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Glama

Peeringdb

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?

Beyond annotations (readOnlyHint, openWorldHint, idempotentHint), the description reveals important behavioral traits: one parallel fan-out call, USPTO soft-fail after May 2025, empty sections meaning genuine absence of data rather than failure, resolved_from/resolved_to behavior, and the explicit notes line for private companies. This is substantial context beyond the structured annotations and contradicts nothing.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but front-loaded with examples and a clear preference directive before diving into output structure. Every section earns its place: input shapes, fan-out sources, output fields, edge cases, and empty-data semantics are all covered without repetition or filler.

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 fully carries return-value documentation: it enumerates resolved metadata, recent_filings, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI, and sources_used/sources_failed. It also handles the main edge cases (private companies, empty FDA results, expired USPTO API) and both input parameters thoroughly. Nothing an agent needs to call this correctly is missing.

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

Parameters5/5

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

Schema coverage is already 100%, but the description adds real semantic value: it clarifies that 'type' accepts 'company' or 'ticker' interchangeably, enumerates the three accepted value shapes (ticker, zero-padded CIK, company name), and gives concrete examples like 'AAPL', '0000320193', and 'Moderna'. It also explains the name-resolution fallback via SEC EDGAR.

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 names a specific verb (profile/research/brief) and resource (US public company) with multiple natural-language examples, and clearly states it fans out across SEC, XBRL, patents, contracts, FDA, hiring, news, and GLEIF in one call. It differentiates itself from single-pack lookups and sibling alternatives like compare_entities by focusing on a holistic, per-entity profile.

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?

The description explicitly says 'ALWAYS PREFER' this tool over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view, and explains when a private company yields resolved:false. It does not explicitly exclude use cases like direct comparison or deep research, but the primary when-to-use guidance is unambiguous.

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

Many tools have overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, discover_tools, and suggest_questions all serve question-answering/discovery; polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread, and bet_research all analyze prediction markets; ai_visibility_check and scan_competitor_ai_presence overlap heavily. Only the three PeeringDB search tools are clearly distinct.

Naming Consistency2/5

Naming mixes verb-led snake_case (search_networks, validate_claim, subscribe) with noun-phrase tools (entity_profile, bet_research, recent_alerts) and inconsistent prefixes (ask_pipeworx vs ask_pipeworx_beta vs ask_pipeworx_grounded; polymarket_arbitrage vs polymarket_fill_risk vs polymarket_kalshi_spread). No consistent verb_noun pattern is present.

Tool Count2/5

34 tools is heavy for a coherent surface, especially since the server is named 'Peeringdb' but only 3 of 34 tools relate to PeeringDB. The Pipeworx/Prediction-market/memory/AI-visibility tools form several distinct sub-domains that would be better split into separate servers or consolidated.

Completeness2/5

For PeeringDB, only search_exchanges/facilities/networks exist—no get-by-id, no facility/network details beyond search results, and no read/update operations. For the broader Pipeworx domain, coverage is fragmented: many meta-tools overlap while some obvious operations (e.g., updating a saved memory, deeper entity relationships) are missing. The domain is poorly scoped, making completeness hard to assess.

Resources