Skip to main content
Glama

Dockerhub

by io.github.pipeworx-io

Recent Changes

recent_changes
Read-onlyIdempotent

"What's new with X" / "latest on Y" / "what happened to Z this week / month / quarter" / "updates on Acme" / "news on Tesla recently" / "what's happening with Apple" — change feed for a company in the last N days/weeks/months in ONE parallel call. Fans out to SEC EDGAR (filings since since), GDELT→GNews fallback (news mentions in window — GDELT preferred, GNews when rate-limited or 5xx), USPTO (patents granted; PatentsView API sunset May 2025 so this soft-fails until reactivated). since accepts ISO date ("2026-04-01") or relative shorthand ("7d", "30d", "3m", "1y"). Returns structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs. Use entity_profile instead when you want the static profile (filings + fundamentals + LEI + patents) regardless of window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesEntity type. Only "company" supported today.
sinceYesWindow start — ISO date ("2026-04-01") or relative ("7d", "30d", "3m", "1y"). Use "30d" or "1m" for typical monitoring.
valueYesTicker (e.g., "AAPL") or zero-padded CIK (e.g., "0000320193").

TDQS

A4.4/5.0
Behavior5/5

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

Discloses multi-source fan-out, fallback from GDELT to GNews, USPTO soft-fail, output structure (changes grouped by source, total_changes, citation URIs). Complements annotations with behavioral context.

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

Conciseness3/5

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

Description is thorough but verbose; includes extensive examples and fallback details. Front-loaded with user query examples, but could be more concise by moving some details to parameter descriptions or output schema.

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

Completeness4/5

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

Given no output schema, the description adequately covers return structure and source behavior. Parameter schema coverage is 100%, so description does not need to compensate much. Complete for a multi-source aggregation 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?

Adds meaning beyond schema: explains 'since' accepts ISO or relative with examples, 'value' can be ticker or CIK, 'type' only company. Provides usage guidance for typical monitoring interval.

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?

Clear verb+resource: 'change feed for a company'. Distinguishes from sibling 'entity_profile' by contrasting static vs. dynamic profile. Lists multiple sources and query examples.

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

Usage Guidelines4/5

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

Explicitly states when to use (e.g., 'What's new', 'latest on Y') and when not to (use entity_profile for static profile). Provides alternative tool name. Could be more detailed on when not to use.

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

All Dockerhub 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

A3.6/5.0
Disambiguation2/5

Many tools overlap in purpose, e.g., ask_pipeworx, ask_pipeworx_grounded, deep_research, entity_profile, and validate_claim all perform data lookups with subtle differences. Polymarket tools also have overlapping scopes. The large number of tools with similar functions creates confusion.

Naming Consistency3/5

Names are inconsistent: some use verb_noun (get_image, list_subscriptions), others are descriptive phrases (ai_visibility_check, bet_research), and some are single words (forget, recall). No clear pattern.

Tool Count2/5

33 tools is high, and many are unrelated to Dockerhub. The server name suggests a focused Docker toolset, but the bulk of tools are for Pipeworx/Polymarket/data lookups, making the count excessive for the advertised domain.

Completeness2/5

As a Dockerhub server, it lacks basic Docker operations like push, delete, or manage repositories. As a general data toolset, it covers many domains but still misses some core operations (e.g., no tool for searching inside images).

Resources