AI Integrations

Sparx EA AI Integrations: Connect Your EA Repository to Every AI Tool

Your EA Repository Is a Live Data Source: If You Connect It

Architects spend months building rigorous models in Sparx EA. That work disappears the moment someone closes the EA client. Stakeholders, executives, and even other architects don’t see it. They see whatever was in last month’s PowerPoint.

EA GraphLink changes that. It’s a connectivity layer that transforms your EA Repository into a live data source for every AI tool your organization uses. One deployment connects Power BI, Copilot, Fabric, Tableau, Agentforce, Claude, Cursor, and more: simultaneously, on the same data.

The catch is important: EA GraphLink doesn’t invent structure where none exists. It transforms your EA Repository using the MDG Technology definition: the formal semantic schema you’ve already built (or need to build). A well-governed MDG produces rich, queryable architecture intelligence. A fragmented one produces confused outputs at scale. MDG quality is assessed in Discover and established in Deploy. It’s the upstream prerequisite for everything downstream.


The Problem EA GraphLink Solves

When you deploy Sparx EA, you solve the first problem: architects get a single source of truth for models. But you create a second problem: that truth is locked inside the EA client, visible only to people with EA licenses who know how to navigate the interface.

Stakeholders have questions that architecture data could answer:

But those questions go to architects via email or Slack. Architects export reports manually. Decision-making happens against stale snapshots. Data governance teams build their own parallel copies to feed BI tools. Integration teams replicate capabilities in their platforms because they can’t access the authoritative source.

When EA Repository is live-connected:

That’s what EA GraphLink enables.


The EA GraphLink Foundation

EA GraphLink sits at the center of the Sparx Systems Architecture Platform stack. It connects directly to the EA Repository database (bypassing the EA client and Pro Cloud Server), transforms the physical schema using the MDG Technology definition, and exposes two interfaces: a GraphQL API for BI dashboards, and an MCP Server for AI tools and data integration platforms.

The Architecture:

Component Role
EA Repository Physical database (SQL Server, MySQL, PostgreSQL) containing all model data
EA GraphLink Connectivity and transformation layer: reads repository, applies MDG schema, exposes interfaces
GraphQL API Interface A: Returns architecture data in structured format for Power BI and Tableau connectors
MCP Server Interface B: Exposes architecture as MCP resources for Claude, Copilot, Agentforce, Cursor, and data integration control planes

One EA GraphLink deployment supports both interfaces simultaneously. You deploy once, and all downstream tools can connect.

The MDG Technology Dependency

EA GraphLink can only expose what the MDG Technology definition describes. The MDG is the semantic bridge between the physical repository schema and the logical architecture model.

This is why Discover (assessment) and Deploy (governance establishment) come before Connect. You cannot skip the MDG foundation.


Your Ecosystem Path: Microsoft, Salesforce, or Universal

Different organizations have different downstream tools. EA GraphLink adapts.

Microsoft Ecosystem Path

If your organization standardizes on Microsoft 365 and Azure:

  1. EA GraphLink Foundation: Deploy EA GraphLink and establish repository connectivity
  2. Power BI: Connect EA GraphLink’s GraphQL interface to Power BI Connector: create live architecture dashboards
  3. Microsoft Fabric: Connect via MCP Server: architecture data becomes a first-class Fabric data source
  4. Microsoft Copilot: Connect via MCP Server: architects and stakeholders query live architecture via Copilot

Salesforce Ecosystem Path

If your organization standardizes on Salesforce and MuleSoft:

  1. EA GraphLink Foundation: Deploy EA GraphLink and establish repository connectivity
  2. Tableau: Connect EA GraphLink’s GraphQL interface: create live architecture dashboards
  3. MuleSoft Fabric: Connect via MCP Server: architecture data integrates into the MuleSoft data plane
  4. Salesforce Agentforce: Connect via MCP Server: agents access architecture context in conversations

Universal AI Tools Path

Regardless of ecosystem:


Integration Reference Guide

Integration Type Who Benefits Ecosystem Start Here If…
Power BI BI Dashboard (GraphQL) Executive, Analyst, Architecture Manager Microsoft You use Power BI for executive dashboards and want live architecture visibility
Microsoft Copilot AI Chat (MCP) Architect, EA Architect, Stakeholder Microsoft You want stakeholders to ask architecture questions in Copilot
Microsoft Fabric Data Integration (MCP) Data Engineer, Data Architect Microsoft You’re building a enterprise data fabric and architecture is a first-class source
Tableau BI Dashboard (GraphQL) Executive, Analyst, Architecture Manager Salesforce You standardize on Tableau for BI and want live architecture visualization
Salesforce Agentforce AI Agent (MCP) Sales, Service, Executive, Stakeholder Salesforce You want Agentforce agents to reference architecture in customer and operational conversations
MuleSoft Fabric Data Integration (MCP) Integration Architect, Data Engineer Salesforce Architecture data is a required source in your MuleSoft integration platform
Claude AI Chat (MCP) Architect, EA Architect, Software Engineer Universal You use Claude for architecture analysis and want live repository context
Cursor / Claude Code IDE Integration (MCP) Software Architect, Developer Universal You want IDE-native access to live architecture while coding or designing systems
Google Gemini AI Chat (MCP) Architect, EA Architect Universal Your team uses Gemini and wants architecture context in chat
ChatGPT Enterprise AI Chat (MCP) Architect, EA Architect Universal You standardize on OpenAI and want architecture context in enterprise ChatGPT
Azure OpenAI AI Chat (MCP) Architect, EA Architect, Enterprise Governance Universal You deploy OpenAI models in Azure and need architecture context without external API calls
Kernaro AI Hub Stakeholder Platform Business Stakeholder, Executive, EA Architect Universal (Sparx-hosted) You want non-technical stakeholders to ask natural language architecture questions in a browser

Where to Start: Three Scenarios

Scenario 1: “Our organization primarily uses Microsoft 365”

Start with: EA GraphLink Foundation → Power BI → Copilot

  1. Deploy EA GraphLink and verify repository connectivity (Connect engagement)
  2. Connect Power BI and build your first set of live dashboards
  3. Once dashboards are mature, connect Copilot for stakeholder queries
  4. Optionally: Fabric for advanced data integration

Timeline: 8-12 weeks. Cost range: $50K–$185K+ (Connect service).

Scenario 2: “Our organization primarily uses Salesforce”

Start with: EA GraphLink Foundation → Tableau → Agentforce

  1. Deploy EA GraphLink and verify repository connectivity (Connect engagement)
  2. Connect Tableau and build your first set of live dashboards
  3. Once dashboards are mature, connect Agentforce for stakeholder queries
  4. Optionally: MuleSoft Fabric for deep integration

Timeline: 8-12 weeks. Cost range: $50K–$185K+ (Connect service).

Scenario 3: “We’re evaluating multiple AI tools”

Start with: EA GraphLink Foundation → Integration Comparison

  1. Deploy EA GraphLink as the foundation (Connect engagement)
  2. Simultaneously test GraphQL integrations (Power BI, Tableau) and MCP integrations (Claude, Copilot)
  3. Make build vs. buy decisions based on live performance data
  4. Scale to the integrations that drive the most value

Timeline: 10-16 weeks. Cost range: $75K–$185K+ (Connect service with extended testing scope).


Before You Start: The MDG Check

CRITICAL: Do not start a Connect engagement if your MDG Technology definition is in poor shape.

Your MDG is in good shape if:

Your MDG needs work if:

If your MDG is strong: Proceed directly to Connect.

If your MDG needs work: Start with Deploy ($30K–$130K). Deploy establishes MDG governance, documents definitions, and ensures consistent application across the repository. Then Connect.

If you’re not sure: Start with Discover ($25K–$75K). Discover includes an MDG readiness assessment and a roadmap for governance work.


Frequently Asked Questions

What is EA GraphLink?

EA GraphLink is a connectivity and transformation layer that connects your EA Repository directly to Power BI, Tableau, AI tools, and data integration platforms. It reads data from the physical repository, transforms it using your MDG Technology definition, and exposes two interfaces: a GraphQL API for BI tools and an MCP Server for AI tools.

Do I need separate EA GraphLink deployments for Microsoft and Salesforce tools?

No. One EA GraphLink deployment serves both. The GraphQL interface connects to Power BI and Tableau simultaneously. The MCP Server connects to Copilot, Agentforce, Claude, and every other tool at the same time. Deploy once, integrate many.

What is the MDG Technology dependency and why does it matter for AI?

The MDG Technology definition is the semantic schema that describes your architecture data. EA GraphLink transforms the physical repository schema into a logical model using the MDG. If the MDG is fragmented or informal, EA GraphLink cannot produce meaningful outputs: not because of a software limitation, but because there is no semantic foundation to transform. MDG quality is assessed in Discover and established in Deploy before you Connect.

Can I connect Sparx EA to Claude or other non-Microsoft AI tools?

Yes. Claude, Cursor, Claude Code, Google Gemini, ChatGPT Enterprise, and Azure OpenAI all connect via the MCP Server interface. EA GraphLink uses the open MCP standard: you’re not locked to one vendor’s AI platform.

What’s the difference between the GraphQL interface and the MCP interface?

GraphQL serves BI tools (Power BI, Tableau) that need structured data for dashboards. MCP serves AI tools and data integration platforms that need to understand and reason about architecture. Both interfaces expose the same underlying data, transformed by the same MDG. You use one or both depending on your tools.

How long does a typical Connect engagement take?

8–16 weeks, depending on scope. A simple deployment (EA GraphLink + one BI tool) is faster. Multi-tool integrations with testing and optimization take longer. Sparx Services works with you on timeline during scoping.

What software licenses do I need to purchase and who do I buy them from?

You purchase EA GraphLink, Kernaro Hub, and any Sparx Systems software directly from Sparx Systems. Sparx Services provides the software bill of materials as part of the Connect engagement. You purchase Power BI, Tableau, Copilot, and Agentforce licenses directly from Microsoft or Salesforce. Sparx Services is not a reseller: we help you understand what you need and how to use it.

Where should I start if my MDG is in poor shape?

Start with Deploy ($30K–$130K) to establish MDG governance and document definitions across your repository. Once governance is in place and consistent application is verified, then move to Connect. A Connect engagement on top of a fragmented MDG will produce unusable results; a Connect engagement after Deploy produces high-value integrations.


Ready to Connect Your EA Repository?

Your architecture models contain insights that should drive decisions across the business. EA GraphLink makes those insights live, queryable, and accessible to stakeholders, executives, and AI tools: without exporting, copying, or manual reporting.

Three paths forward:

[CTA Button: Schedule a Consultation] | [Learn about Discover] | [Learn about Deploy]

Ready to make your EA investment work harder?

Talk to a Sparx Services architect about where your organization is on the journey and what the next stage looks like.