by AudienseCo
mcp-audiense-insights is a tool that connects AI agents to the Audiense Insights platform. It enables AI agents to access and analyze marketing insights and audience data for various use cases like market research and content strategy.
The Audiense Insights MCP Server is a tool that connects to the Audiense Insights platform, allowing AI agents to access and analyze marketing insights and audience data. It provides tools to retrieve reports, get audience demographics, and analyze cultural and content engagement.
To use the server, you need an Audiense Insights account with API credentials. The server is configured by setting environment variables for your Audiense client ID and secret. It can then be run and connected to an MCP client like Claude Desktop.
Q: What is Audiense Insights? A: Audiense Insights is a marketing platform that provides rich insights into audiences, helping businesses to understand and connect with their target customers.
Q: Is this repository still maintained? A: No, this repository is deprecated. The Audiense Insights MCP has been migrated to a remote model. For more information, you should contact Audiense support.
Q: What do I need to use the server? A: You need a Node.js environment (v18+), an Audiense Insights account with API credentials, and an MCP-compatible client.
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.
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.
Before using this server, ensure you have:
Open the configuration file for Claude Desktop:
code ~/Library/Application\ Support/Claude/claude_desktop_config.json
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.
get-reports
Description: Retrieves the list of Audiense insights reports owned by the authenticated user.
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:
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:
get-baselines
Description: Retrieves available baseline audiences, optionally filtered by country.
Parameters:
country
(string, optional): ISO country code to filter by.Response:
get-categories
Description: Retrieves the list of available affinity categories that can be used in influencer comparisons.
compare-audience-influencers
Description: Compares influencers of a given audience with a baseline audience. The baseline is determined as follows:
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:
get-audience-content
Description: Retrieves audience content engagement details, including:
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:
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:
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:
Use case: Structured guidance for audience analysis.
tail -f ~/Library/Logs/Claude/mcp*.log
To check server logs:
tail -n 20 -f ~/Library/Logs/Claude/mcp*.log
Get-Content -Path "$env:AppData\Claude\Logs\mcp*.log" -Wait -Tail 20
This project is licensed under the Apache 2.0 License. See the LICENSE file for more details.
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