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MCPFax Public-Data Utility API

LEI lookup

v1_lei
Read-onlyIdempotent

LEI lookup: Legal Entity Identifier record by LEI code or entity name. Source: GLEIF. $0.008 per call · GET /v1/lei

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoEntity legal name (if no LEI). Example: 'Apple Inc.'.
leiNo20-character LEI. Example: 'HWUPKR0MPOU8FGXBT394'.

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already cover read-only, idempotent, open-world, and non-destructive behavior. The description adds useful operational context such as the data source, pricing, and HTTP endpoint, but it does not disclose details like what happens when both q and lei are provided, how matches are returned, or error behavior.

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 compact and front-loaded, with all key facts in one sentence. 'LEI lookup:' is slightly redundant with the title, but the rest—source, pricing, and endpoint—is useful and earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple lookup with no output schema, the description gives the essential inputs and source but stops short of explaining response shape, match semantics, or whether one of q/lei is required. Since the schema allows empty required fields, a note that at least one of q or lei should be supplied would improve completeness.

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%, with both q and lei well documented including examples. The description's mention of 'by LEI code or entity name' adds no meaning beyond what the schema already provides, so the baseline score of 3 is appropriate.

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 performs a lookup of Legal Entity Identifier records, with the resource (LEI code or entity name), source (GLEIF), and endpoint. It is specific enough to distinguish from the other lookup tools, especially since no other tool targets LEI data.

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 gives clear context: use this to retrieve an LEI record by either the 20-character LEI code or an entity legal name. It does not explicitly mention when not to use it or name alternatives, but the GLEIF source and LEI-specific purpose make the intended usage reasonably obvious.

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

A3.7/5.0
Disambiguation5/5

Every tool targets a distinct resource or operation—geocoding, weather, DNS, VIN, stock quotes, etc.—with no meaningful overlap in purpose. Even the location- and finance-related tools are clearly separated by their descriptions.

Naming Consistency5/5

All tools follow the same v1_<resource>[_modifier] snake_case pattern, such as v1_air_quality, v1_reverse_geocode, and v1_validate_email. Although the names are not verb-based, the convention is perfectly consistent across all 31 tools.

Tool Count2/5

31 tools exceeds the 25+ threshold and creates a heavy selection burden for agents, even though the server's stated purpose is broad. Many endpoints are small single-purpose lookups that could be grouped into fewer combined tools without losing clarity.

Completeness4/5

As a general public-data utility, the set covers a wide range of common lookup categories: location, weather, finance, legal, health, business, internet, and reference data. It has minor gaps like historical financial time series or phone-number validation, but no obvious dead ends since all tools are self-contained read-only lookups.

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