Audiense Insights MCP Server

Audiense insights mcp server lets Claude, Cursor and other MCP clients work with Audiense Insights directly. Marketing insights and audience analysis from Audiense reports, covering demographic, cultural, influencer, and content engagement analysis.

What Audiense Insights does

This server, based on the Model Context Protocol (MCP), allows Claude or any other MCP-compatible client to interact with your Audiense Insights account. It extracts marketing insights and audience analysis from Audiense reports, covering demographic, cultural, influencer, and content engagement analysis.

Installing the audiense insights mcp server

Setup follows the standard MCP pattern: clone or install the server, then register it in your client's configuration file and restart the client. The configuration snippets on this page cover Claude Desktop, Claude Code and Cursor.

Configuration

Before the server will start you need to supply 3 environment variables: AUDIENSE_CLIENT_ID, AUDIENSE_CLIENT_SECRET, TWITTER_BEARER_TOKEN. Keep credentials in your client's env block or a secrets manager rather than committing them.

Where it fits

Developer-tool servers are usually the first ones people connect, because they turn "help me with this code" into an assistant that can actually read the repo and act on it. Audiense Insights sits in that group. Worth comparing against the other developer tools servers in this directory before you commit to one, since several overlap in scope but differ sharply in setup cost and permissions.

Practical notes

• This server runs locally, so it operates with whatever access your machine and its credentials already have. Scope that deliberately rather than by default.
• It will not start until its required credentials are present, so set those before wondering why the tools never appear.
• MCP clients ask for confirmation before each tool call by default. Keep that on while you learn what the audiense insights mcp server actually does with your data.
• Every entry in this directory is reviewed by hand before it goes live, and details are checked against the project's own documentation.