Covers conformance fixtures, adversarial cases, quality metrics, budgets, monitoring, fallback, and incident review for analytics mcp server, so adopters can publish the governed analytics operations as discoverable MCP tools with strict input and output sc...
Package status: reference context ready for human review. The contract and test scenarios are complete, but no claim is made that an adopting implementation has passed them.
Decision
For Analytics MCP server, verify the contract under success, denial, failure, recovery, load, and drift so adopters can publish the governed analytics operations as discoverable MCP tools with strict input and output schemas and host-bound authorization. MCP is the protocol surface, not the security boundary; tool annotations and model behavior never replace gateway and database enforcement. This is a reference contract: database products, numeric budgets, jurisdictions, retention, organizational defaults, and accountable owners remain explicit adoption choices.
Scope
- The Analytics MCP server actors, inputs, outputs, states, versions, and externally visible outcomes needed to publish the governed analytics operations as discoverable MCP tools with strict input and output schemas and host-bound authorization.
- The role-specific focus of this block: verify the contract under success, denial, failure, recovery, load, and drift, including primary, cached, asynchronous, export, support, and recovery paths where applicable.
- Adoption-specific configuration, ownership, rollout, evidence retention, and review responsibilities needed to use the contract safely.
Outside this block
- MCP is the protocol surface, not the security boundary; tool annotations and model behavior never replace gateway and database enforcement.
- Choosing a universal database, model, renderer, vendor, numeric threshold, retention period, timezone, jurisdiction, or service-level objective.
- Claiming that packaged scenarios ran against a downstream implementation or that this reference grants security, privacy, accessibility, analytical, or legal approval.
Contract
- Verification evidence for Analytics MCP server must demonstrate this rule: The server exposes metrics.list, metrics.describe, entities.resolve, analytics.query, analytics.compare, analytics.breakdown, analytics.freshness, and bounded result retrieval.
- Verification evidence for Analytics MCP server must demonstrate this rule: No tool accepts arbitrary SQL, database names, table names, column names, connection strings, secrets, or unrestricted expression text.
- Verification evidence for Analytics MCP server must demonstrate this rule: Each tool has a human-readable title and description plus closed JSON input and output schemas; unknown properties and unsupported enum values are rejected.
- Verification evidence for Analytics MCP server must demonstrate this rule: Authentication and granted scopes arrive through the trusted MCP host or transport, and every call is authorized independently against the requested resource.
- Verification evidence for Analytics MCP server must demonstrate this rule: A read-only annotation may improve host UX but is treated as untrusted metadata and never as evidence that an operation is safe or authorized.
- Verification evidence for Analytics MCP server must demonstrate this rule: Structured content contains metric definitions, result values, quality, provenance, and stable errors; untrusted database values are sanitized before model context.
- Verification evidence for Analytics MCP server must demonstrate this rule: Long-running warehouse calls use explicit bounded task handles, status, cancellation, expiry, and authorization rechecks rather than implicit connection state.
- Verification evidence for Analytics MCP server must demonstrate this rule: Protocol version, tool schema version, metric plan version, server release, and correlation ID are observable for compatibility and incident review.
Implementation guidance
- Create paired positive and negative fixtures for each public operation, semantic rule, authorization boundary, and terminal state.
- Measure correctness, unsupported output, denial consistency, latency, resource use, and recovery by contract and implementation version.
- Inject dependency, policy, schema, freshness, cancellation, and audit failures before promoting the implementation beyond review.
- Keep human domain review for consequential interpretations and feed disagreements into versioned fixtures and rules.
Failure handling and safeguards
- For Analytics MCP server, A malformed call returns a protocol or schema error; a denied or over-budget analytical request returns a safe tool execution error the model can act on.
- For Analytics MCP server, Tool-list or schema drift fails compatibility checks and cannot silently change the meaning of a cached prompt or saved plan.
- For Analytics MCP server, An expired task handle, revoked authorization, or disconnected worker reaches a visible terminal state without exposing another caller's work.
Verification and operations
- For the testing evidence of Analytics MCP server, validate tools/list and tools/call against the negotiated MCP schema and reject unknown, oversized, injected, or type-confused arguments.
- For the testing evidence of Analytics MCP server, test authorization, tenant isolation, rate limits, output sanitization, handle opacity, cancellation, expiry, and replay on every tool.
- For the testing evidence of Analytics MCP server, use recorded protocol fixtures across supported client versions and prove deterministic tool ordering and compatible structured results.
Adoption assumptions
- The adopting product has authenticated identity, a versioned authorization policy, owned metric definitions, bounded telemetry, and a controlled path for change.
- Names and values in the example are fictional adoption fixtures, not universal defaults, production credentials, performance promises, or business targets.
- Referenced specifications constrain protocol, security, accessibility, or vendor behavior; the adopting team must confirm current applicability before promotion.
The executable-looking examples in this package are fixtures and acceptance contracts. Run the collection validator to check structure and metadata, then translate and execute the scenarios in the target repository before recording implementation evidence.
References
- Model Context Protocol 2026-07-28, Tools (applies as of 2026-09-12)
- Model Context Protocol 2026-07-28, Authorization (applies as of 2026-09-12)
- Model Context Protocol 2026-07-28, Security Best Practices (applies as of 2026-09-12)