Social Listening MCP Server
About
MCP Server - Chat with your Syften social listening data
Details
- Author
- fred-em
- Downloads
- 465
- Categories
- Other
Jump to
- Real-time social mention monitoring
- AI-powered content categorization
- Webhook notifications for important mentions
- Historical data backfilling
- Trend analysis and reporting
- Natural language query support
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Social Listening MCP ServerCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Install Node.js v16+, clone the repo, run npm install and npm run build. Configure your Syften API key as an environment variable, then add the server to your Claude Desktop or VSCode Claude extension configuration. Use the provided tools (e.g., configure_ai_filter, setup_webhook, analyze_trends) via natural language prompts in Claude.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"social listening mcp server": {
"social-listening": {
"command": "node",
"args": [
"/absolute/path/to/social-listening/build/index.js"
],
"env": {
"SYFTEN_API_KEY": ""
}
}
}
}
}
McpServers
{
"social-listening": {
"command": "node",
"args": [
"/absolute/path/to/social-listening/build/index.js"
],
"env": {
"SYFTEN_API_KEY": ""
}
}
}
Social Listening MCP Server
A Model Context Protocol (MCP) server that provides social listening capabilities through Syften's API. This server enables AI-powered analysis of social mentions, with support for real-time notifications via webhooks.
Features
- Real-time social mention monitoring
- AI-powered content categorization
- Webhook notifications for important mentions
- Historical data backfilling
- Trend analysis and reporting
- Natural language query support
Prerequisites
1. Node.js (v16 or later)
2. A Syften account with API access
3. Claude Desktop app or VSCode with Claude extension
Installation
1. Clone the repository:
git clone https://github.com/fred-em/social-listening.git
cd social-listening
2. Install dependencies:
npm install
3. Build the server:
npm run build
Configuration
1. Syften API Setup
1. Log in to your Syften account
2. Go to Settings > API Access
3. Generate an API key if you haven't already
4. Copy your API key for the next step
2. Claude Desktop Configuration
Add the server configuration to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"social-listening": {
"command": "node",
"args": ["/absolute/path/to/social-listening/build/index.js"],
"env": {
"SYFTEN_API_KEY": "your-api-key-here"
}
}
}
}
3. VSCode Configuration (Optional)
If you're using VSCode with the Claude extension, add the configuration to /Users/YOUR_USERNAME/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json:
{
"mcpServers": {
"social-listening": {
"command": "node",
"args": ["/absolute/path/to/social-listening/build/index.js"],
"env": {
"SYFTEN_API_KEY": "your-api-key-here"
}
}
}
}
Available Tools
1. configure_ai_filter
Configure AI filtering settings for mention analysis.{
"enabled": true,
"min_confidence": 0.7,
"categories": ["spam", "support", "feedback", "bug_report", "feature_request"],
"webhook_url": "https://your-webhook.com/endpoint",
"webhook_secret": "your-secret-token"
}
2. setup_webhook
Configure webhook endpoint for real-time notifications.{
"endpoint_url": "https://your-webhook.com/endpoint",
"secret_token": "your-secret-token",
"enabled": true
}
3. backfill_month
Backfill mentions for a specific month.{
"year": 2024,
"month": 2
}
4. sync_latest
Sync new mentions since last update.{}
5. analyze_trends
Analyze mention trends over time.{
"start_date": "2024-01-01",
"end_date": "2024-02-01",
"group_by": "day",
"tags": ["feature", "bug"]
}
6. get_top_sources
Get top mention sources/authors.{
"start_date": "2024-01-01",
"end_date": "2024-02-01",
"limit": 10
}
7. nlp_prompt
Process natural language queries.{
"prompt": "show me feedback mentions from last week"
}
8. get_ai_filtered_mentions
Get mentions processed by AI filtering.{
"start_date": "2024-01-01",
"end_date": "2024-02-01",
"min_confidence": 0.8,
"categories": ["feedback", "bug_report"],
"limit": 50
}
Example Usage in Claude
Here are some example prompts you can use with Claude:
1. Configure AI filtering:
Configure the social listening AI filter to detect bug reports and feature requests with 80% confidence.
2. Set up webhook notifications:
Set up a webhook for the social listening server to send notifications to https://my-server.com/webhook with the secret token "my-secret".
3. Analyze trends:
Show me the trend of bug reports and feature requests from last month.
4. Get filtered mentions:
Show me all high-confidence bug reports from the past week.
5. Natural language queries:
What kind of feedback have we received about the new feature launch?
Webhook Integration
When configuring webhooks, the server will send notifications in this format:
{
"mention_url": "https://example.com/post",
"ai_score": 0.95,
"ai_categories": ["bug_report", "feature_request"],
"timestamp": "2024-02-12T15:30:00Z"
}
Headers included with webhook requests:
- Content-Type: application/json
- X-Webhook-Secret: your-secret-token
Development
Building from source
```bash
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