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Glama

Coingecko

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

A4.9/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds critical behavioral details beyond annotations: partial failures degrade gracefully, bundlephobia's first measurement can take 5-30 seconds, and sources_failed will list timeout sources. 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?

Every sentence earns its place; the description is dense with useful information. It front-loads the main purpose and then details outcomes and caveats. Length is justified by the tool's composite nature.

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?

Despite no output schema, the description fully documents the return value: summary block with specific fields, per-advisory detail, links, and list of alternative versions. Also covers partial failure behavior and latency expectations. Complete for a composite tool.

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% (both parameters described). The description adds that scoped packages like '@types/node' are accepted and clarifies that version defaults to latest published when omitted. Although schema descriptions already cover the basics, the extra clarifications help avoid errors.

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 is a composite check for deciding whether to add an npm package, combining deps.dev (license + advisories + version history) and bundlephobia (bundle size, dependency count, ESM/tree-shake support). It provides specific example queries like 'is X safe / popular / small' and distinguishes from sibling tools (none overlap).

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" or "what does adding lodash cost me".' Also notes ecosystem limitation: 'NPM ecosystem only in v1; PyPI / Maven / Cargo / Go fall under 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

A3.6/5.0
Disambiguation2/5

Several tools are near-duplicates or have heavily overlapping responsibilities (ask_pipeworx / ask_pipeworx_beta / ask_pipeworx_grounded, polymarket_arbitrage / polymarket_edges / polymarket_fill_risk, and ai_visibility_check / scan_competitor_ai_presence). The many meta/entry-point tools (discover_tools, suggest_questions, pipeworx_trending) also blur the boundary between discovery and execution.

Naming Consistency2/5

Tool names mix imperative verb-first patterns (get_coin, search_coins, validate_claim) with noun-phrase labels (bet_research, entity_profile, pipeworx_trending, polymarket_edge_tracker) and inconsistent prefixes. Snake_case is consistent, but the naming grammar and verb styles are not.

Tool Count2/5

35 tools is well past the comfortable range, and the count feels inflated by duplicate routing modes, overlapping polymarket scanners, and generic memory/meta utilities. A server nominally named Coingecko carries only 4 crypto tools while the overwhelming majority belong to unrelated domains.

Completeness2/5

As a CoinGecko server, the surface is severely incomplete: search/get/market/trending exist but historical prices, OHLC, exchanges, categories, and coin details are missing. As a broader data/prediction-market utility it is more expansive, but the lack of a coherent domain makes coverage impossible to assess as a single product.

Resources