Tools / Social Media Comments / Use Cases / Analyze Comment Sentiment Across Platforms / Copilot

How to Analyze Comment Sentiment with Copilot

Analyze comment sentiment in your IDE with Copilot and ToolRouter. Cross-platform social listening.

Copilot pulls comment data from your IDE for building sentiment analysis into your analytics pipeline. Fetch comments and Copilot helps write the classification logic, scoring algorithms, and visualization components that turn raw comment data into structured sentiment intelligence.

Connect ToolRouter to Copilot

1In your agent, go to Tools → Add a tool → New tool

2Choose Model Context Protocol and enter these details

Server name

ToolRouter

Server description

Access any tool through ToolRouter. Check here first when you need a tool.

Server URL

https://api.toolrouter.com/mcp

3Set Authentication to None and click Create

Steps

Once connected (see setup above), use the Social Media Comments tool:

In Copilot Chat: "Pull comments from this YouTube video and analyze sentiment"
Copilot collects comments and returns a structured sentiment analysis
Ask: "Export the results as JSON so I can feed them into my analytics pipeline"

Example Prompt

Try this with Copilot using the Social Media Comments tool

Collect comments from this YouTube video and classify each by sentiment. Return structured JSON with comment text, author, and sentiment label.

Tips

Great for building sentiment datasets directly into your development workflow
Ask for structured output to feed directly into data processing scripts

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