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trendforge-mcp

by flyflyloop
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trendforge-mcp

An MCP server for TrendForge — the YouTube gaming opportunity ranking.

Install it once and Claude Desktop, Cursor, or Codex can answer "what should I record?" by querying TrendForge's live ranking directly, without you leaving the chat.

What it exposes

Three read-only tools:

Tool

What it does

list_opportunities

Top games right now ranked by opportunity score (Demand / Supply / Timing).

get_game

One game's full breakdown + AI video ideas + related games.

check_topic

Live YouTube shelf check on any game/topic (heavier — use for serious ideas).

Scores: opportunity = 0.4·Demand + 0.35·Supply + 0.25·Timing, each 0–100, higher is better. See the full methodology.

Related MCP server: PeepTrend MCP Server

Install

Claude Desktop

Add to claude_desktop_config.json (Settings → Developer → Edit Config):

{
  "mcpServers": {
    "trendforge": {
      "command": "npx",
      "args": ["-y", "trendforge-mcp"]
    }
  }
}

Restart Claude Desktop. You'll see trendforge in the tools list.

Cursor

Add to .cursor/mcp.json (project) or global MCP settings:

{
  "mcpServers": {
    "trendforge": {
      "command": "npx",
      "args": ["-y", "trendforge-mcp"]
    }
  }
}

Codex (codex CLI)

Add to ~/.codex/config.toml:

[mcp_servers.trendforge]
command = "npx"
args = ["-y", "trendforge-mcp"]

Configuration

Env var

Default

Purpose

TRENDFORGE_HOST

https://trendforgeapp.com

Override the TrendForge host (e.g. for a staging build).

Example with a custom host:

{
  "mcpServers": {
    "trendforge": {
      "command": "npx",
      "args": ["-y", "trendforge-mcp"],
      "env": { "TRENDFORGE_HOST": "https://staging.example" }
    }
  }
}

Try it

Once connected, ask your assistant things like:

  • "What are the top 10 YouTube gaming opportunities right now for a small channel?"

  • "Give me video ideas for Palworld."

  • "Check whether a Hades 2 beginner guide is worth making — I have under 1K subs."

Local development

npm install
npm run build
node bin/trendforge-mcp.js   # speaks MCP over stdio

Notes

  • All data is read-only and computed from public Steam, YouTube Data API, and Google Trends signals.

  • check_topic hits the YouTube API and is rate-limited server-side, same as the free web checker.

  • Not affiliated with Valve, Google, or YouTube.

Available Tools

3 tools
check_topicA

Run a live YouTube shelf check on any game, topic, or query: returns opportunity verdict, demand, competition pressure, big-channel dominance, Shorts mix, exact-title collisions, fit for a channel size, suggested angles, and the top recent videos returned. Heavier call (hits YouTube API) — use for a specific idea the creator is seriously considering, not for browsing.

ParametersJSON Schema
NameRequiredDescriptionDefault
qYesGame name, niche, or YouTube query, e.g. 'Hades 2 beginner guide'.
timeframeNo7d
channelTierNoCreator's channel size for the fit signal. Omit to skip fit.

TDQS

A4/5.0
Behavior3/5

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

There are no annotations, so the description carries the full burden. It does disclose a key behavioral trait: 'Heavier call (hits YouTube API)' and 'live', indicating real-time cost/latency. However, it omits details like auth requirements, rate limits, or error behavior, so the disclosure remains incomplete.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

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

The description is two sentences with no wasted words. It front-loads the core action, lists the outputs in a compact enumeration, and then adds the cost/usage disclaimer in a subordinate clause. Every part earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, but the description enumerates the key return fields: opportunity verdict, demand, competition pressure, Shorts mix, collisions, fit, suggested angles, and top recent videos. It also covers the heavier cost context. It could be enhanced with an example response or format, but the current detail is sufficient for a 3-parameter 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?

Schema coverage is 67%, with q and channelTier having descriptions and timeframe having an enum. The description adds little beyond the schema, except connecting 'fit for a channel size' to channelTier and giving a broad context for q. The parameter meanings are mostly clear from the schema itself.

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 and resource: 'Run a live YouTube shelf check on any game, topic, or query.' It also distinguishes this tool from browsing-oriented tools by stating it is for a specific idea the creator is seriously considering, not for browsing.

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 explicitly says when to use the tool ('for a specific idea the creator is seriously considering') and when not to use it ('not for browsing'). It also mentions the heavier cost as a reason for this guidance, but does not name sibling tools as alternatives.

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

get_gameA

Get the full breakdown for one game: Demand/Supply/Timing scores, confidence, risk flags, a one-line reason it ranks, AI-generated video ideas (title + angle + why-now), and 3 related games. Needs a slug — get it from list_opportunities first, or pass a slug you know.

ParametersJSON Schema
NameRequiredDescriptionDefault
slugYesGame slug, e.g. 'palworld'.

TDQS

A4.5/5.0
Behavior4/5

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

No annotations provided, so the description carries full burden. It lists exact output fields and notes the input requirement. There are no hidden side effects or unstated behaviors; as a read operation, this is sufficiently transparent.

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, information-dense, and front-loaded. Every sentence earns its place: the first lists the output components, the second provides input acquisition guidance. No fluff.

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?

The tool returns a complex breakdown, and the description enumerates all components, so the agent knows what to expect despite no output schema. The single parameter is fully contextualized with usage guidance. This is complete for one-parameter tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema already defines slug with example, but description adds meaning by explaining where to get the slug ('from list_opportunities first') and that a known slug can also be passed. This goes beyond the schema's basic description.

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?

Specific verb 'Get' + resource 'full breakdown for one game' with enumerated components (scores, confidence, risk flags, reason, video ideas, related games). Clearly distinguishes from siblings by indicating it is per-game and requires a slug, contrasting with list_opportunities.

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?

Provides explicit instruction to obtain slug from list_opportunities first, which implies the typical workflow and alternative. Lacks explicit 'when not to use' but the context is clear enough for an agent to select appropriately.

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

list_opportunitiesA

List the top YouTube gaming opportunities right now, ranked by TrendForge's opportunity score (0.4Demand + 0.35Supply + 0.25*Timing, each 0-100, higher = better). Use this when a creator asks what to play/record, or which games have an open content gap. Higher opportunity = demand is real but creator supply is still thin.

ParametersJSON Schema
NameRequiredDescriptionDefault
qNoOptional name/tag filter, e.g. 'horror' or 'co-op'.
limitNoNumber of games to return (1-50, default 15).

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals the ranking formula (0.4*Demand + 0.35*Supply + 0.25*Timing) and interprets what 'higher opportunity' means, which is valuable contextual behavior. It does not mention output format or pagination, but for a read-only list tool this is acceptable.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

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

The description is two sentences, front-loaded with the main purpose, and every clause earns its place. The formula is concise and adds informational value without verbosity.

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 list tool with no output schema and two optional parameters, the description covers purpose, use case, ranking behavior, and interpretation of results. It is sufficiently complete for an agent to select and invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so baseline is 3. The description adds context around the ranking system but does not elaborate on parameter-specific meanings beyond the schema. The formula indirectly clarifies why 'limit' matters, but that is marginal.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool lists 'top YouTube gaming opportunities' with a specific ranking methodology. The verb 'list' and resource 'opportunities' are precise, and the scope (YouTube gaming, ranked by opportunity score) distinguishes it from siblings like get_game or check_topic.

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 explicitly says to use it 'when a creator asks what to play/record, or which games have an open content gap.' This gives strong usage context, though it does not name alternative tools or explicitly state when not to use it.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 3 tool updatesv0.1.2
    • First observedcheck_topic
    • First observedget_game
    • First observedlist_opportunities
Install Server
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TDQS

A4.4/5.0
Disambiguation5/5

Each tool serves a distinct purpose: list_opportunities for browsing ranked opportunities, get_game for deep-diving into a specific game, and check_topic for live YouTube checks on arbitrary queries. No overlap in functionality, making tool selection unambiguous.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern (list_, get_, check_), using lowercase with underscores. The naming convention is uniform and intuitive, matching the action each tool performs.

Tool Count5/5

The server has 3 tools, which is well-scoped for its niche purpose of YouTube gaming opportunity analysis. Each tool is essential and earns its place, covering browsing, detail retrieval, and live validation without redundancy.

Completeness5/5

The tool surface fully covers the domain's needs: list_opportunities provides the overview, get_game offers granular data for one game, and check_topic enables ad-hoc validation of any idea. No obvious gaps exist for a read-only analytics service.

Maintenance

ActivitySlowing
ResponsivenessSyncing

Resources

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