Skip to main content
Glama

Stat Ee

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?

Even with readOnly/openWorld/idempotent annotations, the description adds substantial behavioral context: soft-failures (USPTO sunset), expected empty sections (FDA products for small-molecule-only companies), resolved_from/resolved_to, and sources_used/sources_failed semantics. No contradiction with 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 and dense, but every clause contributes — return-section semantics, edge cases, and input handling. It is front-loaded with examples and purpose. Slightly better structure (bullets) would improve scannability, but the content 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?

With no output schema, the description carries full responsibility for return values, and it delivers: it enumerates all response sections, explains empty vs failed sources, covers input variants and edge cases. An agent has enough to invoke correctly and interpret results without guessing.

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 baseline is 3. The description adds meaning beyond the schema by explaining that names resolve via SEC EDGAR, that zero-padded CIKs are expected, and that private companies return resolved:false with a notes line rather than a hard failure.

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 states 'full cross-source profile of a US public company in ONE parallel call' — a specific verb, resource, and scope. It also distinguishes itself from an alternative class of lookups ('ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups').

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?

It explicitly says when to prefer this tool ('when the user asks for a holistic view') and names the alternative approach it should replace. It also gives clear input guidance for ticker, CIK, or company name, and describes the resolved:false behavior for private companies.

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

All Stat Ee 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

A3.9/5.0
Disambiguation3/5

Most tools have fairly distinct action/resource targets and the descriptions carefully separate entry points like ask_pipeworx, deep_research, and ask_pipeworx_grounded. However, ask_pipeworx_beta is explicitly an identical clone of ask_pipeworx right now, and a few related pairs (ai_visibility_check vs scan_competitor_ai_presence, stat_ee_find_table fetch_latest vs estonia_average_wage) add ambiguity.

Naming Consistency3/5

Names are consistently lowercase snake_case and verb-led names like resolve_entity, query_table, and suggest_questions are clear. But the set mixes conventions: bare nouns (subjects, recall, forget), adjective-noun phrases (recent_alerts, recent_changes), no-verb names (estonia_average_wage, table_meta), and multiple prefixes (pipeworx_*, polymarket_*, stat_ee_*). It is readable but not a single predictable pattern.

Tool Count2/5

36 tools is well above the 15-tool threshold for a well-scoped server, and the set spans many unrelated domains: Estonian statistics, Pipeworx research, Polymarket betting, AI visibility, npm scanning, memory, and subscriptions. There is also clear redundancy (ask_pipeworx_beta duplicates ask_pipeworx, ai_visibility_check could be folded into scan_competitor_ai_presence). This feels scattered for a server named 'Stat Ee'.

Completeness4/5

For the broad data-research/agent-assistant purpose, key workflows are well covered: discovery/query/grounded/deep research, entity resolution/profile/compare/validate/recent changes, complete memory CRUD, subscription CRUD with alert feeds, and a full Polymarket edge/arb/fill-risk suite. The main gap is not missing operations within these workflows but rather the overall scope being too broad and unfocused.

Resources