Ownership tree by LEI or name: parent chain, ultimate parent, subsidiaries (GLEIF). Paid via x402.
Scored across 1 tool
There is only a single tool, so there is no possibility of misselection or overlap with any sibling tool. Its scope (ownership tree lookup) is unambiguous and matches the server's stated purpose exactly.
The sole tool name 'lei_ownership_tree' is clear snake_case and self-describing, with the domain prefix (lei) tying it to the GLEIF LEI space. With only one name, no convention violations are possible.
A one-tool surface is thin by the usual 3-15 guideline, though it is defensible since the domain is a single read-only lookup that packs parent chain, exceptions, and subsidiaries into one call. Still, a companion tool (e.g. LEI/name resolution or relationship detail) would round out the surface.
For a corporate ownership tree service the coverage is strong: it accepts LEI or company name, returns the full parent chain, reporting exceptions, and direct/ultimate subsidiaries with counts. Minor gaps exist around large-tree paging and per-relationship detail (dates, status, ownership percentages), but core workflows are covered.
Corporate ownership tree for any entity with an LEI, by LEI or company name: full parent chain up to the ultimate accounting-consolidation parent, reporting exceptions (why no parent is reported), and direct/ultimate subsidiaries with counts. Official GLEIF Level 2 relationship data, CC0. Use when you must know who ultimately owns or controls a company (parent chain, ultimate parent, subsidiaries) for KYB, credit or group-exposure checks. Paid per call via x402 (USDC on Base).
| Name | Required | Description | Default |
|---|---|---|---|
| lei | No | 20-character LEI | |
| name | No | Company name if no LEI | |
| children_limit | No | Max direct subsidiaries listed (default 25) | |
| payment_signature | No | x402 v2 PAYMENT-SIGNATURE header value. Omit to receive payment requirements. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden and does well: it discloses the data provenance (official GLEIF Level 2 relationship data, CC0) and the billing model (paid per call via x402, USDC on Base), which are traits no structured field conveys. It stops short of stating coverage limits, error behavior, or latency, so it is not a full 5.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, all earning their place: purpose and outputs first, usage context second, provenance and payment model last. The critical information (what tree, keyed how) is front-loaded with no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only lookup with no output schema, the description adequately characterizes what comes back (parent chain, exceptions, subsidiary counts) and how payment works. The remaining gap is that it does not describe response shape or failure modes in more detail, which is minor given the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description reinforces the LEI-or-name keying and mentions that subsidiaries come with counts (implying children_limit), but it adds no format, default, or constraint detail beyond what the schema already documents.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific resource and verb: a corporate ownership tree for any entity with an LEI, keyed by LEI or company name. It enumerates exactly what is produced (parent chain to ultimate accounting-consolidation parent, reporting exceptions, direct/ultimate subsidiaries with counts), so an agent can tell precisely what this tool returns without opening the schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives a clear when-to-use condition: 'Use when you must know who ultimately owns or controls a company ... for KYB, credit or group-exposure checks.' That is concrete context rather than implied usage. No alternatives or when-not conditions are named, but no sibling tools exist, so there is nothing to route against.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
lei_ownership_treeCompany registry lookup by name, LEI or number: status, address, officers, parents. Paid via x402.
UBO, sanctions & ownership graph. 23 tools, 130.7M entities, 31 registries.
Company hierarchy analysis and address verification via MCP
B2B data enrichment for 375M+ companies: legal entities, corporate hierarchies, and contacts.
Add one secure layer between your agents and this server.
