VASTlint, from AleksUIX, is an MCP server and validation suite that checks VAST XML for advertising delivery failures. The tool parses VAST and related tag formats, exposes machine-callable audit operations for agentic workflows, and surfaces rule-level issues for human review. It pairs a high-performance validation engine with deterministic repair routines and targets ad-tech developers, QA engineers, and trafficking teams needing traceable validation inside delivery pipelines.

What tasks it actually performs in ad delivery workflows

More than 230 IAB-derived rules drive the validator, with each rule mapped to IAB Tech Lab and relevant RFC specifications for traceability. The tool classifies malformed XML and tag-level violations so teams can prioritise fixes by delivery impact. As an MCP-accessible service, it enables automated auditing of creatives where rule-level traceability matters for maintaining impression delivery.

How it integrates with developer and agent toolchains

The implementation supports direct use from agent clients and developer tools: MCP clients such as Claude Desktop and Cursor, a cross-platform CLI (macOS, Linux, Windows), a VS Code extension, and language bindings for Python, Go, Node.js, and Elixir. These bindings reduce integration friction for CI/CD pipelines and programmatic trafficking systems that need linting before ad serving.

How outputs behave under operational constraints

Validation reports return granular findings rather than binary pass/fail results, which suits QA workflows that require actionable remediation. Error reports reference the originating specification entries to make corrective work measurable. The developer’s zero-dependency, performance-focused implementation supports high-throughput environments where per-request validation latency must be low.

Where automated repairs help and where human review remains necessary

The tool includes deterministic repair routines for common, well-scoped issues, for example normalising non-HTTPS URLs and fixing certain schema inconsistencies. Those repairs are labelled experimental and intended for low-risk fixes; complex or ambiguous violations still require human review because automatic changes cannot cover every creative or business rule nuance.

Practical choice for integration-focused ad-tech teams with human-in-the-loop checks

VASTlint is a solid option for teams that need machine-readable, traceable validation built into agentic or CI workflows, anchored to formal IAB and RFC rules. Expect to pair its machine findings with human review for ambiguous or business-specific cases, since automated repairs are scoped to deterministic fixes and do not replace manual QA on complex creatives.