Annalist Financial Statements

Search the entities of Atlas

search_entities

Read-onlyIdempotent

Find a company, a bank or another legal entity in Atlas, the map of the relationships between companies, by part of its name, its LEI or the id of a covered company. Returns each entity's id (used by get_relationships and find_connections), its country, LEI, the covered company that it is or whose group it belongs to (Citibank, N.A. to citigroup), and its number of links.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "search_entities"
  }
}

Input Schema

Name	Required	Description
`limit`	No	maximum number of entities (default 20)
`query`	No	part of a name, an LEI or a company id, for example JPMorgan Chase Bank or boeing
`country`	No	ISO 3166 country code, for example US, SG or JP

Output Schema

Name	Required	Description	Default
`note`	No
`total`	Yes
`measure`	No
`entities`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 4, 2026

TDQS

A3.5/5.0

Behavior3/5

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

The annotations already establish that this is a safe, idempotent, read-only search with no destructive behavior. The description adds useful context about returned fields and how entity ids feed other tools, but it does not disclose matching behavior, ranking, pagination, or other search semantics beyond what the schema and output schema provide.

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 search action and lookup keys, followed by return information. It is reasonably tight, though the parenthetical covered-company example and return-field enumeration make it somewhat longer than necessary given the existing output schema.

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 three-parameter, read-only search tool with full schema coverage, rich annotations, and an output schema, the description gives enough context to call the tool correctly. Its main gap is the lack of explicit routing guidance against the other search and company-lookup siblings.

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 three parameters are already documented in the schema. The description reinforces that the query can be part of a name, an LEI, or a company id, but it adds no detail about the country filter or limit behavior beyond what the schema supplies.

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?

The description clearly states a specific verb and resource: find a company, bank, or legal entity in Atlas. It also explains the supported lookup keys (name fragment, LEI, covered-company id), but it does not explicitly distinguish this tool from close siblings such as search_companies or search.

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?

Usage is implied by the statement that returned ids are used by get_relationships and find_connections, suggesting this is an entity-resolution step before relationship queries. However, there is no explicit when-to-use guidance, no when-not guidance, and no comparison with the sibling search tools.

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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