Audiense Insights MCP server for AI agents

This MCP server enables Claude and other MCP-compatible clients to access your Audiense Insights account, providing marketing insights and audience analysis from Audiense reports, including demographic, cultural, influencer, and content engagement data.

Prerequisites

Before using the Audiense Insights MCP server, ensure you have:

Node.js (v18 or higher)
Claude Desktop App
Audiense Insights Account with API credentials
X/Twitter API Bearer Token (optional, for enriched influencer data)

Configuring Claude Desktop

Open the configuration file for Claude Desktop:

MacOS:

code ~/Library/Application\ Support/Claude/claude_desktop_config.json

Windows:

code %AppData%\Claude\claude_desktop_config.json

Add or update the following configuration:

"mcpServers": {
  "audiense-insights": {
    "command": "npx",
    "args": [
     "-y",
      "mcp-audiense-insights"
    ],
    "env": {
      "AUDIENSE_CLIENT_ID": "your_client_id_here",
      "AUDIENSE_CLIENT_SECRET": "your_client_secret_here",
      "TWITTER_BEARER_TOKEN": "your_token_here"
    }          
  }     
}

Save the file and restart Claude Desktop.

Available Tools

`get-reports`

Description: Retrieves the list of Audiense insights reports owned by the authenticated user.

Parameters: None
Response: List of reports in JSON format.

`get-report-info`

Description: Fetches detailed information about a specific intelligence report, including status, segmentation type, audience size, segments, and access links.

Parameters:
- report_id (string): The ID of the intelligence report.
Response:
- Full report details in JSON format.
- Status message if the report is still processing.

`get-audience-insights`

Description: Retrieves aggregated insights for a given audience, including demographics, behavioral traits, psychographics, and socioeconomic factors.

Parameters:
- audience_insights_id (string): The ID of the audience insights.
- insights (array of strings, optional): List of specific insight names to filter.
Response: Insights formatted as a structured text list.

`get-baselines`

Description: Retrieves available baseline audiences, optionally filtered by country.

Parameters:
- country (string, optional): ISO country code to filter by.
Response: List of baseline audiences in JSON format.

`get-categories`

Description: Retrieves the list of available affinity categories for influencer comparisons.

Parameters: None
Response: List of categories in JSON format.

`compare-audience-influencers`

Description: Compares influencers of a given audience with a baseline audience, providing affinity scores and uniqueness metrics.

Parameters:
- audience_influencers_id (string): ID of the audience influencers.
- baseline_audience_influencers_id (string): ID of the baseline audience influencers.
- cursor (number, optional): Pagination cursor.
- count (number, optional): Number of items per page (default: 200).
- bio_keyword (string, optional): Filter influencers by bio keyword.
- entity_type (enum: person | brand, optional): Filter by entity type.
- followers_min (number, optional): Minimum number of followers.
- followers_max (number, optional): Maximum number of followers.
- categories (array of strings, optional): Filter influencers by categories.
- countries (array of strings, optional): Filter influencers by country ISO codes.
Response: List of influencers with affinity scores, baseline comparison, and uniqueness scores.

`get-audience-content`

Description: Retrieves audience content engagement details, including liked content, shared content, and influential content.

Parameters:
- audience_content_id (string): The ID of the audience content.
Response: Content engagement data in JSON format.

`report-summary`

Description: Generates a comprehensive summary of an Audiense report, including metadata, audience size, segment information, top insights, and top influencers.

Parameters:
- report_id (string): The ID of the intelligence report to summarize.
Response: Complete report summary in JSON format with structured data.

Predefined Prompts

This server includes preconfigured prompts:

audiense-demo: Helps analyze Audiense reports interactively.
segment-matching: Matches and compares audience segments across Audiense reports.

Usage:

Accepts a reportName argument to find the most relevant report.
If an ID is provided, it searches by report ID instead.

Troubleshooting

Tools Not Appearing in Claude

Check Claude Desktop logs:
```
tail -f ~/Library/Logs/Claude/mcp*.log
```
Verify environment variables are set correctly.
Ensure the absolute path to index.js is correct.

Authentication Issues

Double-check OAuth credentials.
Ensure the refresh token is still valid.
Verify that the required API scopes are enabled.

Viewing Logs

To check server logs:

For MacOS/Linux:

tail -n 20 -f ~/Library/Logs/Claude/mcp*.log

For Windows:

Get-Content -Path "$env:AppData\Claude\Logs\mcp*.log" -Wait -Tail 20

How to install this MCP server

For Claude Code

To add this MCP server to Claude Code, run this command in your terminal:

claude mcp add-json "audiense-insights" '{"command":"npx","args":["-y","mcp-audiense-insights"],"env":{"AUDIENSE_CLIENT_ID":"your_client_id_here","AUDIENSE_CLIENT_SECRET":"your_client_secret_here","TWITTER_BEARER_TOKEN":"your_token_here"}}'

See the official Claude Code MCP documentation for more details.

For Cursor

There are two ways to add an MCP server to Cursor. The most common way is to add the server globally in the ~/.cursor/mcp.json file so that it is available in all of your projects.

If you only need the server in a single project, you can add it to the project instead by creating or adding it to the .cursor/mcp.json file.

Adding an MCP server to Cursor globally

To add a global MCP server go to Cursor Settings > Tools & Integrations and click "New MCP Server".

When you click that button the ~/.cursor/mcp.json file will be opened and you can add your server like this:

{
    "mcpServers": {
        "audiense-insights": {
            "command": "npx",
            "args": [
                "-y",
                "mcp-audiense-insights"
            ],
            "env": {
                "AUDIENSE_CLIENT_ID": "your_client_id_here",
                "AUDIENSE_CLIENT_SECRET": "your_client_secret_here",
                "TWITTER_BEARER_TOKEN": "your_token_here"
            }
        }
    }
}

Adding an MCP server to a project

To add an MCP server to a project you can create a new .cursor/mcp.json file or add it to the existing one. This will look exactly the same as the global MCP server example above.

How to use the MCP server

Once the server is installed, you might need to head back to Settings > MCP and click the refresh button.

The Cursor agent will then be able to see the available tools the added MCP server has available and will call them when it needs to.

You can also explicitly ask the agent to use the tool by mentioning the tool name and describing what the function does.

For Claude Desktop

To add this MCP server to Claude Desktop:

1. Find your configuration file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
Linux: ~/.config/Claude/claude_desktop_config.json

2. Add this to your configuration file:

{
    "mcpServers": {
        "audiense-insights": {
            "command": "npx",
            "args": [
                "-y",
                "mcp-audiense-insights"
            ],
            "env": {
                "AUDIENSE_CLIENT_ID": "your_client_id_here",
                "AUDIENSE_CLIENT_SECRET": "your_client_secret_here",
                "TWITTER_BEARER_TOKEN": "your_token_here"
            }
        }
    }
}

3. Restart Claude Desktop for the changes to take effect