lookup_leiResolve a Legal Entity Identifier (LEI) or search legal names against the GLEIF public register (keyless deterministic lookup). Price: 0.005 USDC per call (x402, Base). Resource: https://api.exo-trust.com/execute/lookup_lei. Returns the payment challenge unless already settled.
| Name | Required | Description | Default |
|---|---|---|---|
| lei | No | ||
| name | No | ||
| country | No | ||
| page_size | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description covers some behavioral aspects: it mentions the cost (0.005 USDC per call), the resource URL, and the unusual return behavior ('Returns the payment challenge unless already settled'). However, it does not explicitly state whether the tool is read-only, has side effects, or handles errors, leaving some ambiguity.
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?
The description is brief and to the point, with no filler phrases. It packs useful operational details (price, resource, return behavior) into a compact structure, though the information is presented as a list rather than flowing prose.
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?
There is no output schema, and the description only hints at the return value (payment challenge unless settled). It does not specify the structure of successful results or error scenarios. Combined with the lack of parameter explanations, the tool is under-specified for confident autonomous use.
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?
The schema lists four parameters (lei, name, country, page_size) but the description provides zero explanation of their meanings, formats, or relationships. An agent cannot infer how to set these parameters from the description alone.
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 clearly states the tool's core function: resolving a Legal Entity Identifier (LEI) or searching legal names against the GLEIF public register. It also specifies the lookup type (keyless deterministic) and is distinct from the sibling tools, which cover other domains.
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?
The description provides no guidance on when to use this tool versus alternatives. It does not mention any prerequisites, typical scenarios, or conditions that would favor this tool over other sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clearly distinct purposes, but edgar_financials and edgar_report overlap heavily, with the report apparently building on the same financial data. The three registry lookups (sanctions, VAT, LEI) are distinct, and the text-processing tools are separable.
Naming is inconsistent: some tools use bare verbs (classify, extract, proofread, rewrite, summarize, translate), some use verb_noun (check_sanctions, lookup_lei, validate_vat, code_explain), and others use domain-based names (clinical_dd, edgar_financials, edgar_report, synergy_discovery). No single consistent convention is applied.
14 tools is within the reasonable range and each covers a distinct specialist area, but the set feels slightly broad and includes a few near-duplicates (edgar_financials vs edgar_report). It is not excessive, though tightening could improve focus.
The catalog covers a wide range of domains: sanctions, VAT, LEI, SEC filings, clinical trials, code analysis, text transformation, and discovery. It includes a discovery tool to enumerate specialists, which helps. Minor gaps like missing update/delete-style operations are not expected for a read-only specialist API, so coverage is strong.