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.
- 🤖 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
- Node.js (v16 or higher)
- A Prem AI account with API key
- A Prem project ID
To install prem-mcp-server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @ucalyptus/prem-mcp-server --client claude
# Using npm
npm install prem-mcp-server
# Using yarn
yarn add prem-mcp-server
# Using pnpm
pnpm add prem-mcp-server
Create a .env
file in your project root:
PREM_API_KEY=your_api_key_here
PREM_PROJECT_ID=your_project_id_here
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.
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"
}
}
}
}
npx prem-mcp-server
- Basic Chat
Let's have a conversation about artificial intelligence.
- RAG with Documents
Based on the documents in repository XYZ, what are the key points about [topic]?
- Using Templates
Use template ABC to generate [specific type of content].
The server supports uploading documents to Prem AI repositories for RAG operations. Supported formats:
.txt
.pdf
.docx
query
: The input textsystem_prompt
: Custom system promptmodel
: Model identifiertemperature
: Response randomness (0-1)max_tokens
: Maximum response lengthrepository_ids
: Array of repository IDs for RAGsimilarity_threshold
: Threshold for document similaritylimit
: Maximum number of document chunks
template_id
: ID of the prompt templateparams
: Template-specific parameterstemperature
: Response randomness (0-1)max_tokens
: Maximum response length
# 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
-
Server Not Found
- Verify the server path in
claude_desktop_config.json
- Check if the server is running
- Verify the server path in
-
API Key Invalid
- Ensure your Prem AI API key is valid
- Check if the API key has the required permissions
-
Document Upload Failed
- Verify file format is supported
- Check file permissions
- Ensure repository ID is correct
Contributions are welcome! Please feel free to submit a Pull Request.
MIT License - see the LICENSE file for details.
- Prem AI for their powerful AI platform
- Model Context Protocol for the protocol specification
- Anthropic for Claude and the MCP ecosystem
For issues and feature requests, please use the GitHub Issues page.