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Glama

Pubchem

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").

Schema Changelog

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

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds significant behavioral context: it fans out to SEC EDGAR, GDELT→GNews fallback, and USPTO (with PatentsView sunset note). This goes beyond annotations to explain how the tool operates.

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?

The description is concise and front-loaded with example queries, making the purpose immediately clear. Every sentence contributes valuable information. It is not overly verbose, though it could be slightly more structured with bullet points or explicit sections.

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 tool's moderate complexity (multiple sources, fallback, no output schema), the description covers input format, source behavior, and return structure (changes array with URIs). It also references the alternative tool 'entity_profile'. However, it lacks details on error handling or rate limits.

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?

All three parameters are fully described in the schema (100% coverage). The description enhances this by providing format examples for 'since' (ISO dates and relative shorthand), explaining that 'value' accepts ticker or CIK, and noting that 'type' is limited to 'company'.

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 defines the tool as a change feed for a company over a time window, using concrete example queries like 'What's new with X' and 'latest on Y'. It distinguishes itself from the sibling tool 'entity_profile' by explicitly stating when to use the alternative for static profiles.

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?

The description provides explicit guidance: use for recent changes within a window, and use 'entity_profile' for static profiles. It details fallback logic across multiple sources and gives typical usage for the 'since' parameter (e.g., '30d' or '1m'), making it easy for the agent to decide when and how to invoke.

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

All Pubchem toolsInspect
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TDQS

A3.6/5.0
Disambiguation2/5

Many tools overlap heavily: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all answer factual questions through similar routing; the polymarket_* tools and entity_profile/compare_entities/recent_changes also cover the same ground. The server is named Pubchem but most tools are unrelated, adding another layer of confusion.

Naming Consistency4/5

All tool names are snake_case and mostly follow verb_noun (search_by_name, get_compound, create_subscription, etc.). Minor deviations exist like entity_profile and recent_alerts being noun-first, and the pipeworx_*/polymarket_* prefixes make the set feel more like multiple products than one coherent API.

Tool Count2/5

35 tools is a large surface, and only 4 (search_by_name, get_compound, get_classification, get_synonyms) actually belong to PubChem. The other 31 tools form a broad Pipeworx/prediction-market toolkit that seems unrelated to the server's stated name and purpose.

Completeness2/5

For a PubChem server the coverage is minimal: basic name->CID resolution, compound properties, classification, and synonyms, but no formula search, bioassay, spectra, or list/search by other identifiers. The Pipeworx tools are extensive for general data querying but require accounts/keys for full use, so anonymous agents hit incomplete workflow dead ends.

Resources