Enterprise Model Context Protocol (MCP) Server & Client
About
A comprehensive enterprise-grade implementation of the Model Context Protocol (MCP) for connecting LLMs with enterprise tools and data sources. It is cost-optimized for production, allows zero-cost testing without any LLM API keys, and supports either OpenAI GPT or Anthropic…
Explore
- JWT Authentication: Secure token-based authentication
- Role-Based Access Control: Fine-grained permissions
- SQL Injection Protection: Query validation and parameterization
- Sandboxed File Access: Restricted file system operations
- HTTPS/WSS Support: Encrypted communications
- Audit Logging: Comprehensive security event logging
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
Enterprise Model Context Protocol (MCP) Server & ClientCommand (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
- Python 3.11+
- PostgreSQL (optional, for enterprise database features)
- Redis (optional, for caching and session management)
cp ../.env.example .env
cd mcp_client
pip install -r requirements.txt
export OPENAI_API_KEY="your-openai-key" # OR
export ANTHROPIC_API_KEY="your-anthropic-key" # OR neither for zero-cost testing
MCP_SERVER_HOST=localhost
MCP_SERVER_PORT=8000
MCP_SERVER_SECRET_KEY=your-secret-key-here
DATABASE_URL=postgresql://user:password@localhost:5432/mcp_enterprise
REDIS_URL=redis://localhost:6379
JWT_SECRET_KEY=your-jwt-secret-key
JWT_ALGORITHM=HS256
JWT_EXPIRATION_HOURS=24
import asyncio
from src.mcp_client.core.client import MCPClient
from src.mcp_client.llm.openai_integration import OpenAIWithMCP
async def main():
docker-compose -f docker-compose.prod.yml up -d
kubectl get pods -l app=mcp-server
- Database Tool: Secure SQL query execution with injection protection
- File Tool: File system operations with sandboxed access
- API Tool: HTTP client for external API integrations
llm = OpenAIWithMCP(
api_key="your-openai-key",
mcp_client=mcp_client
)
messages = [{
"role": "user",
"content": "Query the database for user analytics and create a report file"
}]
result = await llm.chat_completion_with_tools(messages)
print(result['response'])
await mcp_client.disconnect()
asyncio.run(main())
```
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"enterprise model context protocol (mcp) server & client": {
"enterprise_mcp": {
"command": "python",
"args": [
"-m",
"src.mcp_server.main"
]
}
}
}
}McpServers
{
"enterprise_mcp": {
"command": "python",
"args": [
"-m",
"src.mcp_server.main"
]
}
}A comprehensive enterprise-grade implementation of the Model Context Protocol (MCP) for connecting LLMs with enterprise tools and data sources.
💰 Cost-Optimized for Production
- Zero-cost testing: Works without any LLM API keys
- Optimized models: Uses gpt-4o-mini and claude-3.5-haiku (97% cheaper than premium models)
- Single API key: Choose either OpenAI OR Anthropic (not both)
- Direct tool access: Enterprise functionality without LLM overhead
🚀 Features
MCP Server
- JSON-RPC 2.0 Protocol: Full MCP specification compliance - Enterprise Tools: Database queries, file operations, API integrations - Security: JWT authentication, role-based access control - Monitoring: Prometheus metrics, structured logging - WebSocket Support: Real-time bidirectional communicationMCP Client
- Multi-LLM Support: OpenAI GPT and Anthropic Claude integration - Tool Discovery: Automatic detection of server capabilities - Async Operations: High-performance async/await architecture - Error Handling: Robust error handling and retry mechanismsEnterprise Tools
- Database Tool: Secure SQL query execution with injection protection - File Tool: File system operations with sandboxed access - API Tool: HTTP client for external API integrations📦 Installation
Prerequisites
- Python 3.11+ - PostgreSQL (optional, for enterprise database features) - Redis (optional, for caching and session management)Quick Start with Docker
```bash
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