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Emdb

by io.github.pipeworx-io

Pipeworx Trending

pipeworx_trending
Read-onlyIdempotent

What other AI agents are calling on Pipeworx right now. Returns the top tools, top packs, and total call volume over a recent window (24h, 7d, or 30d). Useful for: (1) discovering what data sources are hot for current events, (2) confirming a popular tool is the canonical choice before asking your own question, (3) seeing whether your use case aligns with what most agents need. Self-aggregating signal — derived from CF analytics-engine, no PII, just (pack, tool, count). Cached 5min-1h depending on window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
windowNo24h (default) | 7d | 30d. Shorter windows surface what's hot right now; longer windows show steady-state demand.

Schema Changelog

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

  1. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive hints. The description adds valuable context: data derivation from CF analytics-engine, no PII, cached 5min-1h, and the granularity (pack, tool, count). This goes beyond what annotations provide.

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?

The description is concise at three sentences, each serving a clear purpose: main function, use cases, and behavioral details. It is front-loaded with the primary output, no wordiness, and every sentence adds value.

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 the simple input (1 optional enum) and lack of output schema, the description adequately covers input behavior, data source, and caching. However, the output format (shape of the returned data) is only hinted at ('top tools, top packs, total call volume') but not precisely specified, which would improve completeness.

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?

The sole parameter 'window' has 100% schema coverage with an enum description. The description adds semantics by explaining the effect of different windows ('hot right now' vs. 'steady-state demand'), which is not captured in the schema alone.

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

Purpose4/5

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

The description clearly states the verb ('Returns') and resource ('top tools, top packs, and total call volume') and specifies the window parameter. It distinguishes from siblings by focusing on trending data from other agents, but does not explicitly contrast with similar tools like 'discover_tools' or 'search_within'.

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?

Three concrete use cases are enumerated, and the window parameter is explained with guidance on short vs. long windows. However, no mention is made of when not to use the tool or alternatives, which would be helpful given the large number of sibling tools.

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

A3.7/5.0
Disambiguation2/5

Multiple tool clusters have overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical (the beta is explicitly the same right now); five polymarket_* tools all surface opportunity/edge information; entity_profile, compare_entities, and recent_changes all cover company research. The descriptions are detailed, but an agent can easily misselect between similar tools.

Naming Consistency4/5

All tool names use consistent snake_case and are descriptive, with clear prefix patterns for prediction-market tools (polymarket_*) and the router variants (ask_pipeworx_*). Some names are verb-noun while others are noun-phrases, but the convention is uniformly underscore-separated, with no camelCase or other mixing.

Tool Count2/5

33 tools is excessive for a coherent server, and the scope is sprawled across EMDB access, Pipeworx data routing, prediction markets, memory, subscriptions, and miscellaneous utilities. Even though each tool has a defined role, the sheer breadth and number make it feel like several servers' worth of functionality crammed into one.

Completeness2/5

The server's name suggests it should be focused on EMDB, but only two tools (get_map, search_maps) cover that domain — no browsing, filtering, or extended metadata beyond basic fields. Meanwhile, the bulk of the surface is devoted to unrelated Pipeworx/platform features. For the stated purpose, the coverage is severely incomplete.

Resources