Audiense Insights MCP Server

What is Audiense Insights MCP Server about?

Enables Claude and any MCP‑compatible client to retrieve and interact with Audiense Insights reports, delivering marketing‑focused audience analytics such as demographics, psychographics, influencer comparisons, and content engagement.

How to use Audiense Insights MCP Server?

Install Node.js v18+.
Configure Claude Desktop (or any MCP client) with an entry under mcpServers pointing to the package mcp-audiense-insights using npx.
Set required environment variables (AUDIENSE_CLIENT_ID, AUDIENSE_CLIENT_SECRET, optional TWITTER_BEARER_TOKEN).
Restart Claude Desktop; the server will appear as the audiense‑insights MCP server.
Invoke the provided tools (get-reports, get-audience-insights, compare-audience-influencers, etc.) through the client to fetch data or generate summaries.

Key Features

Report discovery – get-reports lists all intelligence reports for the authenticated user.
Detailed report info – get-report-info returns status, segmentation, audience size, and access links.
Aggregated audience insights – demographics, behavioral traits, psychographics, socioeconomic factors.
Baseline audiences – retrieve country‑specific or global baselines for influencer comparison.
Influencer comparison – affinity, baseline affinity, uniqueness scores with extensive filtering options.
Content engagement analytics – top liked/shared content, domains, emojis, hashtags, media, and word clouds.
Full report summarization – report-summary compiles metadata, segment details, top insights, and influencer metrics into a structured JSON.
Predefined prompts – audiense-demo and segment-matching for interactive analysis workflows.

Use Cases

Marketing teams extracting audience demographics and interests to tailor campaigns.
Social media strategists comparing influencer affinity against baseline audiences to identify high‑impact partners.
Content creators analyzing what types of posts, domains, or hashtags resonate most with a target segment.
Research analysts generating automated summaries of multiple Audiense reports for quick stakeholder briefings.
Customer success teams troubleshooting account performance by drilling into segment‑level insights.

FAQ

Do I need a Twitter token? It is optional and only needed for enriched influencer data.
What happens if a report is still processing? get-report-info and report-summary will return a status message indicating the report is pending.
Can I filter influencers by follower count? Yes, using followers_min and followers_max parameters in compare-audience-influencers.
Where are the logs stored? On macOS/Linux: ~/Library/Logs/Claude/mcp*.log; on Windows: %AppData%\Claude\Logs\mcp*.log.
Is the project still maintained? The repository is deprecated; the service has been migrated to a remote model. Contact support@audiense.com for the new endpoint.

⚠️ 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.