Prem MCP Server: Seamless Deployments & Enterprise Scalability

Prem MCP Server

A Model Context Protocol (MCP) server implementation for Prem AI, enabling seamless integration with Claude and other MCP-compatible clients. This server provides access to Prem AI's powerful features through the MCP interface.

Features

• 🤖 Chat Completions : Interact with Prem AI's language models
• 📚 RAG Support : Retrieval-Augmented Generation with document repository integration
• 📝 Document Management : Upload and manage documents in repositories
• 🎭 Template System : Use predefined prompt templates for specialized outputs
• ⚡ Streaming Responses : Real-time streaming of model outputs
• 🛡️ Error Handling : Robust error handling and logging

Prerequisites

• Node.js (v16 or higher)
• A Prem AI account with API key
• A Prem project ID

Installation

# Using npm
npm install prem-mcp-server

# Using yarn
yarn add prem-mcp-server

# Using pnpm
pnpm add prem-mcp-server

Configuration

1. Environment Variables

Create a .env file in your project root:

PREM_API_KEY=your_api_key_here
PREM_PROJECT_ID=your_project_id_here

2. Cursor Configuration

To use the Prem MCP server with Cursor, add the following to your ~/.cursor/mcp.json:

{
  "mcpServers": {
    "PremAI": {
      "command": "node",
      "args": ["/path/to/your/prem-mcp/build/index.js", "--stdio"],
      "env": {
        "PREM_API_KEY": "your_api_key_here",
        "PREM_PROJECT_ID": "your_project_id_here"
      }
    }
  }
}

Replace /path/to/your/prem-mcp with the actual path to your project directory.

3. Claude Desktop Configuration

For Claude Desktop users, add the following to your claude_desktop_config.json:

{
  "mcpServers": {
    "PremAI": {
      "command": "npx",
      "args": ["prem-mcp-server", "--stdio"],
      "env": {
        "PREM_API_KEY": "your_api_key_here",
        "PREM_PROJECT_ID": "your_project_id_here"
      }
    }
  }
}

Usage

Starting the Server

npx prem-mcp-server

Example Prompts

1. Basic Chat

Let's have a conversation about artificial intelligence.

2. RAG with Documents

Based on the documents in repository XYZ, what are the key points about [topic]?

3. Using Templates

Use template ABC to generate [specific type of content].

Document Upload

The server supports uploading documents to Prem AI repositories for RAG operations. Supported formats:

• .txt
• .pdf
• .docx

API Reference

Chat Completion Parameters

• query: The input text
• system_prompt: Custom system prompt
• model: Model identifier
• temperature: Response randomness (0-1)
• max_tokens: Maximum response length
• repository_ids: Array of repository IDs for RAG
• similarity_threshold: Threshold for document similarity
• limit: Maximum number of document chunks

Template Parameters

• template_id: ID of the prompt template
• params: Template-specific parameters
• temperature: Response randomness (0-1)
• max_tokens: Maximum response length

Development

# Clone the repository
git clone https://github.com/yourusername/prem-mcp-server.git

# Install dependencies
npm install

# Build the project
npm run build

# Run tests
npm test

Troubleshooting

Common Issues

1. Server Not Found

* Verify the server path in `claude_desktop_config.json`
* Check if the server is running

2. API Key Invalid

* Ensure your Prem AI API key is valid
* Check if the API key has the required permissions

3. Document Upload Failed

* Verify file format is supported
* Check file permissions
* Ensure repository ID is correct

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT License - see the LICENSE file for details.

Acknowledgments

• Prem AI for their powerful AI platform
• Model Context Protocol for the protocol specification
• Anthropic for Claude and the MCP ecosystem

Support

For issues and feature requests, please use the GitHub Issues page.