# 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

- **Type:** MCP server
- **Install:** `agentstack add mcp-audienseco-mcp-audiense-insights`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [AudienseCo](https://agentstack.voostack.com/s/audienseco)
- **Installs:** 0
- **Category:** [Integrations](https://agentstack.voostack.com/c/integrations)
- **Latest version:** 0.1.0
- **License:** Apache-2.0
- **Upstream author:** [AudienseCo](https://github.com/AudienseCo)
- **Source:** https://github.com/AudienseCo/mcp-audiense-insights
- **Website:** https://audiense.com

## Install

```sh
agentstack add mcp-audienseco-mcp-audiense-insights
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

## ⚠️ **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## 🚫 This repository is no longer maintained.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](mailto:support@audiense.com).

---
---

## 🏆 Audiense Insights MCP Server

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)_

---

## ⚙️ 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": "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.

## Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [AudienseCo](https://github.com/AudienseCo)
- **Source:** [AudienseCo/mcp-audiense-insights](https://github.com/AudienseCo/mcp-audiense-insights)
- **License:** Apache-2.0
- **Homepage:** https://audiense.com

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/mcp-audienseco-mcp-audiense-insights
- Seller: https://agentstack.voostack.com/s/audienseco
- Browse the marketplace: https://agentstack.voostack.com/browse

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