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Connecting SIS, LMS and CRM to AI Agents with MCP

Integration with the Model Context Protocol

A higher education course from ibl.ai (self-paced, 14 to 16 hours, free). Student information system integration for AI agents: wrap Banner, Canvas and Slate as MCP servers, scope access by FERPA role, and audit every call.

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Course description

Student information system integration is the bottleneck for every AI initiative on campus: the SIS holds enrollment and standing, the LMS holds grades and engagement, the CRM holds prospects and yield, and each speaks its own API and its own role model. This course teaches you to expose those systems to AI agents through the Model Context Protocol (MCP), the open standard whose current specification is dated 2026-07-28. You will inventory your campus systems, wrap each one as a thin MCP server that exposes tools rather than raw endpoints, put a broker in front of them for routing, caching and deny-by-default access control, and scope every call to the caller's FERPA role. You will then build a working cross-system agent on sample SIS and LMS data, embed it in an LMS course over LTI 1.3, and read the audit trail it produces. Why now: MCP authorization has stabilized on OAuth 2.1, and a 2026 survey of 130 campus CTOs found most institutions still waiting for AI to meet its return on investment. Integration is where that return lives.

About this course

Student information system integration is the bottleneck for every AI initiative on campus: the SIS holds enrollment and standing, the LMS holds grades and engagement, the CRM holds prospects and yield, and each speaks its own API and its own role model. This course teaches you to expose those systems to AI agents through the Model Context Protocol (MCP), the open standard whose current specification is dated 2026-07-28. You will inventory your campus systems, wrap each one as a thin MCP server that exposes tools rather than raw endpoints, put a broker in front of them for routing, caching and deny-by-default access control, and scope every call to the caller's FERPA role. You will then build a working cross-system agent on sample SIS and LMS data, embed it in an LMS course over LTI 1.3, and read the audit trail it produces. Why now: MCP authorization has stabilized on OAuth 2.1, and a 2026 survey of 130 campus CTOs found most institutions still waiting for AI to meet its return on investment. Integration is where that return lives.

What you will be able to do

  1. Produce a campus systems inventory that records, for each SIS, LMS and CRM, its API style, authentication model, rate limits and FERPA classification of every exposed field.
  2. Design and document an MCP server for one campus system with at least three tools, each carrying a policy block (roles, PII minimization, audit, deny by default).
  3. Configure OAuth 2.1 authorization for an MCP server, including Protected Resource Metadata, scope selection and client registration, and explain each requirement by its RFC.
  4. Map the FERPA "school official" conditions from the Department of Education's guidance onto concrete scopes, roles and audit requirements for a connector.
  5. Classify at least eight threats from the MCP lifecycle threat taxonomy and the OWASP agentic Top 10 and name the control that mitigates each.
  6. Build, run and audit a cross-system agent that answers an academic-standing question from sample SIS and LMS data, then embed it in an LMS course over LTI 1.3.

Who this course is for

Roles: campus IT directors and enterprise architects, integration and identity engineers, data stewards and FERPA compliance officers, and the functional leads (registrar, advising, enrollment management) who will own the first agent use case.

Institutions: any institution running a separate SIS, LMS and CRM: four-year publics and privates, community colleges, and system offices that integrate on behalf of campuses.

Before you start: working knowledge of REST APIs and OAuth 2.0, familiarity with your own SIS, LMS and CRM (for example Banner, Colleague, PeopleSoft or Workday Student; Canvas, Brightspace, Blackboard or Moodle; Slate or Salesforce), and a general understanding of FERPA. No machine-learning background is required. Labs use sample data, so no production credentials are needed.

Format

  • Estimated time: 14 to 16 hours.
  • Level: intermediate to advanced technical.
  • Hands-on: three labs (register a custom MCP server; build a cross-system academic-standing agent on sample SIS and LMS data with role scoping; embed via LTI 1.3 and read the audit log) plus an inventory template and a policy-block template you keep.
  • Structure: 4 sections, each ending in an AI conversation assessment, then a capstone assessment.

Self-paced. Every lesson is taught by an AI tutor that opens with a short story and works through one idea and one question at a time. Each section ends with an AI conversation assessment, and the course closes with a capstone assessment. Section assessments count for 60% and the capstone for 40%; 70% passes. There are no multiple-choice quizzes.

Currency of this course

Last verified 2026-09-28

Outline

  1. Section 0 · Start here

    • 0.1 Orientation

  2. Section 1 · The campus data problem and what MCP changes

    • 1.1 Why integrate instead of buying another point tool
    • 1.2 MCP in one hour
    • 1.3 Section 1 assessment

  3. Section 2 · Inventory and the data layer

    • 2.1 Inventorying SIS, LMS and CRM
    • 2.2 Designing tools, not endpoints
    • 2.3 Section 2 assessment

  4. Section 3 · Authorization, FERPA scoping and the broker

    • 3.1 OAuth 2.1 authorization in MCP
    • 3.2 The broker
    • 3.3 Threats and controls
    • 3.4 Section 3 assessment

  5. Section 4 · Build, embed and operate

    • 4.1 Hands-on labs
    • 4.2 Operating the layer
    • 4.3 Section 4 assessment

  6. Section 5 · Capstone & wrap-up

    • 5.1 Capstone
    • 5.2 Capstone assessment
    • 5.3 Wrap-up