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Glama

Texas DMV

by io.github.pipeworx-io

Scan Dependency

scan_dependency
Read-onlyIdempotent

Composite "should I add this npm package to my project" check in ONE call — fans out across deps.dev (license + advisories + version history) and bundlephobia (gzipped/minified bundle size, dependency count, ESM/tree-shake support). Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me". Returns a summary block (is_latest, license, published_at, advisory_count, bundle_kb_min, bundle_kb_gz, dependency_count, has_esm, tree_shakeable), per-advisory detail, links, and a list of recent alternative versions. NPM ecosystem only in v1; PyPI / Maven / Cargo / Go fall under deps.dev:version directly. Partial failures degrade gracefully — bundlephobia's first measurement on a new version can take 5-30s; sources_failed will list it if it times out, the rest still returns.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
packageYesnpm package name. Scoped packages (e.g. "@types/node") are accepted.
versionNoSpecific version to check (e.g., "18.3.1"). Defaults to the latest published version when omitted.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations indicate readOnly, openWorld, idempotent, non-destructive. Description adds behavioral context: fans out across two services, bundlephobia first measurement can take 5-30s, sources_failed lists timeouts, partial failures degrade gracefully. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured: first sentence states purpose, then sources, usage, output summary, scope, failure handling. Front-loaded with key verb and resource. Every sentence adds value despite length.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, so description must cover output format. It does: summary block with specific fields, per-advisory detail, links, and recent alternatives. Also covers ecosystem limitation and partial failure behavior.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema describes both parameters (package, version) with 100% coverage, including default behavior. Description adds minimal extra parameter info (scoped packages accepted) but confirms schema details. Baseline 3 is appropriate as schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs a composite check for npm packages combining deps.dev and bundlephobia data, answering questions about safety, popularity, and size. It distinguishes from siblings by noting other ecosystems use deps.dev:version directly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use: when asked 'is X safe/popular/small' or 'what does adding lodash cost me'. Also specifies when not to use: for non-NPM ecosystems (PyPI/Maven/Cargo/Go) use deps.dev:version directly.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.5/5.0
Disambiguation2/5

Several tools occupy nearly interchangeable roles: ask_pipeworx and ask_pipeworx_beta are explicitly identical, while ask_pipeworx_grounded, deep_research, and validate_claim all route similar factual queries. discover_tools/suggest_questions and bet_research/polymarket_edges similarly overlap, so an agent needs to read long descriptions to avoid misselection.

Naming Consistency3/5

All names are readable lowercase snake_case, but the conventions are mixed: imperative verb_noun names (list_subscriptions, validate_claim) sit alongside noun phrases (polymarket_edges, recent_alerts), bare verbs (forget, subscribe), and variant suffixes (ask_pipeworx_beta/grounded). It is not chaotic, but there is no single predictable naming pattern.

Tool Count2/5

Thirty-two tools is far more than the apparent Texas DMV scope supports: only tx_dmv_vehicle_registrations is DMV-related, and the rest are Pipeworx platform, prediction-market, memory, and unrelated utility tools. The count is excessive for the server's stated name and purpose.

Completeness1/5

The Texas DMV surface is severely incomplete: a single statewide registration-count tool covering fiscal years 2001-2021, with no title/registration transactions, VIN lookup, driver services, county/ZIP breakdowns, or current data. The tool's own description references a California DMV companion that is not present, leaving obvious gaps for any realistic DMV workflow.

Resources