veradata-api
Server Details
Verified Latin American data for autonomous AI agents — sanctions screening (OFAC+SARLAFT+CNBV+COAF+UAF), entity enrichment (RUES/CNPJ/RFC), central bank rates (DTF/TIIE/Selic/TRM/UF), and market intelligence. EU AI Act Art.13 compliant. $0.02–$0.10 USDC via x402 on Base and Solana.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 3.6/5 across 4 of 4 tools scored.
Each tool targets a distinct domain (market context, entity enrichment, rates, sanctions) with no overlap in functionality or output.
All tools follow a consistent 'vera_noun' pattern, making it easy to understand the resource each tool operates on.
With 4 tools, the server is well-scoped for its LATAM data purpose, covering core needs without unnecessary bloat.
The tool set covers market context, company data, rates, and sanctions, but lacks a search or aggregation tool across datasets.
Available Tools
4 toolsvera_contextAInspect
AI-powered LATAM market context. Sector + country → market_size, key_players, regulations, growth signals. $0.10 USDC via x402.
| Name | Required | Description | Default |
|---|---|---|---|
| query | No | Specific market question | |
| sector | Yes | Industry sector (e.g. fintech, logistics, healthtech) | |
| country | Yes | ||
| x_payment | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It mentions cost ($0.10 USDC via x402) and the general nature, but lacks details on idempotency, rate limits, or authentication needs.
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 extremely concise with two sentences, no wasted words, and front-loads the core purpose.
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?
With 4 parameters, no output schema, and no annotations, the description is too sparse. It omits the query and x_payment parameters, and does not describe the return format, making it incomplete for reliable agent 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?
Schema coverage is 50%, requiring the description to explain parameters. It only mentions sector and country, ignoring query and x_payment. It adds marginal meaning but insufficiently compensates for undocumented parameters.
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 it provides 'AI-powered LATAM market context' with sector and country inputs producing market_size, key_players, regulations, growth signals. It clearly distinguishes from siblings like vera_entity, vera_rates, vera_sanctions.
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 implies usage for LATAM market context and lists sibling tools, but does not explicitly state when not to use this tool or provide alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
vera_entityAInspect
Company enrichment from LATAM public registries. RUES CO, CNPJ BR, RFC MX. Returns NIT/CNPJ, status, representative, industry. $0.03 USDC via x402.
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | Company name (for search) | |
| country | Yes | ||
| x_payment | No | ||
| identifier | No | NIT, CNPJ, or RFC |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the cost ($0.03 USDC via x402) and the registries accessed, but does not explicitly state that the operation is read-only, idempotent, or what happens on errors or missing entities. The behavioral disclosure is adequate but not rich.
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 two sentences long, front-loading the core purpose. Every phrase adds value: registries, output fields, cost, and payment method. No extraneous words, making it highly efficient.
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?
Given the absence of an output schema, the description covers the essential return fields (NIT/CNPJ, status, representative, industry). It also mentions the payment requirement. Missing are details on error handling, number of results, or any side effects. For a simple enrichment tool, this is reasonably complete, but lacks some edge-case context.
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 50% (name and identifier have descriptions; country and x_payment do not). The description adds context by mapping country values to registries (RUES CO, CNPJ BR, RFC MX) and explaining identifier types (NIT, CNPJ, RFC). However, it does not explain the x_payment parameter's format or purpose beyond the cost mention, leaving some ambiguity.
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 performs company enrichment from specific LATAM public registries (RUES CO, CNPJ BR, RFC MX) and lists the returned fields (NIT/CNPJ, status, representative, industry). It distinguishes itself from siblings by specifying the registries and output, making its purpose unambiguous.
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 (e.g., vera_context, vera_sanctions). It does not state prerequisites, limitations, or conditions where another tool would be more appropriate. The usage context is implied but not explicitly compared to siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
vera_ratesAInspect
Real-time LATAM central bank rates. Countries: CO, MX, BR, CL, PE. Returns FX rates, benchmark rates, inflation. $0.02 USDC via x402.
| Name | Required | Description | Default |
|---|---|---|---|
| country | Yes | ISO 3166-1 alpha-2 country code | |
| signals | No | Optional: specific signals to return (e.g. usd_cop, dtf_ea) | |
| x_payment | No | x402 payment token |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description discloses real-time nature, returned data types, and a cost ($0.02 USDC via x402), but with no annotations, it fails to mention safety (read-only?), error handling, or rate limits. Adequate but not comprehensive.
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?
Two sentences, front-loaded with purpose, then outputs and cost. No wasted words. Highly efficient.
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?
Despite no output schema, description lists return types (FX, benchmark, inflation) and cost. Lacks detailed structure or pagination info, but sufficient for basic selection and 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?
All three parameters are documented in the schema (100% coverage), so description adds minimal value beyond confirming country codes and optional signals. Baseline 3 is appropriate.
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?
Description clearly states the tool returns real-time LATAM central bank rates for specific countries (CO, MX, BR, CL, PE) and lists output types (FX, benchmark, inflation). However, it lacks an action verb like 'get' or 'retrieve', slightly reducing clarity.
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?
Usage context is implied by the description (LATAM rates) and sibling tools (context, entity, sanctions) suggest distinct purposes. But no explicit guidance on when to use this tool versus alternatives or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
vera_sanctionsAInspect
LATAM sanctions screening. OFAC + SARLAFT CO + CNBV MX + COAF BR + UAF CL. Returns risk_score 0-1 + EU AI Act audit hash. $0.05 USDC via x402.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Person or company name to screen | |
| type | No | person | |
| country | Yes | ISO country code | |
| x_payment | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the cost ($0.05 USDC via x402) and the output format, but does not mention authorization requirements, idempotency, failure scenarios, or any side effects. The cost disclosure is a positive, but overall behavioral transparency is partial.
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?
Two concise sentences that front-load the core purpose and key details (regulatory scope, output, cost). Every sentence adds value; no filler or repetition.
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?
Given the tool has 4 parameters, no output schema, and no annotations, the description covers purpose, scope, output, and cost, but is missing failure behavior, rate limits, parameter defaults (e.g., type default), and usage examples. Adequate for basic understanding but incomplete for confident invocation.
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 input schema has 50% description coverage (name and country have descriptions; type and x_payment lack them). The tool description adds context (LATAM regulatory lists) but does not elaborate on parameter meaning beyond what the schema provides. Baseline 3 is appropriate; the description compensates marginally with scope context.
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?
Description clearly states the tool performs LATAM sanctions screening, lists specific regulatory frameworks (OFAC, SARLAFT, etc.), and mentions the output (risk_score and hash). While it distinguishes from sibling tools by its specific function, it does not explicitly contrast with siblings.
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 implies the tool is used for sanctions screening in LATAM, but provides no explicit guidance on when to use it versus alternatives. No when-not-to or prerequisite conditions are mentioned; the listing of sibling tools does not include usage guidance.
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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