by raw-labs · MCP Server · ★ 69
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MXCP: Enterprise-Grade MCP Framework for AI Applications The structured methodology for building production-ready MCP servers with enterprise security, data quality, and comprehensive testing 🚀 What Makes MXCP Different? MXCP isn't just another MCP implementation - it's a complete methodology for building production AI applications the right way: The Production-Ready Approach 📊 Data Modeling First: Start with dbt models, data contracts, and quality tests 📋 Service Design: Define types, security policies, and API contracts upfront 🛠️ Smart Implementation: Choose SQL for data, Python for logic - or combine both ✅ Quality Assurance: Validate, test, lint, and evaluate before deployment 🚨 Production Operations: Monitor drift, track audits, ensure performance Enterprise Features Built-In 🔒 Security First: OAuth authentication, RBAC, policy enforcement 📝 Complete Audit Trail: Track every operation for compliance 🎯 Type Safety: Comprehensive validation across SQL and Python 🧪 Testing Framework: Unit tests, integration te
| Stars | 69 |
| Forks | 9 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 31.75/100 |
| Open Issues | 30 |
| Last Updated | 2026-05-26 |
| Created | 2025-05-21 |
| Platforms | claude-code, cli, mcp, python |
| Est. Tokens | ~227k |
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mxcp is Model eXecution + Context Protocol: Enterprise-Grade Data-to-AI Infrastructure. It is categorized as a MCP Server with 69 GitHub stars.
mxcp is primarily written in Python. It covers topics such as chatgpt, claude, dbt.
You can find installation instructions and usage details in the mxcp GitHub repository at github.com/raw-labs/mxcp. The project has 69 stars and 9 forks, indicating an active community.
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