Skip to main content
Glama

Epa Emissions

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.

TDQS

A4.8/5.0
Behavior5/5

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

Beyond annotations (readOnly, idempotent), description adds details on fan-out, partial failure handling, bundlephobia timeout, and what the tool returns. No contradiction with annotations.

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

Conciseness4/5

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

Single paragraph that is dense but well-organized. Could benefit from a list for return fields but still concise and front-loaded.

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?

Even without an output schema, the description fully details the return structure (summary block, advisories, links, alternatives). Covers edge cases (partial failures, ecosystem scope).

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

Parameters4/5

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

Schema coverage is 100%, but description adds value by noting scoped packages are accepted (not in schema) and that version defaults to latest. Slightly exceeds baseline.

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 it's a composite check for npm packages, fanning out across deps.dev and bundlephobia, and lists what it returns. It distinguishes from siblings by being npm-specific.

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 says 'Use whenever an agent asks "is X safe / popular / small"' and notes ecosystem limitation and alternative for other ecosystems.

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

All Epa Emissions toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

B3.3/5.0
Disambiguation3/5

The tool set contains multiple groups with overlapping purposes (e.g., ask_pipeworx/ask_pipeworx_grounded/deep_research for data queries, multiple Polymarket tools, and memory tools). However, detailed descriptions help differentiate them, so ambiguity is moderate but not severe.

Naming Consistency2/5

Naming conventions are inconsistent: some tools follow verb_noun (ask_pipeworx, compare_entities), others use domain-prefixed noun_verb (ghg_emissions_by_sector, polymarket_arbitrage). This mix, combined with a server name that doesn't match the tool domain, makes the naming pattern unclear.

Tool Count1/5

With 35 tools, the server is overloaded, especially given its name 'Epa Emissions' which suggests a narrow focus. Only 5 tools (ghg_*, tri_*) are related to emissions; the rest are unrelated, making the count inappropriate for the server's assumed purpose.

Completeness2/5

For an EPA/emissions server, the tool set is incomplete: it lacks other emissions data (e.g., air quality, water quality, enforcement). The inclusion of many unrelated tools (e.g., Polymarket, memory) does not compensate for missing core emissions coverage.

Resources