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Glama

Feodotracker

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. Added

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare safe traits (readOnly, idempotent, etc.). Description adds valuable behavioral context: composite nature, graceful degradation with sources_failed, and bundlephobia's 5-30s measurement delay. No contradiction.

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?

Description is relatively long but every sentence serves a purpose. Front-loaded with core purpose and use case, then provides details on behavior and return format. Could be slightly tighter, but still efficient.

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?

Given no output schema, description explains return structure (summary block, advisories, links, alternative versions). It covers complexity of the composite call, partial failures, and ecosystem limitations, making it complete for agent usage.

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% with clear parameter descriptions. Description adds practical usage notes (scoped packages accepted, default version to latest). This adds minor but helpful context beyond schema.

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?

Description clearly states it performs a composite check for deciding to add an npm package, fanning out across deps.dev and bundlephobia. It specifies the exact resource (npm package) and action (scan), and distinguishes from sibling tools like deps.dev for other ecosystems.

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 provides use cases: 'is X safe / popular / small' or 'what does adding lodash cost me'. Also notes NPM-only in v1 and directs PyPI/Maven etc. to deps.dev:version. Includes behavior on partial failures and timing.

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

All Feodotracker toolsInspect
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TDQS

A3.5/5.0
Disambiguation2/5

Multiple near-duplicate clusters exist: ask_pipeworx, ask_pipeworx_beta (explicitly identical to the stable router right now), and ask_pipeworx_grounded all route through the same 5,767-tool catalog, and six polymarket_* tools overlap heavily in surfacing bet/edge opportunities. The blocklist tools (list, recent, aggressive) are only weakly distinguished by time window and confidence, requiring careful reading to select correctly.

Naming Consistency2/5

Naming mixes several incompatible conventions: bare adjectives/nouns for blocklist tools (aggressive, list, recent), brand-prefixed compounds (polymarket_arbitrage, pipeworx_feedback), verb_noun pairs (check_ip, resolve_entity), and noun phrases (entity_profile, bet_research). The server name 'Feodotracker' appears nowhere in the tool names, and the blocklist cluster uses a completely different style from the data cluster.

Tool Count2/5

At 35 tools, the count exceeds the 25-tool threshold for 'too many', but the deeper issue is that roughly 31 tools serve a general data-lookup/prediction-market platform while only 4 serve the server's stated Feodotracker blocklist purpose. The count reflects two unrelated products merged into one MCP server rather than a well-scoped tool surface.

Completeness2/5

For the named Feodotracker domain, the surface is thin: list/check/recent cover basic blocklist access but miss historical lookups, per-entry threat intel, or export formats that a botnet tracker would need. For the data-lookup domain the 31-tool suite is impressively complete, but the two domains don't form a coherent whole—each leaves the other's lifecycle half-served.

Resources