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Glama

Eodhd

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

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, so the safety profile is covered. The description adds substantial operational context beyond annotations: fan-out across eight source families, per-section empty-is-real semantics ('an empty section is a real "no data", not a bug'), a soft-fail for the sunset USPTO PatentsView API, GDELT→GNews fallback, and resolved:false with an explicit notes line for private companies. 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?

Dense, but nearly every sentence carries operational value: trigger phrases, routing preference, source fan-out, return fields, failure semantics, and input forms. The seven near-duplicate trigger phrases ('tell me about X' / 'research Acme' / 'brief me on Tesla') are the only real redundancy, and the single-paragraph wall of text could benefit from light structuring.

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?

This is a high-complexity tool (two params, eight-plus data sources, three input forms, multiple edge cases) with no output schema, so the description carries the full disclosure burden. It covers every return section (cik/company_name, recent_filings with URIs, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI), sources_used/sources_failed for diagnosing empty results, and every failure mode. Nothing an agent needs to invoke this correctly is missing.

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 value above the schema: it documents that type accepts 'company' or 'ticker' interchangeably, gives concrete value examples (AAPL, 0000320193, Moderna), and explains the SEC EDGAR name-resolution behavior with its resolved_from/resolved_to side effects. This meaningfully exceeds what the schema alone 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 states a specific verb+resource: 'full cross-source profile of a US public company in ONE parallel call.' Seven trigger-phrase examples ('brief me on Tesla', 'company profile for Microsoft', 'everything you know about $TICKER') anchor the trigger surface, and 'US public company' scopes it precisely enough to distinguish it from generic research siblings like deep_research or bet_research.

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?

Explicit routing guidance: 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view' directly names the alternative pattern and the condition that selects this tool. It also covers input-conditional behavior (private companies return resolved:false, not failure). However, it does not explicitly differentiate from near-neighbor siblings such as resolve_entity, compare_entities, or deep_research, leaving some routing decisions to inference.

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

Multiple tool clusters overlap heavily: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route research questions; polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, and bet_research all hunt prediction-market edges; ai_visibility_check and scan_competitor_ai_presence do nearly the same job. The verbose descriptions help, but an agent would still struggle to pick the right tool in these clusters.

Naming Consistency2/5

Everything is snake_case, but there is no coherent pattern: some names are verb_noun (compare_entities, validate_claim), some are bare verbs (remember, forget, recall), some are prefixed by domain (eodhd_*, pipeworx_*, polymarket_*, ai_visibility_*), and the Eodhd prefix clashes with the Pipeworx family. The conventions feel inherited from multiple unrelated codebases rather than a unified design.

Tool Count2/5

33 tools is already heavy for most servers, but the real problem is that only 2 tools (eodhd_eod_prices, eodhd_fundamentals) relate to the server's stated purpose. The other 31 span Pipeworx research, Polymarket betting, memory, subscriptions, feedback, llms.txt generation, and npm dependency checking — a massively over-scoped grab bag for a server named 'Eodhd'.

Completeness2/5

For the nominal EODHD domain the surface is severely incomplete: no splits, dividends, options, exchanges list, or other standard EODHD endpoints — just prices and fundamentals. As a general research/data platform it is broad rather than deep, mixing a decent question-answering core with unrelated one-off utilities, so no single coherent lifecycle is fully covered.

Resources