# mcp-sentiment

> mcp-sentiment — philip-walsh-mcp-sentiment. Use this tool when you need to analyze the sentiment of text data, such as customer reviews or social media posts, to determine the emotional tone and opinions expressed. It solves problems like understanding customer satisfaction, identifying areas for improvement, and monitoring brand reputation. The mcp-sentiment tool takes text inputs and outputs sentiment scores, providing valuable insights for informed decision-making.

Canonical page: https://skillsregistry.net/skills/philip-walsh-mcp-sentiment  
JSON: https://api.skillsregistry.net/v1/skills/philip-walsh-mcp-sentiment

## Description

MCP Server Sentiment Analysis 🤗

## Trust

- **Trust score (0–1):** 0.98
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/Philip-Walsh/mcp-sentiment)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "philip-walsh-mcp-sentiment"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/philip-walsh-mcp-sentiment` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/philip-walsh-mcp-sentiment/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt