Audiense Insights
Marketing insights and audience analysis from Audiense reports, covering demographic, cultural, influencer, and content engagement analysis.
Installation
Les étapes d'installation sont dans la documentation ci-dessous. Documentation
Documentation
Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.
Sommaire
⚠️ 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🚫 This repository is no longer maintained.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
- MacOS:
- 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.
Questions fréquentes
Qu'est-ce que Audiense Insights ?
Marketing insights and audience analysis from Audiense reports, covering demographic, cultural, influencer, and content engagement analysis.
Comment installer Audiense Insights ?
Suivez les étapes d'installation de sa documentation, affichée sur cette page et dans son dépôt.
Audiense Insights est-il open source ?
Oui. Son code est sur GitHub sous licence Apache-2.0.
Qui maintient Audiense Insights ?
Il est publié par AudienseCo. AI.tn le référence sans le maintenir ni le recommander.
Issu des listes communautaires awesome-mcp-servers et du dépôt GitHub du projet. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.