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TrendFlow

by dev.mory

Server Details

Google Trends data: interest over time, by region, related queries, and trending now.

If you are the author of this connector, you can claim ownership with GitHub, an HTTP challenge, or a DNS record. Claimed connector authors can inspect health checks, view analytics, and manage their listing.
Status
Healthy
Last Tested
Transport
Streamable HTTP
URL
Repository
dariomory/trendflow-js
GitHub Stars
2
Server Listing
trendflow

Available Tools

8 tools
get_interest_by_regionInterest by regionA
Read-only
Inspect

Break down search interest for one term by geography. Use this when the user asks where something is popular, or wants a regional or city-level comparison. Values are normalized relative interest (0-100 within the result set).

ParametersJSON Schema
NameRequiredDescriptionDefault
regionNoCountry code such as "US", "GB", "TH"; a sub-region such as "US-CA"; or a US metro code such as "807". Empty string means worldwide.
keywordYesA search term, or a topic id from search_topics (e.g. "/m/0mkz").
categoryNoGoogle Trends category id to restrict the query to; 0, the default, is every category. Narrowing disambiguates a word with several meanings without needing a topic id.
timeframeNoTime range. A preset, or a custom range as two ISO dates: "2023-01-01 2023-06-30". The range also sets granularity — hourly ranges return minute-level points and "all" returns monthly ones, so a long range cannot show a short spike.
resolutionNoGeographic granularity of the breakdown.
searchPropertyNoWhich Google surface to measure: empty for web search, or images, news, youtube, or froogle (Shopping). These are separate indexes, so values from different properties are not comparable to each other.

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint: true and openWorldHint: true, so safety is covered. The description adds valuable behavioral context beyond annotations: 'Values are normalized relative interest (0-100 within the result set).' This helps interpret results and clarifies scope ('for one term'). No contradiction with annotations.

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 three sentences, each earning its place: action, usage trigger, and value normalization. It is front-loaded with the primary purpose and contains no redundant or filler words. Ideal conciseness for a tool with a rich schema.

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 has 6 parameters, no output schema, and a read-only nature, the description covers the key usage context and result interpretation (normalized 0-100). It could mention the exact return shape (e.g., list of regions with values), but the name and schema provide enough for an agent to infer the output. The description is complete enough for a well-specified tool.

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?

The input schema provides 100% coverage with descriptions for all 6 parameters, including enums for resolution and searchProperty, and detailed descriptions for region and timeframe. The tool description does not add further parameter-level semantics; it only states scope and normalization. With high schema coverage, baseline 3 is appropriate.

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 starts with a specific verb+resource: 'Break down search interest for one term by geography.' It clearly differentiates from siblings like get_interest_over_time (which focuses on time) and get_related_queries (which focuses on related terms). The phrase 'where something is popular' further reinforces the geography-specific purpose.

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 provides explicit usage context: 'Use this when the user asks where something is popular, or wants a regional or city-level comparison.' While it does not list exclusions or alternative tools by name, the guidance is clear enough to distinguish from siblings. The absence of named alternatives prevents a 5, but the context is sufficient for selection.

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

get_interest_over_timeInterest over timeA
Read-only
Inspect

Get relative search interest for one or more terms over a historical period. Use this when the user asks how popular something is, whether it is rising or falling, or how several things compare — passing multiple keywords compares them on one scale. Values are normalized relative interest (0-100 within the result set), not absolute search volume.

ParametersJSON Schema
NameRequiredDescriptionDefault
regionNoCountry code such as "US", "GB", "TH"; a sub-region such as "US-CA"; or a US metro code such as "807". Empty string means worldwide.
categoryNoGoogle Trends category id to restrict the query to; 0, the default, is every category. Narrowing disambiguates a word with several meanings without needing a topic id.
keywordsYes1-5 search terms. Pass several to compare them against each other. Accepts topic ids from search_topics (e.g. "/m/0mkz") as well as literal phrases.
timeframeNoTime range. A preset, or a custom range as two ISO dates: "2023-01-01 2023-06-30". The range also sets granularity — hourly ranges return minute-level points and "all" returns monthly ones, so a long range cannot show a short spike.
searchPropertyNoWhich Google surface to measure: empty for web search, or images, news, youtube, or froogle (Shopping). These are separate indexes, so values from different properties are not comparable to each other.

TDQS

A4.4/5.0
Behavior4/5

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

With readOnlyHint=true and openWorldHint=true already declared, the description adds valuable context: values are normalized relative interest (0-100 within the result set), not absolute search volume. This goes beyond annotations and helps the agent interpret results correctly, though it does not cover return format 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?

Three sentences, front-loaded with the core action, and every sentence adds value—what it does, when to use it, and how to interpret results. No filler or repetition of schema details.

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 (5 parameters, no output schema), the description adequately covers the essential semantics: temporal scope, comparison behavior, and normalization. It could mention the return format (e.g., time series of points), but the normalization and comparison details largely compensate for the lack of an 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 100%, so the baseline is 3. The description enhances parameter understanding by explaining that multiple keywords are compared on one scale and that results are relative, not absolute. This adds interpretive meaning that the schema's field descriptions do not fully convey.

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 uses a specific verb ('Get') and resource ('relative search interest over a historical period'), clearly distinguishing it from siblings like get_interest_by_region (geographic) and get_related_queries (related terms). It also clarifies the comparative aspect ('passing multiple keywords compares them on one scale'), which sets expectations precisely.

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?

Explicit when-to-use guidance is provided ('Use this when the user asks how popular something is, whether it is rising or falling, or how several things compare'). It does not mention when not to use it or name alternative tools, but the context is clear enough for an agent to select this tool appropriately.

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

list_regionsList regionsA
Read-only
Inspect

Returns the geo codes Google Trends accepts. With no argument it lists every country; given a country code it lists that country's sub-regions — US states, German states, UK nations — each as a code and a name.

Any code returned here can be passed as the region argument of the other tools.

ParametersJSON Schema
NameRequiredDescriptionDefault
countryNoCountry code such as "US", "GB", "TH"; a sub-region such as "US-CA"; or a US metro code such as "807". Empty string means worldwide.

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds behavioral context: with no argument it lists all countries; with a country code it lists sub-regions, returning code-and-name pairs. It also clarifies that these codes are acceptable inputs elsewhere, which goes beyond the annotation.

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 exactly two sentences, front-loaded with the core purpose, and every clause adds value. No filler or repetition of schema content.

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 read-only reference tool with one optional parameter and no output schema, the description fully explains the input/output behavior (list of code/name pairs) and its integration with sibling tools. No critical information is missing.

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 100% with a detailed description for the `country` parameter. The description adds semantic meaning by explaining the effect of omitting the argument (list all countries) versus supplying a country code (list sub-regions). This complements the schema's format-level 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?

The description states a specific verb and resource: 'Returns the geo codes Google Trends accepts.' It clearly distinguishes itself from trend-analysis siblings by explaining it provides region codes, not trend data. The behavior with and without an argument is also described.

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 gives practical usage context: 'Any code returned here can be passed as the `region` argument of the other tools.' This tells the agent when to use this tool (to obtain valid region codes for sibling tools), but it does not explicitly state exclusions or alternatives beyond that implicit guidance.

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

research_bulkResearch many trendsA
Read-only
Inspect

Researches up to 10 topics in a single call, each with the same full picture as research_trend: interest over time, where it is most searched, and related queries. Each topic is looked up on its own scale, so they are not comparable to one another.

Use this when you need data across many topics — a long or rich research pass — instead of one tool call per topic. Each section is fetched independently, so a partial result is normal: any section that fails carries an error instead of data and the rest still returns.

ParametersJSON Schema
NameRequiredDescriptionDefault
regionNoCountry code such as "US", "GB", "TH"; a sub-region such as "US-CA"; or a US metro code such as "807". Empty string means worldwide.
topicsYes1-10 topics (terms or topic ids) to research. Each is looked up on its own scale, so they are not comparable to one another. Use this to gather data across many topics in one call instead of one tool call per topic.

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint. Description adds important behavioral details: each topic is looked up on its own scale (non-comparable), independent fetching per section, and normal partial failures. 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.

Conciseness5/5

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

Two short paragraphs: first explains capability and structure, second gives usage guidance. No wasted words. Front-loaded with the most critical info (max 10 topics, same full picture).

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?

Given the tool has only 2 parameters (both well-documented in schema) and no output schema, the description sufficiently covers behavior, usage context, error handling, and comparability caveat. A partial result note substitutes for return format details.

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 100%, so baseline is 3. Description reinforces parameter semantics: 'topics' must be 1-10 items, each looked up independently and not comparable across topics. Adds clarity that topics can be terms or topic IDs, which is not in 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 states the tool researches up to 10 topics per call, giving the same full picture as research_trend (interest over time, regional distribution, related queries). It clearly distinguishes this bulk version from the single-topic sibling by specifying batch size and mention of 'full picture' equivalence.

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?

Explicitly advises when to use: 'when you need data across many topics — a long or rich research pass — instead of one tool call per topic.' Also explains partial results are normal, setting expectations for error handling.

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

research_trendResearch a trendA
Read-only
Inspect

Returns a full picture of one term in a single call: interest over time, where it is most searched, and the queries people search alongside it. Suited to open-ended research on a topic rather than one narrow question.

Each section is fetched independently, so a partial result is normal: any section that fails carries an error instead of data and the rest still returns.

ParametersJSON Schema
NameRequiredDescriptionDefault
regionNoCountry code such as "US", "GB", "TH"; a sub-region such as "US-CA"; or a US metro code such as "807". Empty string means worldwide.
keywordYesA search term, or a topic id from search_topics (e.g. "/m/0mkz").

TDQS

A4.2/5.0
Behavior4/5

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

Annotations declare readOnlyHint and openWorldHint, but the description adds valuable behavioral context: sections are fetched independently, so partial results are normal and failures carry an 'error' field. This goes beyond the annotations and helps the agent understand that missing sections are expected, not a tool malfunction.

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 and front-loaded: the first sentence states the main capability, the second adds usage context, and the final note explains error semantics. Every sentence earns its place, with no redundancy or filler.

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 there is no output schema, the description provides a solid overview of the returned data sections and error behavior. However, it does not describe the exact structure or format of each section's data (e.g., time series format, region names). For a complex tool with multiple sections, a bit more detail on the response shape would be ideal, but the current description is adequate for selection and initial invocation.

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?

The input schema already covers both parameters with descriptions (keyword, region), and schema coverage is 100%. The description adds no further parameter-level detail, but it doesn't need to—the schema is self-sufficient. Baseline 3 is appropriate.

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 uses a specific verb ('Returns') and resource ('full picture of one term'), listing the exact sections: interest over time, where most searched, and related queries. It clearly distinguishes itself from the more granular siblings (get_interest_over_time, etc.) by framing itself as a comprehensive single-call research tool rather than a narrow query.

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 states it is 'Suited to open-ended research on a topic rather than one narrow question,' providing clear contextual guidance. It does not explicitly name alternative tools for narrow questions, but the sibling list and the 'rather than' phrasing imply when to use this versus the individual getters. The partial-result note also sets expectations for use.

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

search_topicsSearch topicsA
Read-only
Inspect

Resolves a name — a company, product, person, technology, or concept — to its Google Trends topic id (mid), with a type field that distinguishes same-name entities such as Nike the company from Nike the goddess.

A topic aggregates every spelling and translation of one concept, so it measures considerably more search activity than a literal phrase: the topic for "artificial intelligence" scores 62 where the literal string scores 1. The other TrendFlow tools accept a topic id anywhere they accept a keyword.

ParametersJSON Schema
NameRequiredDescriptionDefault
queryYesA search term, or a topic id from search_topics (e.g. "/m/0mkz").

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the readOnlyHint/openWorldHint annotations, the description explains that a topic aggregates spellings and translations, and quantifies the difference (AI topic scores 62 vs literal string's 1). This provides significant behavioral context for search volume semantics.

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 total. The first sentence states purpose and output, the second provides an illustrative example and integration context. Every sentence earns its place; there is no redundant or filler text.

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?

With one parameter and no output schema, the description fully explains what the tool returns (mid and type), why it matters (aggregated volume), and how it fits into the tool ecosystem. It is complete for a simple lookup tool.

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?

The schema already covers the single parameter (query can be a search term or an existing topic id) with 100% coverage. The description adds examples of entity types (company, product, person, etc.) but does not materially change understanding of the parameter's meaning or format beyond 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 uses a specific verb ('resolves') and names the resource ('Google Trends topic id') and output ('mid'), with an added 'type' field. It clearly distinguishes itself from sibling tools by focusing on entity resolution rather than trend measurement.

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 states that 'other TrendFlow tools accept a topic id anywhere they accept a keyword', implying this tool should be used to obtain topic ids for those tools. It gives a useful disambiguation example (Nike company vs goddess) but does not explicitly enumerate when not to use it or name alternative tools.

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. 1 tool update
    • Addedresearch_bulk
  2. 1 tool update
    • Addedlist_regions
  3. 5 tool updates
    • Changedget_interest_by_region5 fields changed
      • addedInput schema / properties / category
        Added value: +{
+  "description": "Google Trends category id to restrict the query to; 0, the default, is every category. Narrowing disambiguates a word with several meanings without needing a topic id.",
+  "maximum": 9007199254740991,
+  "minimum": 0,
+  "type": "integer"
+}
      • changedInput schema / properties / region / anyOf
        Previous value: -[
-  {
-    "enum": [
-      "",
-      "US",
-      "GB",
-      "DE",
-      "FR",
-      "IT",
-      "ES",
-      "CA",
-      "AU",
-      "JP",
-      "IN",
-      "BR",
-      "MX",
-      "NL",
-      "SE",
-      "PL",
-      "TR"
-    ],
-    "type": "string"
-  },
-  {
-    "pattern": "^[A-Z]{2}$",
-    "type": "string"
-  }
-]New value: +[
+  {
+    "enum": [
+      "",
+      "US",
+      "GB",
+      "DE",
+      "FR",
+      "IT",
+      "ES",
+      "CA",
+      "AU",
+      "JP",
+      "IN",
+      "BR",
+      "MX",
+      "NL",
+      "SE",
+      "PL",
+      "TR"
+    ],
+    "type": "string"
+  },
+  {
+    "pattern": "^[A-Z]{2}(-[A-Z0-9]{1,3})?$",
+    "type": "string"
+  },
+  {
+    "pattern": "^\\d{3}$",
+    "type": "string"
+  }
+]
      • changedInput schema / properties / region / description
        Previous value: -"Country code such as \"US\", \"GB\", \"TH\". Empty string means worldwide."New value: +"Country code such as \"US\", \"GB\", \"TH\"; a sub-region such as \"US-CA\"; or a US metro code such as \"807\". Empty string means worldwide."
      • addedInput schema / properties / searchProperty
        Added value: +{
+  "description": "Which Google surface to measure: empty for web search, or images, news, youtube, or froogle (Shopping). These are separate indexes, so values from different properties are not comparable to each other.",
+  "enum": [
+    "",
+    "images",
+    "news",
+    "youtube",
+    "froogle"
+  ],
+  "type": "string"
+}
      • addedInput schema / properties / timeframe
        Added value: +{
+  "anyOf": [
+    {
+      "enum": [
+        "now 1-H",
+        "now 4-H",
+        "now 1-d",
+        "now 7-d",
+        "today 1-m",
+        "today 3-m",
+        "today 12-m",
+        "today 5-y",
+        "all"
+      ],
+      "type": "string"
+    },
+    {
+      "pattern": "^\\d{4}-\\d{2}-\\d{2} \\d{4}-\\d{2}-\\d{2}$",
+      "type": "string"
+    }
+  ],
+  "description": "Time range. A preset, or a custom range as two ISO dates: \"2023-01-01 2023-06-30\". The range also sets granularity — hourly ranges return minute-level points and \"all\" returns monthly ones, so a long range cannot show a short spike."
+}
    • Changedget_interest_over_time8 fields changed
      • addedInput schema / properties / category
        Added value: +{
+  "description": "Google Trends category id to restrict the query to; 0, the default, is every category. Narrowing disambiguates a word with several meanings without needing a topic id.",
+  "maximum": 9007199254740991,
+  "minimum": 0,
+  "type": "integer"
+}
      • changedInput schema / properties / region / anyOf
        Previous value: -[
-  {
-    "enum": [
-      "",
-      "US",
-      "GB",
-      "DE",
-      "FR",
-      "IT",
-      "ES",
-      "CA",
-      "AU",
-      "JP",
-      "IN",
-      "BR",
-      "MX",
-      "NL",
-      "SE",
-      "PL",
-      "TR"
-    ],
-    "type": "string"
-  },
-  {
-    "pattern": "^[A-Z]{2}$",
-    "type": "string"
-  }
-]New value: +[
+  {
+    "enum": [
+      "",
+      "US",
+      "GB",
+      "DE",
+      "FR",
+      "IT",
+      "ES",
+      "CA",
+      "AU",
+      "JP",
+      "IN",
+      "BR",
+      "MX",
+      "NL",
+      "SE",
+      "PL",
+      "TR"
+    ],
+    "type": "string"
+  },
+  {
+    "pattern": "^[A-Z]{2}(-[A-Z0-9]{1,3})?$",
+    "type": "string"
+  },
+  {
+    "pattern": "^\\d{3}$",
+    "type": "string"
+  }
+]
      • changedInput schema / properties / region / description
        Previous value: -"Country code such as \"US\", \"GB\", \"TH\". Empty string means worldwide."New value: +"Country code such as \"US\", \"GB\", \"TH\"; a sub-region such as \"US-CA\"; or a US metro code such as \"807\". Empty string means worldwide."
      • addedInput schema / properties / searchProperty
        Added value: +{
+  "description": "Which Google surface to measure: empty for web search, or images, news, youtube, or froogle (Shopping). These are separate indexes, so values from different properties are not comparable to each other.",
+  "enum": [
+    "",
+    "images",
+    "news",
+    "youtube",
+    "froogle"
+  ],
+  "type": "string"
+}
      • addedInput schema / properties / timeframe / anyOf
        Added value: +[
+  {
+    "enum": [
+      "now 1-H",
+      "now 4-H",
+      "now 1-d",
+      "now 7-d",
+      "today 1-m",
+      "today 3-m",
+      "today 12-m",
+      "today 5-y",
+      "all"
+    ],
+    "type": "string"
+  },
+  {
+    "pattern": "^\\d{4}-\\d{2}-\\d{2} \\d{4}-\\d{2}-\\d{2}$",
+    "type": "string"
+  }
+]
      • changedInput schema / properties / timeframe / description
        Previous value: -"Time range for the series."New value: +"Time range. A preset, or a custom range as two ISO dates: \"2023-01-01 2023-06-30\". The range also sets granularity — hourly ranges return minute-level points and \"all\" returns monthly ones, so a long range cannot show a short spike."
      • removedInput schema / properties / timeframe / enum
        Removed value: -[
-  "now 1-d",
-  "now 7-d",
-  "today 12-m",
-  "today 5-y"
-]
      • removedInput schema / properties / timeframe / type
        Removed value: -"string"
    • Changedget_related_queries4 fields changed
      • addedInput schema / properties / category
        Added value: +{
+  "description": "Google Trends category id to restrict the query to; 0, the default, is every category. Narrowing disambiguates a word with several meanings without needing a topic id.",
+  "maximum": 9007199254740991,
+  "minimum": 0,
+  "type": "integer"
+}
      • addedInput schema / properties / region
        Added value: +{
+  "anyOf": [
+    {
+      "enum": [
+        "",
+        "US",
+        "GB",
+        "DE",
+        "FR",
+        "IT",
+        "ES",
+        "CA",
+        "AU",
+        "JP",
+        "IN",
+        "BR",
+        "MX",
+        "NL",
+        "SE",
+        "PL",
+        "TR"
+      ],
+      "type": "string"
+    },
+    {
+      "pattern": "^[A-Z]{2}(-[A-Z0-9]{1,3})?$",
+      "type": "string"
+    },
+    {
+      "pattern": "^\\d{3}$",
+      "type": "string"
+    }
+  ],
+  "description": "Country code such as \"US\", \"GB\", \"TH\"; a sub-region such as \"US-CA\"; or a US metro code such as \"807\". Empty string means worldwide."
+}
      • addedInput schema / properties / searchProperty
        Added value: +{
+  "description": "Which Google surface to measure: empty for web search, or images, news, youtube, or froogle (Shopping). These are separate indexes, so values from different properties are not comparable to each other.",
+  "enum": [
+    "",
+    "images",
+    "news",
+    "youtube",
+    "froogle"
+  ],
+  "type": "string"
+}
      • addedInput schema / properties / timeframe
        Added value: +{
+  "anyOf": [
+    {
+      "enum": [
+        "now 1-H",
+        "now 4-H",
+        "now 1-d",
+        "now 7-d",
+        "today 1-m",
+        "today 3-m",
+        "today 12-m",
+        "today 5-y",
+        "all"
+      ],
+      "type": "string"
+    },
+    {
+      "pattern": "^\\d{4}-\\d{2}-\\d{2} \\d{4}-\\d{2}-\\d{2}$",
+      "type": "string"
+    }
+  ],
+  "description": "Time range. A preset, or a custom range as two ISO dates: \"2023-01-01 2023-06-30\". The range also sets granularity — hourly ranges return minute-level points and \"all\" returns monthly ones, so a long range cannot show a short spike."
+}
    • Changedget_trending_now2 fields changed
      • changedInput schema / properties / region / anyOf
        Previous value: -[
-  {
-    "enum": [
-      "",
-      "US",
-      "GB",
-      "DE",
-      "FR",
-      "IT",
-      "ES",
-      "CA",
-      "AU",
-      "JP",
-      "IN",
-      "BR",
-      "MX",
-      "NL",
-      "SE",
-      "PL",
-      "TR"
-    ],
-    "type": "string"
-  },
-  {
-    "pattern": "^[A-Z]{2}$",
-    "type": "string"
-  }
-]New value: +[
+  {
+    "enum": [
+      "",
+      "US",
+      "GB",
+      "DE",
+      "FR",
+      "IT",
+      "ES",
+      "CA",
+      "AU",
+      "JP",
+      "IN",
+      "BR",
+      "MX",
+      "NL",
+      "SE",
+      "PL",
+      "TR"
+    ],
+    "type": "string"
+  },
+  {
+    "pattern": "^[A-Z]{2}(-[A-Z0-9]{1,3})?$",
+    "type": "string"
+  },
+  {
+    "pattern": "^\\d{3}$",
+    "type": "string"
+  }
+]
      • changedInput schema / properties / region / description
        Previous value: -"Country code such as \"US\", \"GB\", \"TH\". Empty string means worldwide."New value: +"Country code such as \"US\", \"GB\", \"TH\"; a sub-region such as \"US-CA\"; or a US metro code such as \"807\". Empty string means worldwide."
    • Changedresearch_trend2 fields changed
      • changedInput schema / properties / region / anyOf
        Previous value: -[
-  {
-    "enum": [
-      "",
-      "US",
-      "GB",
-      "DE",
-      "FR",
-      "IT",
-      "ES",
-      "CA",
-      "AU",
-      "JP",
-      "IN",
-      "BR",
-      "MX",
-      "NL",
-      "SE",
-      "PL",
-      "TR"
-    ],
-    "type": "string"
-  },
-  {
-    "pattern": "^[A-Z]{2}$",
-    "type": "string"
-  }
-]New value: +[
+  {
+    "enum": [
+      "",
+      "US",
+      "GB",
+      "DE",
+      "FR",
+      "IT",
+      "ES",
+      "CA",
+      "AU",
+      "JP",
+      "IN",
+      "BR",
+      "MX",
+      "NL",
+      "SE",
+      "PL",
+      "TR"
+    ],
+    "type": "string"
+  },
+  {
+    "pattern": "^[A-Z]{2}(-[A-Z0-9]{1,3})?$",
+    "type": "string"
+  },
+  {
+    "pattern": "^\\d{3}$",
+    "type": "string"
+  }
+]
      • changedInput schema / properties / region / description
        Previous value: -"Country code such as \"US\", \"GB\", \"TH\". Empty string means worldwide."New value: +"Country code such as \"US\", \"GB\", \"TH\"; a sub-region such as \"US-CA\"; or a US metro code such as \"807\". Empty string means worldwide."
  4. 6 tool updates
    • First observedget_interest_by_region
    • First observedget_interest_over_time
    • First observedget_related_queries
    • First observedget_trending_now
    • First observedresearch_trend
    • First observedsearch_topics

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TDQS

A4.3/5.0
Disambiguation4/5

Each tool targets a distinct Google Trends data type—regional, temporal, related queries, trending now, topic resolution—so agents can usually tell them apart. However, research_trend overlaps with three of the get_* tools by combining their outputs, so it could be selected instead of a specific tool if the agent wants just one slice. Search topics is clearly separate.

Naming Consistency4/5

Four tools consistently use the get_verb_noun pattern (get_interest_over_time, etc.), but research_trend and search_topics deviate with different verbs while still keeping snake_case verb_noun. The pattern is readable but not perfectly uniform.

Tool Count5/5

Six tools is an appropriate number for a Google Trends server, covering the main interest endpoints plus a convenience aggregator and a topic resolver. Not too many, not too few.

Completeness4/5

The server covers the core Google Trends features: time series, regional breakdown, related queries, trending now, and topic resolution. A notable gap is the absence of a related_topics endpoint (topics related to a keyword), which complements related queries. Overall, the surface is fairly complete for typical trend research tasks.

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