Skip to main content
Glama

Geodistance

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

A4.9/5.0
Behavior5/5

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

Beyond the readOnly/openWorld/idempotent annotations, the description discloses source fan-out behavior, `sources_used`/`sources_failed` semantics, empty sections meaning real 'no data,' USPTO soft-fail behavior, and private-company handling with `resolved:false` and a `notes` line. This is substantial behavioral context added on top of the 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 front-loaded with the core purpose and preference rule, and every major section adds concrete operational detail. It is long and runs as a single dense paragraph, which keeps it from a 5, but it contains little true filler for a tool with this many source integrations and edge cases.

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 present, the description compensates by enumerating what the tool returns: CIK, company name, resolved_from/resolved_to, recent filings with URIs, fundamentals, sources_used/sources_failed, and LEI. It also covers input variants and failure semantics, making the tool effectively self-contained for an agent to invoke correctly.

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?

Although the schema already covers both parameters, the description adds meaningful semantics: `type` accepts 'company' or 'ticker' interchangeably, `value` can be a ticker, zero-padded CIK, or company name, names resolve via SEC EDGAR, and private companies return a specific structured result rather than failing. This goes well beyond the schema descriptions.

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 clearly states the tool produces a 'full cross-source profile of a US public company in ONE parallel call,' with trigger examples like 'Tell me about X' and 'brief me on Tesla.' It also contrasts itself with 'chaining single-pack SEC/XBRL/news lookups,' which helps an agent distinguish it 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 gives explicit when-to-use guidance: prefer it for holistic view requests, avoid chaining single-source lookups. It also spells out accepted inputs (ticker, CIK, company name), behavior for private companies, and the fact that both `type` values behave identically.

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

All Geodistance 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

A3.8/5.0
Disambiguation3/5

Many tools have clearly distinct purposes, but research entry points overlap heavily (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research) and the beta tool currently behaves identically to the stable version. Polymarket tools and AI visibility tools also create multiple near-overlapping options that require careful reading to disambiguate.

Naming Consistency3/5

All names follow snake_case and are readable, but there is no consistent pattern: some are verb-first (ask_, resolve_, validate_, scan_), some noun-first (entity_profile, pipeworx_trending, polymarket_edges), and some are bare nouns (distance, destination). This mixed convention makes the tool set feel less predictable than it should.

Tool Count2/5

35 tools is excessive for a server named Geodistance, and the actual purpose is a sprawling data-research and prediction-market toolkit with a few geospatial helpers. The set would be better split into focused servers; as-is it feels bloated and poorly scoped.

Completeness3/5

The data-research surface is quite complete (discovery, lookup, grounded answers, comparisons, subscriptions, memory, feedback), and geodistance has core operations like distance, destination, and coordinate conversion. However, the geographic functionality is thin and the overall grab-bag composition makes it hard to assess completeness against any single coherent domain; obvious geospatial features like geocoding, routing, or area calculations are absent.

Resources