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Audiense Insights

BYAudienseCo17GRADE B

Marketing insights and audience analysis from [Audiense](https://www.audiense.com/products/audiense-insights) reports, covering demographic, cultural, influencer, and content engagement analysis.

Config Installation

Add this to your claude_desktop_config.json:

{
  "mcpServers": {
    "audiense-insights": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-audiense-insights"
      ]
    }
  }
}

* Note: Requires restart of Claude Desktop app.

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Adoption Framework for Audiense Insights

Before installing any skill, define a clear objective and measurable outcome. A useful implementation question is: what workflow becomes faster, safer, or more reliable after this skill is active? If that answer is vague, delay rollout and tighten scope first.

For most teams, a low-risk pattern is preview-first rollout with one owner, one test scenario, and one rollback plan. Capture failures in a structured log so quality decisions are evidence-based. This is especially important for skills that touch file systems, external APIs, or automation chains with downstream side effects.

  • Define success metrics before installation.
  • Validate permission scope against policy boundaries.
  • Run one controlled pilot and document failure categories.
  • Promote only after acceptance checks pass consistently.

Pre-Deployment Review Questions

Use these questions before enabling the skill in shared environments. They reduce surprise incidents and make approval decisions consistent across teams.

  • What data can this skill read, write, or transmit by default?
  • Which failures are recoverable automatically and which require manual stop?
  • Do we have verifiable logs that prove safe behavior under load?
  • Is rollback tested, documented, and assigned to a clear owner?

If any answer is unclear, keep rollout in preview and close the gap before production use.

Editorial Review Snapshot

This listing includes an editorial QA layer in addition to automated rendering. Review status is based on documentation depth, content uniqueness, and operational safety signals from the upstream repository.

  • Last scan date: 2026-01-18
  • README depth: 1037 words
  • Content diversity score: 0.54 (higher is better)
  • Template signal count: 0
  • Index status: Index eligible

Recommendation: Pilot in a bounded environment first. Confirm observability and ownership before promoting to shared workflows.

Skill Implementation Board

Actionable utility module for rollout decisions. Use the inputs below to choose a deployment path, then execute the checklist and record an output note.

Input: Security Grade

B

Input: Findings

0

Input: README Depth

1037 words

Input: Index State

Eligible

Decision TriggerActionExpected Output
Input: risk band moderate, docs partial, findings 0Run a preview pilot with fixed ownership and observability checkpoints.Pilot can start with rollback checklist attached.
Input: page is index-eligibleProceed with external documentation and team onboarding draft.Reusable rollout runbook ready for team adoption.
Input: context tags/scenarios are missingDefine two concrete scenarios before broad rollout.Clear scope definition before further deployment.

Execution Steps

  1. Capture objective, owner, and rollback contact.
  2. Run one preview pilot with fixed test scenario.
  3. Record warning behavior and recovery evidence.
  4. Promote only if pilot output matches expected threshold.

Output Template

skill=audiense-insights
mode=B
pilot_result=pass|fail
warning_count=0
next_step=rollout|patch|hold

🛡️ Security Analysis

SCANNED: 2026-01-18
SCORE: 80/100

Clean Scan Report

Our static analysis engine detected no common vulnerabilities (RCE, API Leaks, Unbounded FS).

DocumentationREADME.md

Note: The content below is automatically rendered from the repository's README file.

⚠️ 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 [email protected].



🏆 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
  1. Verify environment variables are set correctly.
  2. 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.