mcp audiense insights

Cos'è il Server MCP di Audiense Insights?

Il Server MCP di Audiense Insights è un potente server progettato sulla base del Protocollo di Contesto del Modello (MCP). Consente un'interazione fluida tra Claude e altri client compatibili con MCP con il tuo account Audiense Insights. Questa integrazione permette agli utenti di sfruttare appieno le capacità di analisi dei dati di Audiense, migliorando le loro strategie di marketing e il coinvolgimento del pubblico.

Caratteristiche del Server MCP di Audiense Insights

• Compatibilità MCP: Il server è costruito per funzionare con qualsiasi client compatibile con MCP, garantendo flessibilità e ampia usabilità.
• Integrazione dei Dati: Consente l'integrazione di varie fonti di dati, abilitando approfondimenti completi sul pubblico.
• Interfaccia Intuitiva: Il server fornisce un'interfaccia intuitiva che semplifica il processo di interazione per gli utenti.
• Analisi in Tempo Reale: Gli utenti possono accedere ad analisi dei dati in tempo reale, aiutandoli a prendere decisioni informate rapidamente.
• Scalabilità: Progettato per crescere con le tue esigenze, il server può gestire un aumento della quantità di dati e utenti senza compromettere le prestazioni.

Come Utilizzare il Server MCP di Audiense Insights

1. Configura il Tuo Account: Inizia creando un account sulla piattaforma Audiense.
2. Collega il Tuo Client Compatibile con MCP: Collega il tuo client compatibile con MCP preferito al Server MCP di Audiense Insights.
3. Configura le Fonti di Dati: Integra le tue fonti di dati per iniziare a raccogliere approfondimenti.
4. Analizza i Dati: Utilizza gli strumenti di analisi del server per interpretare i dati e generare report.
5. Implementa gli Approfondimenti: Usa gli approfondimenti ottenuti per affinare le tue strategie di marketing e migliorare il coinvolgimento del pubblico.

Domande Frequenti

D1: Cos'è il Protocollo di Contesto del Modello (MCP)?

R1: Il Protocollo di Contesto del Modello (MCP) è un protocollo di comunicazione che consente a diversi sistemi di interagire e condividere dati in modo fluido.

D2: Posso utilizzare il Server MCP di Audiense Insights con qualsiasi client?

R2: Sì, purché il client sia compatibile con MCP, puoi integrarlo con il Server MCP di Audiense Insights.

D3: C'è un costo associato all'utilizzo del Server MCP di Audiense Insights?

R3: Audiense offre vari piani tariffari. È meglio controllare il loro sito ufficiale per le informazioni sui prezzi più aggiornate.

D4: Come posso ottenere supporto per il Server MCP di Audiense Insights?

R4: Il supporto può essere accessibile attraverso il sito di Audiense, dove puoi trovare documentazione, FAQ e opzioni di contatto per il servizio clienti.

D5: I miei dati sono sicuri con il Server MCP di Audiense Insights?

R5: Sì, Audiense prende sul serio la sicurezza dei dati e implementa varie misure per proteggere i dati degli utenti.

Per ulteriori informazioni, visita il sito ufficiale di Audiense.

⚠️ 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

1. 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
     

2. 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"
       }          
     }     
   }
   
   

3. 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

1. Check Claude Desktop logs:

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

2. Verify environment variables are set correctly.
3. 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.