Sentiment Analyzer — Emotions, Confidence & Key Phrases

Text sentiment analysis API for AI agents.

CommunityOnlineNo sign-inGlobalFreeRead-only

What it can do

  • Text Analyze Sentiment: Use this when you need to determine the emotional tone and sentiment of text. Returns structured sentiment analysis with emotion breakdown and key drivers. 1. sentiment: overal
  • Text Analyze Sentiment Batch: Use this when you need to analyze sentiment of multiple texts at once (up to 20). Returns an array of individual sentiment results in one call. 1. results: array of senti

What data it sees

Do you need an account

No: the server works without sign-in

Text sentiment analysis API for AI agents. Analyze sentiment (positive/negative/neutral) with confidence score, emotion detection (joy, anger, fear, surprise, sadness), and key phrase extraction. Single and batch modes.

Tools: text_analyze_sentiment (single), text_analyze_sentiment_batch (multiple texts).

Use this for social media monitoring, review analysis, brand sentiment tracking, or content moderation. IMPORTANT: For content topic classification, use text_classify_content instead.

Returns: {sentiment, confidence, emotions[], keyPhrases[]}. No API key required — x402 micropayment $0.005/call on Base L2.

How to connect

How to connect Sentiment Analyzer — Emotions, Confidence & Key Phrases to Claude

The server address to paste into Claude settings:

https://sentiment-analyzer--axel-belfort.run.tools

  1. Open Claude (claude.ai or the desktop app).
  2. Go to Settings → Connectors.
  3. Click Add custom connector.
  4. Paste the server address copied below into Remote MCP server URL and click Add.
  5. In a chat, click + → Connectors and switch the new connector on.

Custom connectors are available on Free, Pro, Max, Team and Enterprise plans (Free is limited to one). On Team and Enterprise an organization Owner adds the connector first under Organization settings → Connectors.

Authorization

After you click Add, a sign-in window for the service opens. Sign in with your own account and approve access. Claude never sees your password.

How to connect Sentiment Analyzer — Emotions, Confidence & Key Phrases to ChatGPT

The server address to paste into ChatGPT settings:

https://sentiment-analyzer--axel-belfort.run.tools

  1. Open ChatGPT in a browser (chatgpt.com). A Plus, Pro, Business, Enterprise or Edu plan is required.
  2. Turn on developer mode once: Settings → Apps → Advanced settings → Developer mode.
  3. Open Settings → Connectors and click Create.
  4. Fill in the form: Name (anything), Description (one line about what the service does), MCP server URL (copy it below).
  5. Under Authentication choose OAuth if the service requires sign-in, otherwise None. Click Create.
  6. In a new chat open + → Apps/Connectors and enable the connector.

OpenAI has renamed this section before (Connectors → Apps/Plugins). If the label differs, search settings for "developer mode". On Business/Enterprise workspaces an admin must allow custom connectors first.

Authorization

On first use ChatGPT opens the service's sign-in window. Sign in and approve access.

How to connect Sentiment Analyzer — Emotions, Confidence & Key Phrases to Cursor

The server address to paste into Cursor settings:

https://sentiment-analyzer--axel-belfort.run.tools

Fastest: click Open in Cursor below and confirm the prompt.

Manually:

  1. In Cursor open Settings → Cursor Settings → MCP and click Add new global MCP server.
  2. Paste the JSON copied below into ~/.cursor/mcp.json (per project: .cursor/mcp.json in the repo root).
  3. Save the file. The server appears in the MCP list; authorize it there if asked.

Authorization

If the service needs sign-in, an authorize button appears next to the server in the MCP list.

Server tool list (2)

Raw names from tools/list. Only developers need these.

text_analyze_sentimentUse this when you need to determine the emotional tone and sentiment of text. Returns structured sentiment analysis with emotion breakdown and key drivers. 1. sentiment: overall sentiment label (posi
text_analyze_sentiment_batchUse this when you need to analyze sentiment of multiple texts at once (up to 20). Returns an array of individual sentiment results in one call. 1. results: array of sentiment objects, one per input t