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Glama

Ipify

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. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already mark the tool as readOnly, idempotent, and non-destructive, lowering the burden. The description goes well beyond by disclosing the parallel fan-out across many sources, GDELT→GNews fallback, USPTO API sunset soft-fail behavior, resolved_from/resolved_to semantics, and the meaning of empty sections and sources_used/sources_failed. This is rich behavioral context with no contradiction to the annotations.

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 densely packed with relevant information for a complex multi-source tool. It is front-loaded with examples and a priority directive. However, the single run-on paragraph structure makes scanning harder than it needs to be; bullet points or section breaks would improve readability without adding length.

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?

With no output schema, the description carries the full burden of explaining the return shape. It enumerates every output section (cik, company_name, recent_filings with URIs, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI, sources_used/failed) and clarifies no-data and failure semantics. An agent has enough context to invoke the tool and interpret its results correctly.

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. The description adds meaningful semantics beyond the schema: it specifies zero-padded CIK format, notes that names resolve via SEC EDGAR company-name match, and explains that 'type' values 'company' and 'ticker' are interchangeable. This extra context helps an agent construct valid inputs more confidently.

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 states the tool's purpose: producing a 'full cross-source profile of a US public company in ONE parallel call,' and opens with concrete user-phrase examples ('Tell me about X', 'research Acme', 'brief me on Tesla'). It also differentiates itself from alternatives by explicitly prioritizing this tool over chaining single-pack SEC/XBRL/news lookups for holistic views.

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 gives explicit when-to-use guidance: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view.' It also clarifies interpretation edge cases, such as private companies returning resolved:false and empty FDA sections being expected rather than failures, which helps the agent decide when and how to use the tool correctly.

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

A3.6/5.0
Disambiguation2/5

Multiple tools overlap conceptually, e.g., ask_pipeworx / ask_pipeworx_beta / ask_pipeworx_grounded / deep_research all perform data retrieval, and bet_research / polymarket_edges / polymarket_arbitrage cover prediction markets with unclear boundaries. This overlap forces agents to carefully read descriptions to pick the right tool.

Naming Consistency3/5

Naming is mostly snake_case but inconsistent in pattern: some are verb_noun (compare_entities), some are noun_verb (ai_visibility_check), and some are bare nouns (ipv4) or bare verbs (forget). While readable, the lack of a uniform pattern reduces predictability.

Tool Count2/5

33 tools is high for a single server, especially given the server name 'Ipify' which implies a simple IP lookup service. The broad range (from memory ops to prediction market analysis) suggests the tool set is a collection of utilities rather than a coherent, scoped API.

Completeness2/5

The tool set lacks focus: for a server named 'Ipify', basic IP geolocation or ASN lookup is missing. As a general toolkit, it covers many areas superficially but has significant gaps (e.g., no tools for updating or deleting data, no domain-specific lifecycle).

Resources