CPFHub.io is a Brazilian CPF lookup API built for developers. This MCP server lets AI agents query CPF data — including full name, gender, and date of birth — directly from a conversation, without writing any HTTP code.
LGPD-compliant · ~300ms response time · 99.9% uptime · 10M+ CPFs queried · works with Claude, Cursor, Windsurf, and any MCP-compatible agent.
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Managed credentials
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Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Average 4.1/5 across 2 of 2 tools scored.
The two tools are completely distinct: one retrieves quota/plan information, the other performs a CPF lookup. There is no overlap in their purposes, making selection unambiguous.
Both tools follow a consistent verb_noun snake_case pattern (get_quota_info, lookup_cpf). The naming style is uniform and predictable.
With only 2 tools, the server feels thin for a CPF lookup service, but it covers the essential actions (lookup and quota check). The count is borderline acceptable for the narrow scope.
The core functionality (lookup_cpf) and a supporting quota tool are present, but the surface lacks potentially expected operations like batch lookup, history, or detailed report generation, leaving noticeable gaps for a fuller service.
get_quota_infoAInspectRetorna informações sobre o saldo de créditos e plano do usuário. Requer autenticação via API key.
| Name | Required | Description | Default |
|---|---|---|---|
| api_key | No | Sua API key do CPFHub (opcional se configurada via env) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It discloses the authentication requirement and indicates a read-only retrieval ('Retorna informações'), but it does not mention potential rate limits, whether the call consumes quota, or the output format.
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 short sentences with no filler. It frontloads the core purpose and then adds the auth prerequisite.
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?
The tool has no output schema, so the description should clarify what information is returned. It gives a high-level idea ('saldo de créditos e plano') but lacks specifics like field names or structure, leaving some ambiguity despite the simple scope.
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 only parameter (api_key) is fully described in the schema with 100% coverage, so the description adds no additional parameter semantics. The schema already explains the key is optional if configured via environment, matching the baseline.
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 returns information about the user's credit balance and plan, which is a specific verb+resource. This distinguishes it from the sibling lookup_cpf, which is a lookup operation.
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 clear context for when to use the tool: when needing quota/plan information. It also notes the authentication prerequisite. It doesn't explicitly discuss alternatives, but no alternative quota tool is listed among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
lookup_cpfAInspectConsulta informações de um CPF brasileiro. Retorna nome, data de nascimento e gênero. Requer autenticação via API key.
| Name | Required | Description | Default |
|---|---|---|---|
| cpf | Yes | CPF a ser consultado (apenas números ou formatado) | |
| api_key | No | Sua API key do CPFHub (opcional se configurada via env) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It states that authentication via API key is required and specifies the output fields. It does not detail error handling or confirm read-only behavior, but 'consulta' implies a safe read operation, making the description reasonably transparent.
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-loaded with the main purpose, followed by return fields and authentication. Every sentence provides necessary information without waste.
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?
The tool has no output schema, so the description correctly explains what is returned (nome, data de nascimento, gênero) and mentions the auth prerequisite. It does not cover error cases or response format, but for a simple lookup tool with two parameters, this is largely complete.
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 already fully describes both parameters (cpf and api_key) with 100% coverage. The description adds the auth requirement context but does not elaborate on parameter syntax or formatting beyond what the schema provides, so the baseline of 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?
The description clearly states the tool's function with a specific verb ('Consulta informações') and resource ('CPF brasileiro'), and lists the returned fields (nome, data de nascimento, gênero). It is distinct from the sibling get_quota_info, which focuses on quota information.
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 clear context for when to use the tool (querying Brazilian CPF information) and notes the auth requirement via API key. It does not explicitly mention when not to use it or name alternatives, but the sibling tool is obviously different in purpose.
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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