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Data & AI Architecture Layer

MCP & Agentic Systems

How to connect models to enterprise tools and data safely — the Model Context Protocol, tool-calling contracts, and the governance layer multi-agent systems need before production.

The problem MCP solves

Every model-to-tool integration used to be bespoke

Before a shared protocol, every model-to-database, model-to-API, or model-to-file-system connection was a one-off integration with its own auth, its own schema, its own failure modes. The Model Context Protocol standardizes how a model discovers and calls tools — the same way REST standardized how services talk to each other.

Core patterns

Reference architectures

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Protocol

MCP Servers & Clients

Exposing internal systems as MCP servers with typed tool schemas, and connecting them to any MCP-compatible client.

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Security

Scoped Tool Permissions

Least-privilege tool access per agent session, with explicit human approval for write or destructive actions.

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Orchestration

Multi-Agent Orchestration

Planner/worker and supervisor patterns for coordinating multiple specialized agents on a shared task.

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Governance

Agent Action Audit Trail

Immutable logging of every tool call an agent makes, so autonomous actions are as reviewable as a change ticket.

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Safety

Circuit Breakers

Rate limits, budget caps, and kill-switches to bound what an autonomous loop can do before a human is notified.

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Discovery

Tool & Connector Registry

A central catalog of approved MCP servers and connectors, so teams reuse vetted integrations instead of re-building them.

Enterprise checklist

Before an agent goes into production

“An agent with unscoped tool access isn’t autonomy — it’s an unaudited service account with a chat interface.”
— Viswa