Query your customer feedback: studies, themes, suggestions, tags, and sentiment trends.
Connect any MCP client to your Magic Insights workspace and chat with your customer-feedback studies — list studies, search and filter feedback, and read AI-generated themes, topics, suggestions, tags, and sentiment trends.
This is a remote, hosted MCP server. There's nothing to install — point your client at the URL below and authenticate with a workspace API key.
https://app.magicinsights.ai/api/mcpai.magicinsights/insightsCreate one in the app at Settings → API keys (https://app.magicinsights.ai → your workspace → Settings → API keys), then send it as the Authorization: Bearer <key> header.
claude mcp add --transport http magic-insights https://app.magicinsights.ai/api/mcp \
--header "Authorization: Bearer YOUR_API_KEY"
Add to ~/.cursor/mcp.json (all projects) or .cursor/mcp.json (one project), then enable the server in Cursor settings:
{
"mcpServers": {
"magic-insights": {
"url": "https://app.magicinsights.ai/api/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_KEY"
}
}
}
}
Most clients use the same mcpServers block above — check your client's docs for where its config file lives. The Claude API MCP connector accepts the same URL with an authorization_token.
All tools are read-only and scoped to the workspace that owns the API key.
| Tool | What it does |
|---|---|
get_workspace | One-call overview: plan, study count, connected platforms, tags, total feedback, date range, overall sentiment. |
list_studies | List all studies with description and date range. |
get_study | A study's summary, generated report, and top themes (with sentiment, ids, and example feedback). |
list_topics | A study's topics and the themes grouped under each. |
get_theme_feedback | All feedback under one theme, most relevant first. |
list_suggestions | A study's AI-synthesized recommended actions (problem, solution, priority). |
get_suggestion_feedback | The individual feedback behind a single suggestion. |
search_feedback | Search and filter feedback by keyword, sentiment, platform, tag, or date range. |
get_feedback | One feedback item in full — content, translation, AI summary, and source metadata. |
get_stats | Aggregate stats: total count, sentiment breakdown, date range. |
get_trends | Feedback volume and sentiment over time, bucketed by week or month. |
list_tags | The workspace's custom tags and how many items carry each. |
list_platforms | The source platforms feeding the workspace, each with its feedback count. |
Magic Insights is an AI-driven customer-feedback analytics platform. Learn more at magicinsights.ai.
The server's metadata is published in the official MCP registry; this repository hosts the public server.json and connection docs. The application source is closed.
This listing does not have a supported local package template. Use the maintainer’s documentation for its hosted endpoint, authentication, and client-specific setup. No install command has been inferred.