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NeuralVerge Business Intelligence

LEI Lookup companies search

run_lei_lookup_companies_search

Search the public register of Legal Entity Identifiers by company name or LEI code: LEI, name, country, entity status, LEI registration status and link. Filter by entity status (active or inactive), LEI registration status and country. 1 point per returned record.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusNoEntity status. Options: active = Active, inactive = Inactive / dissolved
countryNoCountry (2-letter code). e.g. DE
keywordYesCompany name or LEI. e.g. Apple
max_itemsNoMax items (up to 250) Default: 25.
reg_statusNoLEI status. Options: ISSUED = Issued, LAPSED = Lapsed, ANNULLED = Annulled, MERGED = Merged, RETIRED = Retired, DUPLICATE = Duplicate, PENDING_TRANSFER = Pending transfer, PENDING_ARCHIVAL = Pending archival
start_pageNoStarting page

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It usefully discloses that results are billed ('1 point per returned record') and lists the returned fields (LEI, name, country, status, registration status, link), which is valuable context. It does not describe pagination behavior or result limits beyond what the schema states.

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?

Two sentences that are front-loaded with the core purpose and efficiently follow with the filter and cost information. No filler, though the returned-field list is slightly dense.

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

Completeness4/5

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

For a search tool with no output schema, the description usefully enumerates the returned fields and mentions cost per record, covering the essentials. The remaining gap is pagination/limit guidance, which the schema partially handles, so it is nearly complete.

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 all six parameters are already documented with types, enums, and examples in the schema. The description restates the filter dimensions (status, reg_status, country) without adding format or syntax beyond what the schema provides, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (Search) and resource (public register of Legal Entity Identifiers) and enumerates the returned fields. It does not, however, differentiate itself from the sibling run_lei_lookup_companies or the related run_gleif_companies_search, so an agent must guess which of the LEI tools to pick.

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

Usage Guidelines3/5

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

The description implies usage via 'Filter by entity status, LEI registration status and country,' giving the agent some sense of what queries are possible. But there is no explicit when-to-use guidance, no exclusions, and no routing to the non-search sibling run_lei_lookup_companies or the GLEIF alternative.

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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