AI Workflow Automation

A Practical Guide to MCP (Model Context Protocol) for Enterprise

4 min read

MCP changes how enterprise AI agents integrate with internal tools. A pragmatic walkthrough.

  1. 01Build an MCP server per bounded context

    “Customer data MCP server”, “Billing MCP server”.

  2. 02Authenticate with mTLS or OAuth client creds

    Never share keys across servers.

  3. 03Audit-log every tool invocation

    Identical schema to LLM invocation logs.

  4. 04Rate-limit per agent identity

    Stops a runaway agent from DOS-ing internal services.

Production-Grade AI Agent ArchitectureThree layers that keep enterprise agents reliableInputStructured payloadLAYER 1Deterministic BoundarySchema-bounded LLM callLAYER 2Validation GateSchema · Range · Cross-refPASS→ Final actionFAIL→ Human reviewLAYER 3 · Audit TrailEvery decision logged: input → prompt → output → action
The 3-layer architecture pattern Ohveda uses to ship reliable, auditable enterprise AI agents to production.

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