mxcp
Active·★ 69·NOASSERTION·Updated 2026-05-26
★ Trending★ LLM Infra
Model eXecution + Context Protocol: Enterprise-Grade Data-to-AI Infrastructure
MXCP is a complete methodology for building production-ready MCP servers with enterprise security, data quality, and comprehensive testing. It enables developers to define services with data contracts, implement them in SQL or Python, and enforce security policies with audit trails and drift detection.
#chatgpt#claude#dbt#duckdb#large-language-model#large-language-models#llms#mcp
01
Features
01Security First: OAuth, RBAC, policy enforcement
02Complete Audit Trail: Track every operation for compliance
03Type Safety: Comprehensive validation across SQL and Python
04Testing Framework: Unit, integration, and LLM behavior tests
05Drift Detection: Monitor schema changes across environments
02
Compatibility
Python 3.11+
Python 3.11+
Verified via docs
Claude Desktop
Claude Desktop
Verified via docs
OpenAI Compatible
OpenAI Compatible
Verified via docs
03
Quick start
1
$ pip install mxcp
04
Use cases
↳Build AI-powered data query tools with SQL and Python
↳Implement enterprise-grade access control for sensitive data
↳Create complex data analysis pipelines with ML integration
05
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Comments
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- EEllis ZhangMar 26, 2026
Used for enterprise data integration, the production-grade reliability is essential
- JJesse WhiteMar 13, 2026
Enterprise-grade data-to-AI infrastructure combining MCP and execution is well designed
- CCasey BrownMar 4, 2026
The MeXCP approach to data access is more principled than ad-hoc MCP server implementations
- DDrew JacksonFeb 27, 2026
Good for organizations that need governed data access in AI workflows