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Rivac AI Labs
Data Intelligence, Document AI & Applied Analytics

Agent/MCP Interfaces for Data Products

AI copilots and agents are becoming the way a growing share of your customers and partners actually want to consume data, not through a dashboard they log into, but through an assistant that can query it directly and reason over the answer. This service adds a Model Context Protocol or agent-ready interface on top of any data product you already have, or that we build alongside it, so AI copilots can query, filter, and retrieve from it programmatically and reliably, with the same access controls and rate limits your other interfaces have. We design the interface around how an agent actually calls tools, not a repurposed human-facing API, so responses come back structured and usable rather than something the agent has to guess at. It solves the emerging gap where a data product with no agent-ready interface is invisible to the growing set of buyers who want to plug their AI stack directly into your data rather than build custom integration code.

This is a capability we deliver for you as a service, not a role we’re hiring for.

How We’d Approach This

A clear, staged plan, not a black box

These are the service-specific steps inside our six-step process.

  1. 1

    Assess the existing data product's API and access model to identify what needs to change for reliable agent/MCP consumption

  2. 2

    Pilot an MCP or agent-tool interface against a representative set of real agent queries, checking response structure and reliability

  3. 3

    Review pilot results with your team and any early agent-based users to refine tool definitions and error handling before wider release

  4. 4

    Ship the production interface with documentation, authentication, and rate limits appropriate for both human-built and autonomous agent clients

What You Get

Deliverables from this engagement

  • Production MCP or agent-ready interface for your data product
  • Documented tool definitions and authentication setup
  • Rate limiting and access controls appropriate for agent traffic
  • Sample agent integration/reference implementation for your team or customers

Six Ways We Could Architect This

Different engagement, different build, pick the shape that fits

There’s more than one way to deliver on this service. Browse a few of the ways we’d structure the work, depending on your speed, budget, and integration needs.

Read all 6 architectures as text

Lean Fast-Start Architecture

Interface Scoping

  • Existing Data Product API
  • Tool Definition Draft
  • Simple Auth Token Setup

Build

  • Single MCP Server
  • Basic Tool Handlers

Testing

  • Local Test Client
  • Sample Agent Query Run

Delivery

  • Working MCP Endpoint
  • Shared with First Agent User
  • Feedback on Tool Reliability
  • Tool Definitions Refined
  • Endpoint Redeployed

Cloud-Native / Managed Services Architecture

Managed Source Layer

  • Data Product API
  • Managed API Gateway
  • Serverless MCP Server Hosting

Managed Service Layer

  • Managed Authentication Service
  • Managed Rate Limiting Service
  • Tool Schema Registry

Observability Layer

  • Managed Logging Service
  • Usage Analytics Dashboard

Operations Layer

  • Autoscaling Backend
  • Managed Secrets Store
  • Health Check Monitoring
  • Automated Failover

Event-Driven & Automation-First Architecture

Triggers

  • Agent Sends Tool Call
  • MCP Request Router
  • Long Running Query Detected
  • Async Job Queue

Automation Layer

  • Background Worker Executes Query
  • Result Ready Webhook

Response Gate

  • Result Valid and Complete
  • Auto Retry with Backoff
  • Structured Response Returned

Usage Analytics

  • Callback to Agent Client
  • Usage Event Streamed
  • Analytics Dashboard Updated

Enterprise-Grade & Compliance-Ready Architecture

Governance Layer

  • Scoped API Keys per Agent Client
  • Data Exposure Compliance Review
  • Rate Limit and Quota Policy

Secure Interface Layer

  • Access Controlled Tool Definitions
  • Redundant Multi Region MCP Hosting
  • Encrypted Transport Layer

Auditable Usage

  • Every Tool Call Logged
  • Anomalous Usage Detection
  • Incident Monitoring Dashboard

Compliance Output

  • Compliance Sign Off
  • Certified Agent Interface
  • Quarterly Access Review

AI-Augmented, Human-in-the-Loop Architecture

API Specification Ingestion

  • Existing Data Product API Spec
  • AI Tool Schema Generator

AI Schema Layer

  • AI Drafted Tool Definitions
  • Schema Confidence Check

Human in the Loop

  • Engineer Review Queue
  • Schema Correct and Safe
  • Correction Sent Back to Generator
  • Human Approved Tool Definition

Delivery

  • Published to MCP Server
  • Agent Clients Can Now Query
  • Agent Error Logs Captured
  • Feedback Improves Schema Generator

Integration-Heavy / Ecosystem-Connected Architecture

Client and Agent Ecosystem

  • Existing Data Product API
  • Client CRM or Data Warehouse
  • Identity and SSO Provider

Interface Core

  • Unified MCP Interface Layer
  • Agent Tool Handler Engine
  • Structured Response Builder

Two Way Sync Layer

  • Claude and ChatGPT Agent Platforms
  • Custom Internal Agents
  • Partner Product Teams
  • Internal Engineering Team

Shared Governance

  • Joint Usage Review
  • Published Agent Analytics Report

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Ready to get started?

Tell us what you’re trying to get done and we’ll help you find the highest-leverage place to start, scoped small enough to prove itself before you commit to anything bigger.

Talk to us about Agent/MCP Interfaces for Data Products

Most engagements like this start as a $500–$2,500 pilot, see full pricing.

Questions? Book a free call