Skip to main content
Glama

zenquotes

by io.github.pipeworx-io

Entity Profile

entity_profile
Read-onlyIdempotent

"Tell me about X" / "research Acme" / "brief me on Tesla" / "what does Apple do" / "company profile for Microsoft" / "give me the rundown on NVDA" / "everything you know about $TICKER" — full cross-source profile of a US public company in ONE parallel call. ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view. Fans out across SEC EDGAR, XBRL, USPTO patents, federal contracts (USAspending), FDA-licensed biologics (Purple Book), H-1B hiring (DOL LCA), news and GLEIF, and returns: cik + company_name (+ resolved_from/resolved_to when value was a name); recent_filings (up to 5 with pipeworx://edgar/company/{cik}/filings/{accession} URIs); fundamentals (LATEST 10-K Revenues + NetIncomeLoss + Cash, sorted period_end DESC); patents (USPTO PatentsView API sunset May 2025 — soft-fails until reactivated); federal_contracts (USAspending awards where the company is the recipient); fda_products (FDA-licensed biologics — vaccines, cell/gene therapies — from the Purple Book; a company with only small-molecule/generic drugs will show none here, that is expected, not a failure); hiring (H-1B sponsorship volume + salary range from DOL LCA filings); recent news mentions via GDELT→GNews fallback; LEI via GLEIF. sources_used / sources_failed say which of these actually returned data for THIS company — an empty section is a real "no data", not a bug. Pass a ticker ("AAPL"), zero-padded CIK ("0000320193"), OR a company name ("Moderna") — names now resolve via SEC EDGAR's company-name match; a private company (no CIK/ticker) returns resolved:false with an explicit notes line, not a bare failure. type accepts "company" or "ticker" interchangeably — both take the same value shapes above.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYes"company" or "ticker" — both are accepted and behave identically; `value` can be a ticker, CIK, or company name either way. person/place coming soon.
valueYesTicker (e.g., "AAPL"), zero-padded CIK (e.g., "0000320193"), or company name (e.g., "Moderna") — names resolve via SEC EDGAR company-name match.

Schema Changelog

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

  1. Changed3 schema fields changed
    • changedInput schema / properties / type / description
      Previous value: -"Entity type. Only \"company\" supported today; person/place coming soon."New value: +"\"company\" or \"ticker\" — both are accepted and behave identically; `value` can be a ticker, CIK, or company name either way. person/place coming soon."
    • changedInput schema / properties / type / enum
      Previous value: -[
-  "company"
-]New value: +[
+  "company",
+  "ticker"
+]
    • changedInput schema / properties / value / description
      Previous value: -"Ticker (e.g., \"AAPL\") or zero-padded CIK (e.g., \"0000320193\"). Names not supported — use resolve_entity first if you only have a name."New value: +"Ticker (e.g., \"AAPL\"), zero-padded CIK (e.g., \"0000320193\"), or company name (e.g., \"Moderna\") — names resolve via SEC EDGAR company-name match."
  2. Added

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnly/openWorld/idempotent/non-destructive, so the bar is lower, but the description still adds rich behavioral context: it fans out across many named sources, reports sources_used/sources_failed, treats empty sections as real no-data, soft-fails on the USPTO sunset, and explains expected empty FDA results. This is far beyond what the annotations alone convey.

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 long, but for a multi-source, ten-section tool every clause carries functional information such as source lists, failure modes, and return shapes. It is front-loaded with examples and the 'ALWAYS PREFER' directive; slight redundancy around name resolution and source enumeration keeps it from a perfect 5.

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 the tool's complexity, no output schema, and multiple sources, the description is exceptionally complete: it lists all returned sections, explains fallback chains, defines empty-result semantics, and documents both input variants and edge cases like private companies. An agent has enough to select and invoke this tool correctly without needing additional context.

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%, so the baseline is 3, but the description meaningfully supplements the schema: it gives concrete examples (AAPL, 0000320193, Moderna), clarifies that 'type' accepts either 'company' or 'ticker' interchangeably, and notes that names resolve via SEC EDGAR. That extra guidance helps an agent choose correct inputs.

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 opens with concrete user phrasings ('Tell me about X', 'brief me on Tesla') followed by a crisp statement of the tool's job: 'full cross-source profile of a US public company in ONE parallel call.' It clearly distinguishes itself from chaining single-pack SEC/XBRL/news lookups, so an agent can tell it apart from siblings like resolve_entity or compare_entities.

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 explicitly says 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view,' giving a direct when-to-use rule. It also covers the private-company case by describing the resolved:false behavior with an explicit notes line rather than a bare failure.

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

All zenquotes 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

A4/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, and the heavy overlap between ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research is mitigated by detailed usage guidance. A few pairs like ai_visibility_check vs scan_competitor_ai_presence or discover_tools vs suggest_questions could confuse an agent, but the descriptions generally draw clear boundaries.

Naming Consistency3/5

Names are all lowercase snake_case and several families are consistent (ask_pipeworx*, polymarket_*), but the overall set mixes styles: verb_noun such as list_quotes and resolve_entity, adjectival noun phrases such as random_quote and today_quote, and bare nouns like entity_profile and recent_changes. The patterns are readable but not predictable.

Tool Count2/5

34 tools is well above the 25+ threshold for 'too many,' and the server name zenquotes suggests a much smaller quote-focused surface. The count is defensible for a broad data gateway, but as a unified server it feels overstuffed with many unrelated feature areas.

Completeness4/5

The combined surface is quite complete for its apparent scope: quote retrieval, query/research, grounding, entity resolution, comparisons, change feeds, subscriptions, memory, and prediction-market analysis are all covered. Minor gaps exist, such as no direct quote search and no explicit tool for fetching a pipeworx:// citation URI.

Resources