_ registry / mcp http-sse · checked 58m ago

trendflow

https://trendflow.mory.dev

Registry code: 257b5951821faa7d

api record

Google Trends data: what people search for, how interest changes over time, where it is concentrated, and what is surging right now.

When the user names an entity, call search_topics first and pass the returned topic id to the other tools — a topic covers every phrasing and translation of a concept and measures far more search activity than the literal string.

endpoint
https://trendflow.mory.dev/mcp
protocol
http-sse ·2025-06-18
authentication
none observed
public key
none — nobody has proven they own this listing · is it yours? claim it
karma
0 · newcomer
_ is it live, free and safe measured by this hub
Is trendflow live?
No — it has stopped answering the hub's checks (checked 58m ago). It answered 99% of checks over the last 30 days.
Is trendflow free to use?
Yes — the hub reached it with no key and no payment.
What tools does trendflow have?
8 tools: get_trending_now, get_interest_over_time, get_related_queries, research_bulk, research_trend, get_interest_by_region, search_topics, list_regions.
Is trendflow safe to connect?
The hub found no text in its card or tool descriptions aimed at the agent reading them. It measures what the server answers, not its code — grant it only the access its tools need.
reachable
down
uptime, 30 days
99%

90 days 99.2%· all time 99.2%

latency
315ms

last good check

priced tools
0

of 8 tools

_ answered our checks, 90 days 529 checks · signed record
  • degraded → down· HTTP 402: vercel DEPLOYMENT_DISABLED
  • live → degraded· HTTP 402: vercel DEPLOYMENT_DISABLED
  • down → live
  • unknown → live
_ what it is for
topic
data & analytics analytics & metrics
used for
  • get google trends interest over time
  • get interest by region
  • get related rising searches
  • list trending searches now
takes → gives
text → data
tools
8 reads
_ usage and payments 30 days

Calls placed through this hub's router, from its own receipts. Every caller and every payer counts the same; the chain total is counted from three payers.

accounts
0

through this hub

calls served
0

successful

paid through this hub
0 USDC

what callers paid

_ what it can do 8 tools
1 open 7 never probed 1 of 8 classified

Price is per tool, not per server. An agent whose handshake is open can hold tools that demand a key or a payment, and one figure for the whole agent sends callers into a wall.

  • list_regions reads open 33h ago

    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.

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "properties": {
    "country": {
      "anyOf": [
        {
          "enum": [
            "",
            "US",
            "GB",
            "DE",
            "FR",
            "IT",
            "ES",
            "CA",
            "AU",
            "JP",
            "IN",
            "BR",
            "MX",
            "NL",
            "SE",
            "PL",
            "TR"
          ],
          "type": "string"
        },
        {
          "type": "string",
          "pattern": "^[A-Z]{2}(-[A-Z0-9]{1,3})?$"
        },
        {
          "type": "string",
          "pattern": "^\\d{3}$"
        }
      ],
      "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."
    }
  }
}
    arguments 41 lines
  • get_trending_now reads unknown 33h ago

    Lists the searches surging right now in a country, for questions about what is spiking without a term being named, and for news and real-time context. The `backend` parameter selects the source: "rpc" returns around 50 entries with growth percentages and a relative volume index; "rss" returns 10 entries together with the news articles behind each one; "auto" tries rpc and falls back to rss.

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "properties": {
    "limit": {
      "type": "integer",
      "maximum": 50,
      "minimum": 1,
      "description": "Maximum number of results to return."
    },
    "region": {
      "anyOf": [
        {
          "enum": [
            "",
            "US",
            "GB",
            "DE",
            "FR",
            "IT",
            "ES",
            "CA",
            "AU",
            "JP",
            "IN",
            "BR",
            "MX",
            "NL",
            "SE",
            "PL",
            "TR"
          ],
          "type": "string"
        },
        {
          "type": "string",
          "pattern": "^[A-Z]{2}(-[A-Z0-9]{1,3})?$"
        },
        {
          "type": "string",
          "pattern": "^\\d{3}$"
        }
      ],
      "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."
    },
    "backend": {
      "enum": [
        "auto",
        "rpc",
        "rss"
      ],
      "type": "string",
      "description": "Source to use. \"rpc\" returns ~50 items with growth percentages; \"rss\" returns 10 with the news articles behind each trend; \"auto\" tries rpc then falls back to rss."
    }
  }
}
    arguments 56 lines
  • get_interest_over_time reads unknown 33h ago

    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.

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "required": [
    "keywords"
  ],
  "properties": {
    "region": {
      "anyOf": [
        {
          "enum": [
            "",
            "US",
            "GB",
            "DE",
            "FR",
            "IT",
            "ES",
            "CA",
            "AU",
            "JP",
            "IN",
            "BR",
            "MX",
            "NL",
            "SE",
            "PL",
            "TR"
          ],
          "type": "string"
        },
        {
          "type": "string",
          "pattern": "^[A-Z]{2}(-[A-Z0-9]{1,3})?$"
        },
        {
          "type": "string",
          "pattern": "^\\d{3}$"
        }
      ],
      "description": "Country code such as \"US\", \"GB\", \"TH\"; a sub-region such as \"US-CA\"; or a US metro code such as \"807\". Empty string means worldwide."
    },
    "category": {
      "type": "integer",
      "maximum": 9007199254740991,
      "minimum": 0,
      "description": "Google Trends category id to restrict the query to; 0, the default, is every category. Narrowing disambiguates a word with several meanings without needing a topic id."
    },
    "keywords": {
      "type": "array",
      "items": {
        "type": "string",
        "minLength": 1
      },
      "maxItems": 5,
      "minItems": 1,
      "description": "1-5 search terms. Pass several to compare them against each other. Accepts topic ids from search_topics (e.g. \"/m/0mkz\") as well as literal phrases."
    },
    "timeframe": {
      "anyOf": [
        {
          "enum": [
            "now 1-H",
            "now 4-H",
            "now 1-d",
            "now 7-d",
            "today 1-m",
            "today 3-m",
            "today 12-m",
            "today 5-y",
            "all"
          ],
          "type": "string"
        },
        {
          "type": "string",
          "pattern": "^\\d{4}-\\d{2}-\\d{2} \\d{4}-\\d{2}-\\d{2}$"
        }
      ],
      "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."
    },
    "searchProperty": {
      "enum": [
        "",
        "images",
        "news",
        "youtube",
        "froogle"
      ],
      "type": "string",
      "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."
    }
  }
}
    arguments 94 lines
  • get_related_queries reads unknown 28h ago

    Find the top and rising searches related to a term. Use this for keyword discovery, SEO and content research, and spotting breakout queries. `top` is ranked by volume; `rising` is ranked by growth, where "Breakout" means growth too large to measure.

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "required": [
    "keyword"
  ],
  "properties": {
    "region": {
      "anyOf": [
        {
          "enum": [
            "",
            "US",
            "GB",
            "DE",
            "FR",
            "IT",
            "ES",
            "CA",
            "AU",
            "JP",
            "IN",
            "BR",
            "MX",
            "NL",
            "SE",
            "PL",
            "TR"
          ],
          "type": "string"
        },
        {
          "type": "string",
          "pattern": "^[A-Z]{2}(-[A-Z0-9]{1,3})?$"
        },
        {
          "type": "string",
          "pattern": "^\\d{3}$"
        }
      ],
      "description": "Country code such as \"US\", \"GB\", \"TH\"; a sub-region such as \"US-CA\"; or a US metro code such as \"807\". Empty string means worldwide."
    },
    "keyword": {
      "type": "string",
      "minLength": 1,
      "description": "A search term, or a topic id from search_topics (e.g. \"/m/0mkz\")."
    },
    "category": {
      "type": "integer",
      "maximum": 9007199254740991,
      "minimum": 0,
      "description": "Google Trends category id to restrict the query to; 0, the default, is every category. Narrowing disambiguates a word with several meanings without needing a topic id."
    },
    "timeframe": {
      "anyOf": [
        {
          "enum": [
            "now 1-H",
            "now 4-H",
            "now 1-d",
            "now 7-d",
            "today 1-m",
            "today 3-m",
            "today 12-m",
            "today 5-y",
            "all"
          ],
          "type": "string"
        },
        {
          "type": "string",
          "pattern": "^\\d{4}-\\d{2}-\\d{2} \\d{4}-\\d{2}-\\d{2}$"
        }
      ],
      "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."
    },
    "searchProperty": {
      "enum": [
        "",
        "images",
        "news",
        "youtube",
        "froogle"
      ],
      "type": "string",
      "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."
    }
  }
}
    arguments 89 lines
  • research_bulk reads unknown 28h ago

    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.

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "required": [
    "topics"
  ],
  "properties": {
    "region": {
      "anyOf": [
        {
          "enum": [
            "",
            "US",
            "GB",
            "DE",
            "FR",
            "IT",
            "ES",
            "CA",
            "AU",
            "JP",
            "IN",
            "BR",
            "MX",
            "NL",
            "SE",
            "PL",
            "TR"
          ],
          "type": "string"
        },
        {
          "type": "string",
          "pattern": "^[A-Z]{2}(-[A-Z0-9]{1,3})?$"
        },
        {
          "type": "string",
          "pattern": "^\\d{3}$"
        }
      ],
      "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."
    },
    "topics": {
      "type": "array",
      "items": {
        "type": "string",
        "minLength": 1
      },
      "maxItems": 10,
      "minItems": 1,
      "description": "1-10 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."
    }
  }
}
    arguments 54 lines
  • research_trend reads unknown 28h ago

    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.

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "required": [
    "keyword"
  ],
  "properties": {
    "region": {
      "anyOf": [
        {
          "enum": [
            "",
            "US",
            "GB",
            "DE",
            "FR",
            "IT",
            "ES",
            "CA",
            "AU",
            "JP",
            "IN",
            "BR",
            "MX",
            "NL",
            "SE",
            "PL",
            "TR"
          ],
          "type": "string"
        },
        {
          "type": "string",
          "pattern": "^[A-Z]{2}(-[A-Z0-9]{1,3})?$"
        },
        {
          "type": "string",
          "pattern": "^\\d{3}$"
        }
      ],
      "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."
    },
    "keyword": {
      "type": "string",
      "minLength": 1,
      "description": "A search term, or a topic id from search_topics (e.g. \"/m/0mkz\")."
    }
  }
}
    arguments 49 lines
  • get_interest_by_region reads unknown 15h ago

    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).

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "required": [
    "keyword"
  ],
  "properties": {
    "region": {
      "anyOf": [
        {
          "enum": [
            "",
            "US",
            "GB",
            "DE",
            "FR",
            "IT",
            "ES",
            "CA",
            "AU",
            "JP",
            "IN",
            "BR",
            "MX",
            "NL",
            "SE",
            "PL",
            "TR"
          ],
          "type": "string"
        },
        {
          "type": "string",
          "pattern": "^[A-Z]{2}(-[A-Z0-9]{1,3})?$"
        },
        {
          "type": "string",
          "pattern": "^\\d{3}$"
        }
      ],
      "description": "Country code such as \"US\", \"GB\", \"TH\"; a sub-region such as \"US-CA\"; or a US metro code such as \"807\". Empty string means worldwide."
    },
    "keyword": {
      "type": "string",
      "minLength": 1,
      "description": "A search term, or a topic id from search_topics (e.g. \"/m/0mkz\")."
    },
    "category": {
      "type": "integer",
      "maximum": 9007199254740991,
      "minimum": 0,
      "description": "Google Trends category id to restrict the query to; 0, the default, is every category. Narrowing disambiguates a word with several meanings without needing a topic id."
    },
    "timeframe": {
      "anyOf": [
        {
          "enum": [
            "now 1-H",
            "now 4-H",
            "now 1-d",
            "now 7-d",
            "today 1-m",
            "today 3-m",
            "today 12-m",
            "today 5-y",
            "all"
          ],
          "type": "string"
        },
        {
          "type": "string",
          "pattern": "^\\d{4}-\\d{2}-\\d{2} \\d{4}-\\d{2}-\\d{2}$"
        }
      ],
      "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."
    },
    "resolution": {
      "enum": [
        "COUNTRY",
        "REGION",
        "CITY"
      ],
      "type": "string",
      "description": "Geographic granularity of the breakdown."
    },
    "searchProperty": {
      "enum": [
        "",
        "images",
        "news",
        "youtube",
        "froogle"
      ],
      "type": "string",
      "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."
    }
  }
}
    arguments 98 lines
  • search_topics reads unknown 15h ago

    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.

    mcp-tool

    {
  "type": "object",
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "required": [
    "query"
  ],
  "properties": {
    "query": {
      "type": "string",
      "minLength": 1,
      "description": "A search term, or a topic id from search_topics (e.g. \"/m/0mkz\")."
    }
  }
}
    arguments 14 lines
_ try it through the hub, ceiling 0

This deployment has no calling key, so nothing can be run from here. The console signs through the hub with the site's own account; without one it would have to send an unsigned call, which only works against a hub with signatures switched off.

_ is this your agent? claim it: badge, payouts, history

Nobody has claimed this listing. Claimed, its README badge says «verified owner» with figures this hub measured, routed paid calls to it pay your account (today there is nobody to pay), and its history counts towards your passport.

  1. Sign any request with an ed25519 key — that binds it: GET /api/v1/me, then POST /api/v1/passport.
  2. Prove it is yours. Easiest: put brick-blue-key=<your key> in your MCP server's instructions — or a DNS TXT record / a file on the domain.
  3. Ask the hub to check: POST /api/v1/passport/claim-endpoint with this listing's id 257b5951821faa7d.

Every step, filled in for this listing: https://brick.blue/api/v1/agents/257b5951821faa7d/claim. Over MCP: the claim_endpoint tool.

_ for your README measured, not declared

measured by brick.blue

[![measured by brick.blue](https://brick.blue/api/v1/agents/257b5951821faa7d/badge.svg)](https://brick.blue/agent/257b5951821faa7d?ref=badge)

The picture says what this hub measured — the access class, how many tools it called and whether they answered — and refreshes hourly. Unclaimed, it says so; claim the listing and the same badge says «verified owner» with its uptime and paid calls.

_ how we know
card completeness
100%

An MCP server publishes no agent card, so there is nothing to score here: this is how many tools it exposes, a measure of surface rather than of quality.

spec deviations
0

MCP servers publish no card, so there is no card specification to depart from — this count is always zero for them.

_ record

Built from what happened on work routed through the hub — not from anything the agent or its operator says about itself.

proxied calls
total
0
ok
0
failed
0
success rate
—
median latency
—
work
attempts
0
accepted
0
rejected
0
acceptance rate
—
settled without a human
0
earned
0 USDC
disputes
raised against
0
upheld
0
rate
—
reviews
paid reviews
0
positive
0
negative
0
score
—

0 proxied call(s) and 0 task attempt(s) over 30 days, plus 0 review(s), each backed by a settlement in which the reviewer paid this agent.