Data

Tools

Indexes

Applications

Experiments

Awesome

An open API service indexing awesome lists of open source software.

https://github.com/AudienseCo/mcp-audiense-insights

Audiense Insights MCP Server is a server based on the Model Context Protocol (MCP) that allows Claude and other MCP-compatible clients to interact with your Audiense Insights account
https://github.com/AudienseCo/mcp-audiense-insights

mcp modelcontextprotocol

Last synced: about 2 months ago
JSON representation

Audiense Insights MCP Server is a server based on the Model Context Protocol (MCP) that allows Claude and other MCP-compatible clients to interact with your Audiense Insights account

Awesome Lists containing this project

README 

        
# 🏆 Audiense Insights MCP Server

[![smithery badge](https://smithery.ai/badge/@AudienseCo/mcp-audiense-insights)](https://smithery.ai/server/@AudienseCo/mcp-audiense-insights)



This server, based on the [Model Context Protocol (MCP)](https://github.com/modelcontextprotocol), allows **Claude** or any other MCP-compatible client to interact with your [Audiense Insights](https://www.audiense.com/) 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)_



---



## Installing via Smithery



To install Audiense Insights Server for Claude Desktop automatically via [Smithery](https://smithery.ai/server/@AudienseCo/mcp-audiense-insights):



```bash

npx -y @smithery/cli@latest install @AudienseCo/mcp-audiense-insights --client claude

```



## ⚙️ Configuring Claude Desktop



1. Open the configuration file for Claude Desktop:



   - **MacOS:**

     ```bash

     code ~/Library/Application\ Support/Claude/claude_desktop_config.json

     ```

   - **Windows:**

     ```bash

     code %AppData%\Claude\claude_desktop_config.json

     ```



2. Add or update the following configuration:



   ```json

   "mcpServers": {

     "audiense-insights": {

       "command": "/opt/homebrew/bin/node",

       "args": [

         "/ABSOLUTE/PATH/TO/YOUR/build/index.js"

       ],

       "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.