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davi713albano-coder

mcp-server-brasil

by davi713albano-coder
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool has a unique and clearly distinct purpose: one for address lookup by CEP, one for company data by CNPJ, and one for currency exchange rates. There is no overlap in functionality.

    Naming Consistency4/5

    Two tools use the 'consulta_' prefix (query), while the third uses 'cotacao_' (rate). While all are descriptive and in snake_case, the prefix inconsistency is a minor deviation from a uniform pattern.

    Tool Count4/5

    With 3 tools, the server is slightly on the smaller side but still within a reasonable range for a focused query service. The number of tools matches the server's apparent scope of providing common Brazilian data lookups.

    Completeness4/5

    The server covers three common Brazilian data queries (address, company, exchange rate) without obvious missing operations for its intended read-only purpose. Minor gaps like historical rates or additional data types exist but do not hinder basic usage.

  • Average 3.6/5 across 3 of 3 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 2 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is failing

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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  "$schema": "https://glama.ai/mcp/schemas/server.json",
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  ]
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior2/5

    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 using ViaCEP but does not inform about potential limitations (e.g., rate limits, reliability) or error handling (e.g., invalid CEP).

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    Two concise sentences, front-loaded with the core action and output. No unnecessary words.

    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 simple lookup tool with a single required parameter and no output schema, the description adequately lists return fields. However, it lacks details on error states and service reliability, which would enhance completeness.

    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 coverage is 100% and the parameter description in the schema already explains the hyphen format. The tool description repeats this without adding new semantic value.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    Description clearly states the tool consults an address by CEP using ViaCEP and lists the return fields. It is distinct from siblings which handle CNPJ and currency queries.

    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?

    No explicit when-to-use or when-not-to-use guidance is provided. However, sibling tool names imply different domains, so usage context is loosely inferred.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior2/5

    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 mentions returned data but does not disclose behavioral traits such as authorization requirements, rate limits, error handling, or any side effects. The description is insufficient for understanding the tool's behavior beyond its basic function.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is a single sentence that is concise and front-loaded. It avoids unnecessary words and clearly communicates the tool's purpose and return values. Every word earns its place.

    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?

    Given the tool's simplicity (single parameter, no output schema), the description is complete for an agent to understand what it does and what it returns. It lists key return fields, which compensates for the lack of output schema. However, some behavioral context is missing (see transparency score).

    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 coverage is 100%, and the parameter description in the schema already explains the CNPJ format (with or without punctuation). The tool description adds no additional meaning beyond what the schema provides, so baseline score of 3 is appropriate.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the tool's purpose: consulting company data by CNPJ using ReceitaWS. It lists specific returned fields (business name, main activity, etc.), and the sibling tools (consulta_cep, cotacao_dolar) are distinct, so no confusion.

    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?

    No explicit guidance on when to use this tool versus siblings, but the naming and description indicate it's for CNPJ queries, which is distinct from CEP or dollar rate tools. Implicit usage context is present but no exclusions or alternatives are stated.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior3/5

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

    Without annotations, the description carries the full burden. It indicates a read operation ('current quotation') but lacks details on data freshness, rate limits, or source reliability beyond mentioning 'AwesomeAPI'.

    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 a single, clear sentence with no unnecessary words. However, it is so brief that it under-specifies some aspects; a slightly longer description with structured details would improve clarity.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness3/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given no output schema, the description does not explain what the return data contains (e.g., values, timestamps). For a simple tool, this may be acceptable, but completeness is hindered by the lack of return format details.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters4/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    No parameters exist, so the description adds no param details beyond the schema. Baseline for 0 parameters is 4, and no further clarification is needed.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the tool provides current exchange rates for USD and EUR to BRL, matching the tool name and distinguishing it from siblings (consulta_cep, consulta_cnpj) which handle different data types.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    No usage guidance is provided. The description does not specify when to use this tool versus alternatives, though siblings are clearly for different domains. No explicit when-to-use or when-not-to-use instructions.

    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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  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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