MCP server connecting financial datasets to Claude — in production Moody's

First Spanish energy company in the ChatGPT ecosystem Nieves Energía

Sergio Gago

Director of AI and Quantum, Moody's

Why MCP matters

Your data, in every AI assistant

MCP is the standard that lets Claude, ChatGPT, and any compatible AI assistant query your platform directly. Build once, connect everywhere.

Security by design

Sensitive data never reaches the model. The MCP server mediates every request — enforcing access rules, scoping responses, and logging all queries for compliance.

The competitive moat

Companies with MCP integrations become the default data source for AI users in their sector. First movers gain distribution advantages that compound over time.

What we build

End-to-end MCP development — from architecture to production deployment

Custom MCP servers

Purpose-built servers that expose your platform's data and capabilities as AI-callable tools. Designed around your data model, your access rules, and your compliance requirements.

Secure access control

Role-based permissions that determine what each user, team, or integration can access — enforced at the server layer before any data reaches the AI assistant.

Context management

Smart context selection: the server surfaces only what the model needs to answer the query, keeping responses focused and latency low.

Enterprise integration

We connect your MCP server to your existing APIs, databases, and internal tools — no rip-and-replace, no new data warehouse required.

Hosting and monitoring

Production-ready deployment with uptime monitoring, query logging, and alerting. We operate what we build.

Security and governance

Audit logs, encryption at rest and in transit, rate limiting, and compliance documentation. Built for regulated industries from day one.

MCP server architecture diagram — data flows through the MCP server before reaching the AI assistant

How it works

The MCP server sits between your data and the AI assistant. It receives requests from the model, resolves them against your APIs and databases, applies access controls, and returns scoped responses — all without sensitive data ever reaching the LLM directly.

Connect your data

We map your existing APIs, databases, and internal platforms to structured MCP tools the AI can call.

Define access rules

Role-based access controls determine what each user or integration can query. Rules are enforced server-side before any data is returned.

Deploy and monitor

Production deployment with full audit logging. Every query is recorded with user context, timestamp, and scope.

Iterate

New data sources, new tools, new access tiers — the architecture is designed for extension without rewrites.

Compatible with all major AI assistants

Ready to connect your platform to AI?

Let's talk

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