Audiense Insights

What is Audiense Insights MCP Server?

The Audiense Insights MCP Server is a tool that connects to the Audiense Insights platform, allowing AI agents to access and analyze marketing insights and audience data. It provides tools to retrieve reports, get audience demographics, and analyze cultural and content engagement.

How to use the project?

To use the server, you need an Audiense Insights account with API credentials. The server is configured by setting environment variables for your Audiense client ID and secret. It can then be run and connected to an MCP client like Claude Desktop.

Key Features

Audience Analysis: Get detailed insights into audience demographics, interests, and online behavior.
Report Retrieval: Access and analyze your Audiense Insights reports programmatically.
Influencer Analysis: Identify and analyze key influencers within a specific audience.
Content Engagement: Understand what content resonates with your target audience.

Use Cases

AI-Powered Market Research: Use AI agents to conduct in-depth market research and audience analysis.
Content Strategy Development: Inform your content strategy by understanding what your audience is interested in and engaging with.
Influencer Marketing: Identify relevant influencers for your brand and analyze their audience to ensure a good fit.
Competitive Analysis: Analyze the audiences of your competitors to identify opportunities and threats.

FAQ

Q: What is Audiense Insights? A: Audiense Insights is a marketing platform that provides rich insights into audiences, helping businesses to understand and connect with their target customers.

Q: Is this repository still maintained? A: No, this repository is deprecated. The Audiense Insights MCP has been migrated to a remote model. For more information, you should contact Audiense support.

Q: What do I need to use the server? A: You need a Node.js environment (v18+), an Audiense Insights account with API credentials, and an MCP-compatible client.

⚠️ Deprecated

🚫 This repository is no longer maintained.

The Audiense Insights MCP has been migrated to a remote model. For more information on how to use the new remote MCP, please reach us at support@audiense.com.

🏆 Audiense Insights MCP Server

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.

🚀 Prerequisites

Before using this 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
Access links
Parameters:
- report_id (string): The ID of the intelligence report.
Response:
- Full report details in JSON format.
- If the report is still processing, returns a message indicating the pending status.

📌 `get-audience-insights`

Description: Retrieves aggregated insights for a given audience, including:

Demographics: Gender, age, country.
Behavioral traits: Active hours, platform usage.
Psychographics: Personality traits, interests.
Socioeconomic factors: Income, education status.
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 that can be used in 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. The baseline is determined as follows:

If a single country represents more than 50% of the audience, that country is used as the baseline.
Otherwise, the global baseline is used.
If a specific segment is selected, the full audience is used as the baseline.

Each influencer comparison includes:

Affinity (%) – How well the influencer aligns with the audience.
Baseline Affinity (%) – The influencer’s affinity within the baseline audience.
Uniqueness Score – How distinct the influencer is compared to the baseline.
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 in JSON format.

📌 `get-audience-content`

Description: Retrieves audience content engagement details, including:

Liked Content: Most popular posts, domains, emojis, hashtags, links, media, and a word cloud.
Shared Content: Most shared content categorized similarly.
Influential Content: Content from influential accounts.

Each category contains:

popularPost: Most engaged posts.
topDomains: Most mentioned domains.
topEmojis: Most used emojis.
topHashtags: Most used hashtags.
topLinks: Most shared links.
topMedia: Shared media.
wordcloud: Most frequently used words.
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:

Report metadata (title, segmentation type)
Full audience size
Detailed segment information
Top insights for each segment (bio keywords, demographics, interests)
Top influencers for each segment with comparison metrics
Parameters:
- report_id (string): The ID of the intelligence report to summarize.
Response:
- Complete report summary in JSON format with structured data for each segment
- For pending reports: Status message indicating the report is still processing
- For reports without segments: Message indicating there are no segments to analyze

💡 Predefined Prompts

This server includes a preconfigured prompts

audiense-demo: Helps analyze Audiense reports interactively.
segment-matching: A prompt to match and compare audience segments across Audiense reports, identifying similarities, unique traits, and key insights based on demographics, interests, influencers, and engagement patterns.

Usage:

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

Use case: Structured guidance for audience analysis.

🛠️ 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

🔐 Security Considerations

Keep API credentials secure – never expose them in public repositories.
Use environment variables to manage sensitive data.

📄 License

This project is licensed under the Apache 2.0 License. See the LICENSE file for more details.