Pearl MCP Server
About
A Model Context Protocol (MCP) server implementation that exposes Pearl's AI and Expert services through a standardized interface
Details
- Author
- Pearl-com
- GitHub stars
- 8
- Downloads
- 336
- Categories
- Other
Jump to
- Support for both stdio and SSE transports
- Integration with Pearl API for AI and expert assistance
- Session management for continuous conversations
- Two interaction modes: AI‑Expert and direct Expert
- Conversation history tracking and stateful session management
- Automatic routing of queries to the most relevant expert category
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
Pearl 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 Python 3.12 or higher, obtain a Pearl API key from the Pearl contact page, clone the repository, create a virtual environment, install dependencies with pip install -e ., and set the PEARL_API_KEY environment variable in a .env file. Run the server locally with pearl-mcp-server --api-key your-api-key (stdio by default) or with --transport sse. Alternatively, connect directly to the hosted server at https://mcp.pearl.com/mcp without local installation. Configure your MCP client (e.g., Claude Desktop, Cursor, Windsurf) with the appropriate JSON settings for stdio or use mcp-remote as a bridge for remote connections.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"pearl mcp server": {
"pearl_mcp_server": {
"command": "python",
"args": [
"-m",
"venv",
".venv"
]
}
}
}
}McpServers
{
"pearl_mcp_server": {
"command": "python",
"args": [
"-m",
"venv",
".venv"
]
}
}Pearl MCP Server
A Model Context Protocol (MCP) server implementation that exposes Pearl's AI and Expert services through a standardized interface. This server allows MCP clients like Claude Desktop, Cursor, and other MCP-compatible applications to interact with Pearl's advanced AI assistants and human experts.
Features
- Support for both stdio and SSE transports
- Integration with Pearl API for AI and expert assistance
- Session management for continuous conversations
- Two interaction modes:
- AI-Expert mode for AI-assisted human expert support
- Expert mode for direct human expert assistance
- Conversation history tracking
- Stateful session management
Prerequisites
- Python 3.12 or higher
- Pearl API Key (Contact Pearl to obtain your API key)
- pip or uv package manager
Installation
1. Clone the repository:
git clone https://github.com/Pearl-com/pearl_mcp_server.git
cd pearl_mcp_server
2. Create a virtual environment and activate it:
python -m venv .venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
3. Install dependencies:
pip install -e .
Configuration
1. Create a .env file in the src directory:
PEARL_API_KEY=your-api-key-here
Running the Server
Local Development
Start the server using either stdio (default) or SSE transport:
```bash
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