Build contract tests for an external tool integration
In this article (5 sections)
An integration can compile while the provider changes a field, error or timeout behaviour. Contract tests protect the application-facing adapter independently from model output.
Run six offline checks
The MCP contract lab stores six deterministic outcomes.
from mcp_cases import contract_tests_case
result = contract_tests_case()
assert result["passed"] == 6
assert result["total"] == 6
assert result["all_pass"] is True
assert result["tests"]["no_network_fixture"] is TrueThe cases cover valid request, unknown metric, missing scope, output schema, timeout mapping and offline execution. This validates a fixture list, not a real API.
Test your adapter contract
Hide provider details behind a small interface. Use authored/sanitized fixtures for ordinary CI and a separate controlled compatibility check for the live service. Test request serialization, response validation, structured errors, pagination, retries and idempotency.
Include authentication/authorization and cross-tenant denials. A 200 status with malformed business data must fail. A provider exception should map to a stable internal code without leaking tokens.
Detect drift deliberately
Pin SDK/API versions where possible and run live contract checks on schedule or before upgrades. Save response schemas/digests under policy. Do not turn a live sandbox success into model-quality evidence.
The Generative & Agentic AI course uses contract tests to separate reliable plumbing from AI behaviour.
Exercise
Build ten offline fixtures and three controlled live compatibility checks for one API. Break a field type and verify CI fails before data reaches a model.
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.
- Review the prerequisite or neighbouring task in Rate-limit tools by user and tenant.
- Continue with Expose business errors as structured tool results.
Reference: Pact contract testing documentation.
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.
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