Query your customer feedback: studies, themes, suggestions, tags, and sentiment trends.
One address for any MCP client. You sign in once, after adding it.
At most: only reads or looks up information.
Odel charges nothing per call. The publisher may charge for its own service.
Odel could not list its tools without signing in.
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.