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prem-mcp-serveur
Implémentation d'un serveur MCP pour utiliser le SDK Prem
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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
Installing via Smithery
To install prem-mcp-server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @ucalyptus/prem-mcp-server --client claude
Installing Manually
# 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
- 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].
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
-
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
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.
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Reviews

user_eiw6aQGW
As a dedicated user of the Strava MCP Server by MCP-Mirror, I am thoroughly impressed with its seamless integration and user-friendly interface. The server's reliability and speed have significantly enhanced my experience. Highly recommended for all Strava enthusiasts looking for an efficient solution! Check it out: https://mcp.so/server/ctvidic_strava-mcp-server/MCP-Mirror