Monte Carlo MCP Server Technical Overview
The Monte Carlo Model Context Protocol (MCP) Server enables AI applications and agents such as Cursor, Claude, and other MCP compatible tools to interact securely with Monte Carlo’s Data + AI Observability Platform.
The Monte Carlo MCP Server provides a secure, scalable, and fully managed environment for AI-assisted data quality management. It connects Monte Carlo’s trusted data quality, lineage, and alerting APIs with AI agents, while maintaining enterprise-grade security.
Architecture Summary
Core Components
| Component | Description |
|---|---|
| MCP Clients | AI tools that initiate requests through the MCP protocol. |
| Integration Gateway | Authenticates requests, validates tokens, and forwards traffic to the MCP Server. |
| MCP Server | Hosted in AWS Lambda, exposes Monte Carlo’s capabilities such as alerting and lineage. |
| GraphQL API | Monte Carlo’s backend service responsible for executing and authorizing data queries. |
Authentication & Authorization
The MCP Server enforces strict authentication and authorization aligned with both the MCP Protocol and Monte Carlo’s security and compliance frameworks.
API Keys
- Customers authenticate using their standard Monte Carlo credentials.
- The MCP Server never directly reuses customer tokens, preventing token pass-through violations.
- API calls are executed under the user’s identity in Monte Carlo’s GraphQL API, preserving existing access controls.
Data Access & Privacy
- Customer Isolation: All API calls are scoped to the authenticated user’s tenant and data region.
- Encryption in Transit: All communications between clients, gateways, and the MCP Server use HTTPS (TLS 1.2+).
- Stateless Design: The MCP Server does not persist or cache customer data — all processing happens in real time.
- Auditing: Requests include telemetry metadata for full traceability and compliance review.
Updated 1 day ago