to use it (e.g., for private/internal URLs, or when to use 'screenshot' for visual content). No exclusions or alternatives are mentioned beyond what sibling names suggest.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
screenshotCInspect
Screenshot of any public URL (viewport PNG)
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full responsibility for behavioral disclosure. It only states 'Screenshot of any public URL (viewport PNG)', omitting details about viewport size, load time, error handling, rate limits, or whether authenticated pages work. This leaves significant behavioral ambiguity.
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 a single, front-loaded sentence that communicates the core purpose without extraneous words. It could be slightly more informative (e.g., 'returns a viewport PNG image') without losing conciseness.
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?
With no output schema and no annotations, the description is the sole source of context. It does not explain the return format (beyond 'PNG'), possible errors, or how the tool interacts with sibling tools like 'url_safety'. For a tool with 1 parameter and no technical metadata, more guidance is expected to complete the agent's understanding.
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?
Schema description coverage is 0% (no param descriptions provided), so the description must compensate. It adds the constraint that the URL must be 'public', which is meaningful but minimal. It does not specify expected URL format, protocol support, or what happens with non-public URLs. Baseline 3 is appropriate given partial compensation.
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 captures a screenshot of any public URL and outputs a viewport PNG. The verb and resource are unambiguous. However, it does not differentiate from sibling tools like 'read' or 'url_safety', which could be used for retrieving content from URLs.
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?
No guidance is provided on when to use this tool versus alternatives (e.g., 'read' for text extraction or 'url_safety' for checking URLs). There are no prerequisites, restrictions, or examples of appropriate use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
searchCInspect
Token-efficient search results (google/bing/yandex)
| Name | Required | Description | Default |
|---|---|---|---|
| q | Yes | ||
| limit | No | ||
| cursor | No | ||
| engine | No | ||
| country | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description hints at 'token-efficient' results, which suggests a behavioral trait, but without annotations, it fails to disclose other important behaviors such as read-only nature, authentication needs, rate limits, or what the response contains.
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 a single sentence, which is concise but not effectively structured. It lacks bullet points or clear separation of concerns, and the brevity sacrifices important details.
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 has 5 parameters, no output schema, and no annotations, the description is grossly incomplete. It does not explain pagination (cursor), default behaviors, or return format, leaving the agent with significant gaps.
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?
Schema description coverage is 0%, so the description must compensate. It only implies the 'engine' parameter via the engine names, but does not explain 'q', 'limit', 'cursor', or 'country'. This is insufficient for an agent to use the tool correctly.
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 states 'search results' with engine options, which is clear enough for a generic search tool. However, it does not differentiate from sibling tools like 'local' or 'history', and the resource being searched is not explicitly stated (e.g., web search).
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?
No guidance is provided on when to use this tool versus alternatives. The description does not mention when not to use it or suggest sibling tools for specific cases like location or financial data.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
universeBInspect
Tradeable asset universe (Hyperliquid xyz DEX)
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It does not mention whether the operation is read-only, whether it has side effects, rate limits, or any other behavioral constraints. The description only states the content, not the behavior.
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 extremely concise—a single sentence with no unnecessary words. It is front-loaded with the key subject. However, it could arguably be too terse, missing an explicit verb that would improve clarity without adding length.
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?
With no output schema, the description should explain what is returned (e.g., format, fields). It only says 'Tradeable asset universe', which is too vague. The agent does not know whether it receives asset symbols, full metadata, or a list of objects. Completeness is low given the lack of structured return information.
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?
There are zero parameters, and the schema coverage is 100% (trivially). The description adds no parameter-level detail, but with no parameters, a baseline of 4 is appropriate. The description is clear about what the tool returns, which is sufficient for a parameterless tool.
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 that the tool provides the tradeable asset universe for Hyperliquid DEX. It uses a noun that implies a list, which distinguishes it from siblings like 'candles' or 'history'. However, it lacks a specific verb (e.g., 'lists') and does not explicitly differentiate from tools like 'search' or 'context'.
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?
No guidance is provided on when to use this tool versus alternatives. The description only states what it is, without mentioning prerequisites, typical use cases, or situations where another tool would be preferred. Sibling tools exist (e.g., 'candles', 'history') but no differentiation is offered.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
unlockCInspect
Any public URL as raw HTML (captcha/bot-wall handled)
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | ||
| max_chars | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It reveals one behavioral trait: captcha/bot-wall handling. However, it omits other important behaviors such as redirect handling, request headers, rate limiting, error codes, or output format details (e.g., whether it returns the full page or truncated content). The single trait is insufficient for an agent to predict side effects.
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 a single sentence, highly concise and front-loaded with the core purpose. Every word adds value. However, the extreme brevity sacrifices necessary detail, making it slightly under-specified. Still, it avoids fluff and this dimension rewards conciseness.
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 has two parameters (one required), no output schema, and no schema descriptions, the description is far from complete. It fails to explain return values, error conditions, authentication needs (public only), or the effect of max_chars. A thorough description would cover these to enable safe and correct use.
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?
Schema description coverage is 0%, so the description must compensate. It does not mention either parameter ('url' or 'max_chars'). The description does not clarify what 'url' format is expected (e.g., must include protocol) or what 'max_chars' controls (truncation limit). Without this, an agent cannot confidently provide correct values.
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 fetches a URL and returns raw HTML, specifying it handles captcha/bot walls. The verb 'unlock' is somewhat ambiguous, but the description resolves it to retrieving HTML. Among siblings like 'read', 'screenshot', and 'url_safety', this stands out as the HTML-fetching tool.
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?
No guidance is provided on when to use this tool versus alternatives like 'read' (which might return structured data), 'screenshot' (visual capture), or 'url_safety' (safety check). There is no mention of prerequisites, limitations, or exclusions (e.g., private URLs, non-HTTP schemes).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
url_safetyBInspect
URL reputation check (malware + phishing)
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description indicates a nondestructive, read-only operation (reputation check). With no annotations, it partially carries the burden. However, it lacks details on what the tool returns (e.g., a Boolean, score, or report), or any rate limits or authentication needs, leaving some transparency gaps.
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 two words plus a parenthetical. It is extremely concise and front-loads the essential information. Every word is meaningful with no waste.
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 single parameter and lack of output schema, the description is too sparse. It does not explain what the 'check' returns (e.g., safe/unsafe label, risk score), or whether it supports batching or works for all URL types. For a security-critical tool, more detail is expected.
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?
Schema description coverage is 0%, so the description must compensate. It does not clarify the URL format (e.g., must include scheme). However, with only one required parameter named 'url', the tool's purpose is fairly obvious, earning a baseline of 3.
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 checks URL reputation for malware and phishing. It uses specific, relevant verbs and resource types, and the focus on security threats distinguishes it from sibling tools like 'search' or 'read'.
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?
No guidance on when to use this tool vs. alternatives is provided. While the context of reputation checking is clear, the description does not mention what kinds of URLs are supported, limitations, or when a different tool (e.g., 'search') would be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
1 tool update
- Added
feedback
15 tool updates
- First observed
calendar - First observed
candles - First observed
context - First observed
earnings - First observed
filings - First observed
history - First observed
local - First observed
macro - First observed
place - First observed
read - First observed
screenshot - First observed
search - First observed
universe - First observed
unlock - First observed
url_safety
Frequently Asked Questions
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, then choose Claim with GitHub. An organization namespace such asio.github.acme/serveralso needs that organization to have installed the Glama AI GitHub App and approved its permissions, because GitHub discloses organization membership only to apps it has installed. Use HTTP or DNS when it has not.HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at
/.well-known/glama.jsonon 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
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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.
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Glama MCP Gateway
Add one secure layer between your agents and this server.
TDQS
Most tools have clearly distinct purposes: financial data tools (calendar, candles, earnings, etc.) are separate from web scraping tools (read, screenshot, unlock, etc.). However, there is some overlap between 'history' (daily closes + range change) and 'candles' (OHLCV), which could cause minor confusion.
Tool names are inconsistent: most are single-word nouns (e.g., 'calendar', 'candles') but some are verbs ('read', 'search', 'unlock') and one uses an underscore ('url_safety'). There is no uniform verb_noun or noun pattern, making it harder for an agent to predict tool names.
With 16 tools, the server is slightly above the ideal range of 3-15, but each tool appears to serve a distinct purpose. The count is manageable given the two domains (financial data and web scraping).
The financial data tools cover many common data points (economic releases, price history, filings, earnings) but miss order books, real-time trades, or news. The web scraping tools are comprehensive for fetching content but lack structured data extraction. The feedback tool suggests the server is still evolving, indicating notable gaps.