Generative AI & Agentic AIMCP and integration contracts

Document an MCP server for a security reviewer

PK
Pankit Kumar
Sr. Data Scientist at Parexel (a Goldman Sachs–backed company) · 20 September 2026 · 2 min read
Technically reviewed by Ishaan Sharma
In this article (5 sections)

A reviewer needs the exposed capability and trust boundaries, not only installation steps. Document what the server can access, how authority flows and what tests support the controls.

Check a complete review record

The MCP contract lab builds an authored document.

python
from mcp_cases import security_review_case

result = security_review_case()
assert result["complete"] is True
assert result["approved"] is False
assert result["server_executed"] is False
assert result["document"]["writes"] == "none"
assert result["document"]["reviewer"] == "pending"

Complete fields do not mean approval or a running server.

Cover the trust model

Describe purpose, deployment, hosts, tools/resources/prompts, schemas, identities/delegation, credential storage, data classes/flows, access, writes/approvals, rate limits, logs/retention, dependencies and network boundaries.

Threats should include prompt injection, cross-tenant access, confused deputy/token passthrough, schema drift, secret leakage, excessive calls and supply-chain issues. Link contract, isolation, failure and adversarial tests plus unresolved findings.

Make review reproducible

Pin code/dependency/config versions, provide local run/test commands, architecture/data-flow diagrams and an inventory of external services. Separate automated results, reviewer comments and approval status. Define incident owner, rollback and reevaluation triggers.

The Generative & Agentic AI course uses this as the MCP deliverable’s evidence index.

Exercise

Write the package for a read-only server and conduct a mock review. Repair every unanswered trust-boundary question while keeping approval pending until authorized review.

Continue learning

This article is part of the MCP and integration contracts sequence. Use the neighbouring tasks when you need the prerequisite or the next application.

References: MCP security best practices and OWASP Agentic Security Initiative.

PK
Pankit Kumar
Lead Instructor, NeuraPath Academy

Pankit Kumar has 10 years in Data Science & AI, building and shipping production systems in regulated pharma and clinical environments. He is a freelance trainer at Boston Institute of Analytics, AnalytixLabs and Scaler, and has taught this material to thousands of working professionals.

This article is part of our Generative & Agentic AI programme — 3 months. Add practical GenAI, retrieval and agent-building skills to your existing toolkit.

Explore Generative & Agentic AI
Counselling is free · no obligation

Not sure which programme fits?

Tell us your background and we will map it to the right entry point — including saying so when a cheaper programme is the better fit. A counsellor replies within one working day.