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trendsmcp-ai

news-sentiment-mcp

news-sentiment-mcp

News Sentiment MCP Works with Claude Works with Cursor

AI向けニュースの感情分析とボリュームデータ ニュースが特定のトピックをどのように取り上げているか、その報道が肯定的か否定的かを把握できます。感情スコア、メディアボリュームのトレンド、過去のカバレッジデータをAI分析向けに構造化して提供します。

完全なドキュメントとライブデモ: https://trendsmcp.ai/news-sentiment-data

Trends MCP の一部 - 12以上のソースからライブトレンドデータを提供するMCPサーバーです。 メインリポジトリ: https://github.com/trendsmcp/trends-mcp


2ステップで始める

ステップ1: trendsmcp.ai で無料のAPIキーを取得 1日100リクエスト、クレジットカード不要。

ステップ2: AIクライアントに追加(YOUR_API_KEY を置き換えてください):

+ Cursorに追加(ワンクリック)

Cursor / Windsurf / Cline   (~/.cursor/mcp.json または同等のファイル)

{
  "mcpServers": {
    "trends-mcp": {
      "url": "https://api.trendsmcp.ai/mcp",
      "transport": "http",
      "headers": { "Authorization": "Bearer YOUR_API_KEY" }
    }
  }
}

VS Code / GitHub Copilot   (.vscode/mcp.json)

{
  "servers": {
    "trends-mcp": {
      "type": "http",
      "url": "https://api.trendsmcp.ai/mcp",
      "headers": { "Authorization": "Bearer YOUR_API_KEY" }
    }
  }
}

Claude Desktop   (claude_desktop_config.json) ユーザー → 設定 → デベロッパー → 設定を編集 — mcpServers内に追加

{
  "mcpServers": {
    "trends-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://api.trendsmcp.ai/mcp",
        "--header",
        "Authorization:${AUTH_HEADER}"
      ],
      "env": {
        "AUTH_HEADER": "Bearer YOUR_API_KEY"
      }
    }
  }
}

Claude.ai(ブラウザ)   設定 → コネクタ → カスタムコネクタを追加:

https://api.trendsmcp.ai/mcp

Related MCP server: news-volume-mcp

クエリ例

接続後、AIに次のように質問してください:

get_growth(keyword='tesla', source='news sentiment, news volume', percent_growth=['3M'])

利用可能なツール

ツール

機能

get_trends

このソースにおけるキーワードの時系列データ

get_growth

1週間、1ヶ月、3ヶ月、6ヶ月、1年間の成長率

get_top_trends

このソースで現在トレンドのトピック

get_ranked_trends

ボリューム順にランク付けされたトップトピック


FAQ

2つのシグナルを提供します:ニュースボリューム(トピックがどれだけ報道されているか)とニュース感情(その報道が肯定的、中立的、否定的のいずれに偏っているか)。両方とも正規化され、時系列として返されます。

感情スコアはどのように計算されますか?

感情はニュース記事の見出しと要約のNLP分析から導出され、-1(非常に否定的)から+1(非常に肯定的)のスケールでスコア化されます。Trends MCPはこれを一貫性のために0〜100のスケールに正規化します。

決算期における企業の感情を追跡できますか?

はい。企業名やティッカーをクエリすると、感情時系列から決算発表、製品発売、規制イベントの前後でメディアのトーンがどのように変化したかがわかります。

どのニュースソースが含まれていますか?

主要な英語ニュースメディア、金融メディア、テクノロジー系出版物が含まれます。個別のメディアを追跡するのではなく、複数のソースを集約したシグナルを提供します。


全データソース

Trends MCPは1つの接続で12以上のソースをカバー: Google検索、YouTube、TikTok、Reddit、Amazon、Wikipedia、 ニュース感情、Webトラフィック、アプリダウンロード、Steam、npmなど。

すべてを閲覧: https://trendsmcp.ai/data-sources


Pythonクライアントとしても利用可能

同じAPIキーがPythonでも直接使用可能 - MCPホストは不要です。

pip install news-sentiment-mcp
import os
from news_sentiment_mcp import TrendsMcpClient, SOURCE

client = TrendsMcpClient(api_key=os.environ["TRENDSMCP_API_KEY"])

series  = client.get_trends(source=SOURCE, keyword="your keyword")
growth  = client.get_growth(source=SOURCE, keyword="your keyword", percent_growth=["1M", "3M", "12M"])
top     = client.get_top_trends(type="News Sentiment", limit=10)

Python完全ドキュメント: trendsmcp.ai/docs

ライセンス

MIT © Trends MCP

Available Tools

3 tools
get_growthA
Read-onlyIdempotent
Inspect

Point-to-point growth for a keyword on one or more sources. Each window is a preset string (12M, 3M, YTD, and the other listed periods). Values are on a 0-100 scale, plus absolute volume when available. Prefer this over get_time_series for growth questions. app downloads and app rankings are keyword sources (Android bundle ID). They are not the App Store / Google Play live boards on get_top_trends. If the request is rate limited or the monthly quota is used up, tell the user their plan limit is reached.

ParametersJSON Schema
NameRequiredDescriptionDefault
sourceYesOne source, or comma-separated sources (e.g. 'amazon, tiktok, youtube'). Valid: 'google search', 'google images', 'google news', 'google shopping', 'youtube', 'wikipedia', 'tiktok', 'reddit', 'amazon', 'news sentiment', 'news volume', 'npm', 'python', 'steam', 'app downloads', 'app rankings'.
keywordYesWhat to look up. The string format is required by source. Standard sources (google search, google images, google news, google shopping, youtube, wikipedia, tiktok, reddit, amazon, news sentiment, news volume): any name or phrase, e.g. 'nike'. npm: exact npmjs.com package name, case-sensitive. Right: 'react', '@babel/core'. Wrong: 'React', 'React.js'. python: exact PyPI project name. Right: 'pandas', 'requests'. Wrong: 'Pandas'. steam: game display name in plain English, not a Steam App ID. Right: 'Elden Ring', 'CS2'. First Steam store search result wins, so use an unambiguous name. app downloads and app rankings: Android bundle ID only (the id= value on Google Play). Right: 'com.openai.chatgpt', 'com.whatsapp'. Wrong: 'ChatGPT', 'WhatsApp', an iOS App Store ID, or a bundle ID that is not Android. Find it at play.google.com/store/apps/details?id=THIS_PART. If the request includes app downloads or app rankings with other sources, keyword must still be the Android bundle ID.
percent_growthNoGrowth windows. Default if omitted: ['12M']. Each item must be a preset string: '7D', '1W', '14D', '2W', '30D', '1M', '2M', '3M', '6M', '9M', '12M', '1Y', '18M', '24M', '2Y', '36M', '3Y', '48M', '4Y', '60M', '5Y', 'MTD', 'QTD', 'YTD'. Every preset is a two-date comparison.

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the readOnlyHint, openWorldHint, and idempotentHint annotations, the description adds useful behavioral context: values are on a 0-100 scale with absolute volume when available, and the agent should tell the user their plan limit is reached on rate limiting or quota exhaustion. These details are not present in the structured fields and do not contradict the 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 compact and every sentence earns its place: core operation, output scale, sibling preference, app-source caveat, and rate-limit handling. It front-loads the primary purpose and avoids redundant phrasing.

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 a detailed input schema, an output schema, and safety annotations, the description fills the remaining gaps: tool selection, output scale, source disambiguation, and error behavior. It is complete enough for an agent to invoke the tool correctly without further inference.

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 documents all parameters thoroughly, including valid sources, keyword formatting rules per source, and every preset growth window. The description references preset windows and Android bundle IDs but does not add meaning beyond the schema, so a baseline of 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 opens with a specific action and resource: 'Point-to-point growth for a keyword on one or more sources.' It also names sibling tools to disambiguate itself, stating it is preferred over get_time_series for growth questions and clarifying that app sources are not the live boards on get_top_trends.

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?

It gives an explicit selection rule: 'Prefer this over get_time_series for growth questions.' It also warns against confusing app downloads/app rankings with get_top_trends live boards, and specifies how to handle rate limits or quota exhaustion. This gives the agent clear when-to-use and when-not-to-use guidance.

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

get_time_seriesA
Read-onlyIdempotent
Inspect

Full historical series for one keyword and one source (0-100 values, plus volume when available). Use for charting or custom math. Not for live 'what's trending now' boards (use get_top_trends). For most growth questions, use get_growth. If the request is rate limited or the monthly quota is used up, tell the user their plan limit is reached.

ParametersJSON Schema
NameRequiredDescriptionDefault
sourceYesExactly one source per request. Valid: 'google search', 'google images', 'google news', 'google shopping', 'youtube', 'wikipedia', 'tiktok', 'reddit', 'amazon', 'news sentiment', 'news volume', 'npm', 'python', 'steam', 'app downloads', 'app rankings'.
keywordYesWhat to look up. The string format is required by source. Standard sources (google search, google images, google news, google shopping, youtube, wikipedia, tiktok, reddit, amazon, news sentiment, news volume): any name or phrase, e.g. 'tesla'. npm: exact npmjs.com package name, case-sensitive. Right: 'react', '@babel/core'. Wrong: 'React', 'React.js'. python: exact PyPI project name. Right: 'pandas', 'requests'. Wrong: 'Pandas'. steam: game display name in plain English, not a Steam App ID. Right: 'Elden Ring', 'CS2'. First Steam store search result wins, so use an unambiguous name. app downloads and app rankings: Android bundle ID only (the id= value on Google Play). Right: 'com.openai.chatgpt', 'com.whatsapp'. Wrong: 'ChatGPT', 'WhatsApp', an iOS App Store ID, or a bundle ID that is not Android. Find it at play.google.com/store/apps/details?id=THIS_PART.

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already cover readOnlyHint and idempotentHint. The description adds behavioral context beyond those hints: the 0-100 value range, volume availability, and rate-limit/quota handling instructions. This provides useful operational detail that annotations do not convey, though the core safety profile is already covered by hints.

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, each earning its place: purpose and scope, usage routing, and error handling. Front-loaded with the core purpose; no repetition or fluff. The alternative tool routing is included efficiently.

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 a two-parameter tool with a full output schema, the description covers purpose, usage scenarios, alternatives, and error handling. An agent has all necessary information to decide when to call it and what to expect, with no critical gaps.

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% and both parameters have detailed, source-specific descriptions (e.g., keyword format per source, valid source list). The tool description adds no additional parameter meaning beyond restating 'one keyword and one source', so the baseline for full schema coverage applies.

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 explicitly states it returns 'Full historical series for one keyword and one source' with a value range and volume detail. It distinguishes itself from siblings get_top_trends and get_growth by stating what it is not for (live trending, growth questions), making the tool's purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Directly states when to use it: 'Use for charting or custom math' and when not to: 'Not for live trending (use get_top_trends)' and 'For most growth questions, use get_growth'. Also provides explicit handling for rate-limited or quota-exhausted requests, which is actionable guidance.

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.

  1. 3 tool updatesv0.1.0
    • First observedget_growth
    • First observedget_time_series
    • First observedget_top_trends

TDQS

A4.3/5.0

Scored across 3 tools

Disambiguation4/5

The three tools are mostly distinct: get_growth answers point-to-point growth questions, get_time_series provides full historical data, and get_top_trends handles live boards. Descriptions explicitly steer usage away from confusion, though get_growth and get_time_series do overlap somewhat for the same keyword/source data.

Naming Consistency5/5

All tools follow the same get_ prefix and describe their primary output with a clear noun: growth, time_series, top_trends. This is predictable and easy to navigate.

Tool Count3/5

Three tools is on the low end of the acceptable range and feels slightly thin for what the server name implies. It is a reasonable number for a narrow trends/growth API, but the mismatch with 'news-sentiment' makes the scope feel underbuilt.

Completeness2/5

Despite the server name including 'sentiment', there is no tool for sentiment analysis, news article retrieval, or sentiment scoring. The current surface only covers growth, historical series, and trending boards, leaving major expected functionality absent.

Maintenance

ActivitySlowing
ResponsivenessNo issues

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