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Glama

Amplitude

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

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior, so the bar for added value is lower. The description still adds substantial behavioral context: fan-out sources, sources_used/sources_failed semantics, USPTO soft-fail after sunset, expected empty fda_products for non-biologic companies, and resolved:false handling for private companies.

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 informative, with front-loaded examples and a complete returns catalog. It is somewhat overstuffed into a single paragraph and has minor redundancy, but every major clause earns its place.

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?

There is no output schema, so the description must carry the burden of explaining return values. It enumerates every response section (cik, filings, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI), explains empty-section semantics, and covers edge cases like private companies and source failures.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage for both parameters is 100%, so the schema already documents type and value semantics. The description adds examples and restates that names resolve via SEC EDGAR, but it does not reveal genuinely new parameter-level meaning beyond what the schema provides.

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 and defines the tool as a 'full cross-source profile of a US public company in ONE parallel call.' It names the resource and explicitly contrasts with chaining single-pack lookups, so an agent can tell it apart from narrower tools.

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 to 'ALWAYS PREFER' this tool over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view. It also scopes use to US public companies and explains the private-company resolved:false behavior, leaving little ambiguity about when to call it.

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

A3.5/5.0
Disambiguation2/5

Several tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta (currently identical), ask_pipeworx_grounded, deep_research, and validate_claim all answer natural-language questions over the same underlying data sources. ai_visibility_check and scan_competitor_ai_presence also overlap as single vs. comparative variants. The detailed descriptions help, but the boundaries between the query/research tools remain genuinely ambiguous for an agent.

Naming Consistency2/5

No consistent global naming convention. There are prefix families (amp_*, pipeworx_*, polymarket_*) but within them the structure varies (amp_get_events vs amp_user_search; ask_pipeworx vs polymarket_fill_risk), and many tools are bare verbs or noun phrases (remember, recall, forget, bet_research, search_within, recent_alerts). The mix of verb-first and noun-first names with irregular prefixes makes predicting tool names unreliable.

Tool Count2/5

36 tools is too many for the server's nominal purpose: only 5 of them (amp_*) relate to Amplitude analytics, while the other 31 form a sprawling all-in-one data/research/prediction-market platform. Even accepting that broader scope, many tools could be consolidated (ask_pipeworx_beta duplicates ask_pipeworx, several polymarket tools are specialized but still numerous), making the count feel padded rather than focused.

Completeness3/5

The Pipeworx side is thorough: lookups, grounded verification, deep research, entity profiles, comparisons, subscriptions, and memory cover most of that domain well. However, the Amplitude analytics side is thin — it only queries events, active users, retention, and user activity, with no way to manage projects, cohorts, event definitions, or user properties. There is also no general web search tool and no direct database/SQL exploration, leaving notable gaps for the advertised all-in-one positioning.

Resources