mcp audiense insights

Audiense Insights MCP 伺服器是什麼？

Audiense Insights MCP 伺服器是一個強大的伺服器，基於模型上下文協議（MCP）設計。它使 Claude 與其他兼容 MCP 的客戶端之間能夠無縫互動，並與您的 Audiense Insights 帳戶連接。這種整合使得用戶能夠充分利用 Audiense 的數據分析能力，提升其行銷策略和受眾參與度。

Audiense Insights MCP 伺服器的特點

• MCP 兼容性：該伺服器旨在與任何兼容 MCP 的客戶端一起使用，確保靈活性和廣泛的可用性。
• 數據整合：它允許整合各種數據來源，提供全面的受眾洞察。
• 用戶友好的介面：伺服器提供直觀的介面，簡化用戶的互動過程。
• 實時分析：用戶可以訪問實時數據分析，幫助他們快速做出明智的決策。
• 可擴展性：該伺服器設計為隨著您的需求增長而增長，能夠處理不斷增加的數據和用戶，而不影響性能。

如何使用 Audiense Insights MCP 伺服器

1. 設置您的帳戶：首先在 Audiense 平台上創建一個帳戶。
2. 連接您的兼容 MCP 的客戶端：將您首選的兼容 MCP 的客戶端連接到 Audiense Insights MCP 伺服器。
3. 配置數據來源：整合您的數據來源以開始收集洞察。
4. 分析數據：利用伺服器的分析工具來解釋數據並生成報告。
5. 實施洞察：利用獲得的洞察來完善您的行銷策略並增強受眾參與度。

常見問題解答

Q1: 什麼是模型上下文協議（MCP）？

A1: 模型上下文協議（MCP）是一種通信協議，允許不同系統之間無縫互動和共享數據。

Q2: 我可以使用任何客戶端與 Audiense Insights MCP 伺服器嗎？

A2: 是的，只要該客戶端是兼容 MCP 的，您就可以將其與 Audiense Insights MCP 伺服器整合。

Q3: 使用 Audiense Insights MCP 伺服器是否需要付費？

A3: Audiense 提供多種定價計劃。最好查看他們的官方網站以獲取最新的定價信息。

Q4: 我該如何獲得 Audiense Insights MCP 伺服器的支持？

A4: 支持可以通過 Audiense 網站獲得，您可以在那裡找到文檔、常見問題解答和客戶服務的聯繫選項。

Q5: 我的數據在 Audiense Insights MCP 伺服器上是否安全？

A5: 是的，Audiense 非常重視數據安全，並實施各種措施來保護用戶數據。

欲了解更多信息，請訪問 Audiense 的官方網站。

⚠️ 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🚫 This repository is no longer maintained.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.