Skip to main content
Glama

Obis

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

A4.4/5.0
Behavior5/5

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

Rich behavioral disclosure far beyond the annotations: fan-out across 8 named sources, sources_used/sources_failed semantics ('an empty section is a real no data, not a bug'), private-company resolved:false behavior with notes line, FDA small-molecule/generic drugs showing none being 'expected, not a failure,' LATEST-10-K fundamentals semantics, and pipeworx:// filing URIs. These details preempt common agent misinterpretations of empty or sparse results. No contradiction with readOnlyHint/idempotentHint/openWorldHint.

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?

Well-structured and front-loaded: trigger phrases and purpose come first, then preference directive, fan-out, return semantics, edge cases, and parameter handling. At roughly 280 words it is long, but nearly every sentence earns its place since there is no output schema to carry return-value documentation. Minor redundancy exists where the description repeats schema content (type interchangeability, EDGAR name resolution), which could be trimmed.

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?

For a tool of this complexity — 8 fan-out sources, 2 required params, no output schema — the description is remarkably complete. It covers purpose, trigger phrasing, when to prefer it, every return section, sources_used/sources_failed interpretation, input format variants, URL format, and edge cases (private company, expected-empty FDA section). Only minor gaps exist (non-US company behavior, news time ranges), which is negligible given the breadth covered.

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 description coverage is 100%, so the baseline is 3 and the schema already documents both parameters well: type's company/ticker interchangeability and value's ticker/CIK/name forms with EDGAR name resolution. The description mostly restates this rather than adding new parameter-level meaning; novel details like resolved_from/resolved_to and private-company handling concern return behavior, not parameter semantics. The description thus earns the baseline but does not exceed it.

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 states a precise verb+resource+scope: 'full cross-source profile of a US public company in ONE parallel call,' anchored by seven concrete trigger phrases ('Tell me about X', 'brief me on Tesla', 'give me the rundown on NVDA'). It distinguishes itself from the alternative pattern of chaining single-pack SEC/XBRL/news lookups, giving an agent a clear identity for the tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly directs usage: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view,' and the trigger phrases clarify when this intent is present. However, it names no sibling alternatives for overlapping cases (e.g., deep_research for broader research, resolve_entity for entity-only resolution, compare_entities for comparisons), and gives no explicit when-not-to-use guidance beyond the implicit single-pack contrast.

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

All Obis 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

A3.7/5.0
Disambiguation2/5

Several tool clusters have unclear boundaries, most notably ask_pipeworx / ask_pipeworx_beta (which currently matches ask_pipeworx exactly) / ask_pipeworx_grounded, as well as bet_research and the five polymarket_* tools which all surface betting opportunities. ai_visibility_check and scan_competitor_ai_presence overlap, and entity_profile/compare_entities/resolve_entity share inputs. Extensive descriptions help differentiate, but an agent could easily misselect between near-duplicate entry points.

Naming Consistency4/5

Names are uniformly snake_case and mostly follow verb_noun or prefix-group patterns such as ask_pipeworx_*, polymarket_*, remember/recall/forget, and subscribe/unsubscribe. Minor deviations like entity_profile and recent_changes drop the verb, but the overall convention is predictable and readable.

Tool Count2/5

34 tools is beyond the 25+ threshold and the server bundles many unrelated domains—Pipeworx data research, Polymarket analysis, memory, subscriptions, AI visibility, npm scanning, and OBIS marine data. Many tools are redundant variants (six Polymarket tools, four ask_pipeworx variants) that inflate the surface area without adding distinct capabilities.

Completeness3/5

The data-query and prediction-market domains are thoroughly covered: routing, grounded answers, deep research, claim validation, entity comparison, edge detection, fill risk, and subscriptions. However, the server's namesake OBIS surface is skeletal—only occurrence samples, taxon resolution, and aggregate statistics, with no full-record access or dataset browsing—and the broad research purpose leaves notable raw-dataset access hidden behind the meta-router.

Resources