ECRVSP Documentos: Escolha da Placa
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ECRVSP Documentos: Escolha da Placa, official-source lookup. Platform-hosted, pay per query with pre
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- ECRVSP Documentos: Escolha da Placa
Available Tools
7 toolsauthenticateAIdempotentInspect
MCP.AI for IDE agents (Cursor, etc.): log in in the browser, copy the access token. Best: add it to this server's config as a header Authorization: Bearer <token> for a permanent, non-expiring connection. Or paste it here for a session-only login: call with { token: "" } after the user pastes, or with no args to get the link.
| Name | Required | Description | Default |
|---|---|---|---|
| token | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explains behavioral nuances such as permanent vs session-only connections and the need to copy the token from the browser. It doesn't contradict annotations (idempotentHint=true, destructiveHint=false) and provides sufficient context for a read-like, non-destructive action.
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 slightly long but well-structured: it starts with purpose, then gives the best practice, then the alternative session login. Every sentence adds value, though some trimming could make it more concise.
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 tool with one optional parameter and no output schema, the description is complete. It covers both usage modes, the user action required, and the permanent/session distinction, leaving no critical gaps.
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?
Even though schema coverage is 0%, the description thoroughly explains the single token parameter, specifying it as a JWT to be passed after the user pastes it. It also clarifies the behavior when no arguments are provided, fully compensating for the lack of schema documentation.
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 purpose: to authenticate the user with MCP.AI by obtaining a link for browser login or accepting a token. It distinguishes from siblings like connect and marketplace by focusing solely on authentication.
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?
Explicitly explains when to use each mode: no args to get a link, or with token for session login. Also presents the preferred alternative of adding the token to config for permanent access, making the decision clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
connectARead-onlyIdempotentInspect
Returns connection status and URLs. When all providers are connected, returns authenticated:true and empty pending[]. When credentials are missing, returns connect_url for the toolkit and per-install URLs.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, so the safety profile is covered. The description adds value by explaining the conditional output (authenticated:true vs connect_url) and what each state means, giving agents more behavioral insight beyond the annotations.
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 with no fluff. The first sentence states the core purpose, and the second explains the two key output states. Information is front-loaded and every word earns its place.
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 parameterless status check tool, the description covers the two most likely states (all connected vs missing credentials) and their outputs. It does not address partial connection states, but given the simplicity of the tool and lack of output schema, the information is adequate for an agent to understand the tool's behavior.
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?
There are no parameters, so schema coverage is moot. Baseline for 0 params is 4, and the description correctly avoids adding extraneous parameter details. It focuses on output semantics instead, which 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 returns connection status and URLs, with specific conditions for different states (authenticated:true when all providers connected, connect_url when credentials missing). This distinguishes it from sibling tools like authenticate and toolkit_info, making the 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 implies use for checking connection status but provides no explicit guidance on when to use this tool versus alternatives. It does not mention conditions like 'use before authenticate' or 'use to troubleshoot connection issues', so usage context is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
ecrvsp_docs_escolher_placa_consultarCRead-onlyIdempotentInspect
ECRVSP Documentos: Escolha da Placa, consulta em fonte oficial. Hospedado pela plataforma, sem credenciais da plataforma, pague por consulta com crédito pré-pago. Consulta informação de fontes e órgãos oficiais brasileiros (a mesma disponível ao cidadão), não é dado sigiloso. O cliente é o controlador dos dados e responde pela finalidade legítima (LGPD).
| Name | Required | Description | Default |
|---|---|---|---|
| a3 | Yes | ||
| cpf | No | ||
| cnpj | No | ||
| a3_pin | Yes | ||
| chassi | Yes | ||
| opcoes | Yes | ||
| login_cpf | Yes | ||
| login_senha | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, and the description aligns with that by stating 'consulta'. It adds useful behavioral context: pay-per-query, no platform credentials needed, and data not confidential. However, it does not describe return format, error behavior, or other side effects beyond cost, so it adds some value but lacks depth.
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 a single paragraph of about 3 sentences, which is reasonably sized but contains redundancy (e.g., repeating 'consulta em fonte oficial' and later 'consulta informação de fontes e órgãos oficiais'). It front-loads the key purpose but could be tightened without losing meaning.
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 8 parameters (6 required) and no output schema, yet the description provides no information about expected inputs, parameter syntax, or what the response contains. It covers payment and data responsibility but omits essential operational details, making it inadequate for an agent to invoke correctly.
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?
With schema_description_coverage at 0%, the description must explain parameters but does not mention any of the 8 fields (a3, a3_pin, login_cpf, login_senha, chassi, opcoes, cpf, cnpj). No supplementary information is given on what these mean or how to format them, leaving the agent entirely reliant on the schema names, which are cryptic.
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 it's a query tool for 'Escolha da Placa' (plate choice) using official sources, distinguishing it from sibling tools like authenticate or connect. It specifies the nature of the query and the source, making the purpose understandable but not deeply precise about the exact output.
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?
No guidance on when to use this tool versus alternatives is provided. It mentions payment and lack of platform credentials but does not compare with other tools or specify scenarios where this is the appropriate choice. There is no 'when not to use' or alternative naming.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
marketplaceAInspect
The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them. Covers capability requests like "find an MCP that does X", "consulta um CPF", "is there a tool for Y". Core flow: action=search discovers MCPs by intent → describe returns one MCP's full profile (every tool with its id + params, pricing, auth) so you pick the right tool_id → invoke RUNS that tool. KEY: invoke works even when the MCP is NOT installed — it runs the tool pontualmente (one-off), without adding the MCP to the toolkit and without bloating the tool list. If the MCP needs a credential/login, invoke returns a connect link; if it is paid and the wallet is empty, invoke returns a checkout/top-up link (the user opens it, then you retry). Use install only to make an MCP PERMANENT in the active toolkit (its tools then show up natively in future sessions); prefer invoke for a single/occasional use. list_tools lists what is callable right now. subscribe/cancel handle per-MCP billing; report_bug sends feedback; request_mcp asks us to build a NEW MCP when nothing fits. Search/describe flag installed_in_toolkit vs installed_in_workspace. Writes (install/uninstall/subscribe/cancel and the one-off install behind invoke) require workspace owner/admin. It also carries the mcp.ai PROMPT LIBRARY, which is about ready-made prompt TEXT rather than MCPs: search_prompts finds one, get_prompt returns its full text with {{variables}} filled, and publish_prompt saves a prompt and returns a shareable mcp.ai/p/ link that opens without login.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | No | ||
| action | No | search | |
| mcp_id | No | ||
| message | No | ||
| tool_id | No | ||
| arguments | No | {} | |
| immediate | No | ||
| tier_slug | No | ||
| prompt_body | No | ||
| prompt_slug | No | ||
| prompt_tool | No | ||
| prompt_vars | No | {} | |
| conversation | No | [] | |
| prompt_title | No | ||
| request_name | No | ||
| cancel_reason | No | ||
| cancel_comment | No | ||
| prompt_targets | No | ||
| report_context | No | ||
| prompt_category | No | ||
| request_details | No | ||
| prompt_description | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the sparse annotations (readOnlyHint false, openWorldHint true, destructiveHint false), the description discloses critical behavioral traits: invoke works without installation, one-off runs avoid toolkit bloat, credential/payment flows return connect/checkout links, and writes require workspace owner/admin. It also explains the prompt library distinction and installed_in_toolkit vs installed_in_workspace flags.
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 dense but well front-loaded, opening with the marketplace's core identity and then organizing into core flow, invoke key behavior, install-vs-invoke guidance, list_tools, billing, and prompt library. Every sentence adds information, though the length is substantial and the prose is somewhat run-on; 'pontualmente' is also an unneeded foreign insertion.
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 tool with 14 actions, 23 parameters, and no output schema, the description covers the main search/invoke/install and prompt-library flows well, including auth and payment edge cases. But it omits the resume action entirely, does not explain return values for search/describe/invoke, and leaves several parameters and failure/retry semantics implicit, so completeness is partial rather than full.
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?
With 0% schema description coverage and 23 parameters, the description compensates substantially for the main action parameter (search/describe/invoke/install/prompt actions) and the mcp_id/tool_id concept. However, several parameters remain unexplained, including resume, immediate, tier_slug, conversation, cancel_reason, prompt_targets, and prompt_category, leaving meaningful semantic gaps.
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 identifies the tool as the official mcp.ai marketplace/catalog and the mechanism for running MCPs/tools, with explicit mention of search → describe → invoke flows. It goes beyond a generic label by naming concrete capability requests and distinguishing its core function from simple catalog browsing.
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?
Contains explicit usage guidance: prefer invoke for one-off use, use install only to make an MCP permanent, list_tools for currently callable tools, request_mcp when nothing fits, and separate prompt-library actions. This clearly tells an agent when to use the marketplace tool and when to choose different actions within it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
report_bugAIdempotentInspect
Report a bug, missing feature, or send feedback. Include the conversation array with recent messages for reproduction.
| Name | Required | Description | Default |
|---|---|---|---|
| context | No | ||
| message | Yes | ||
| conversation | No | [] |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare idempotentHint=true, destructiveHint=false, and readOnlyHint=false. The description adds the useful instruction to include the conversation array for reproduction, but does not disclose any post-submit behavior (e.g., issue creation) or other side effects beyond what annotations imply.
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 short sentences, front-loaded with the core purpose and followed by an actionable reproduction tip. Every sentence earns its place and there is no filler or redundancy.
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 simple 3-parameter tool with no output schema and no enums, the description covers the main action and the reproduction detail. The only notable gaps are the lack of explicit guidance on the required 'message' parameter and the expected response, but the tool's simplicity keeps the overall completeness high.
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 0%, so the free-text description must compensate. It clarifies that 'conversation' should contain recent messages for reproduction, but leaves 'message' and 'context' semantics implicit, forcing the agent to infer their meaning from the tool's purpose.
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 uses a specific verb 'Report' with the resources 'bug, missing feature, or feedback', clearly distinguishing it from sibling tools like authenticate and marketplace. It also adds a practical instruction about including the conversation array, reinforcing the tool's unique role.
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?
Provides clear context: use when reporting bugs, missing features, or feedback. It does not explicitly state when not to use or name alternatives, but given no sibling tool serves a similar purpose, the guidance is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
show_versionARead-onlyIdempotentInspect
Show the current MCP platform and adapter versions.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds no extra behavioral context beyond restating the read-only purpose. It neither contradicts nor enriches the annotation-based safety profile.
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 a single, front-loaded sentence with zero filler. Every word earns its place.
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 simple zero-parameter tool with strong annotations, the description is sufficient. It does not detail the output format, but the tool's simplicity and purpose make this a minor gap rather than a deficiency.
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 tool has zero parameters, so the baseline of 4 applies. The description correctly implies no inputs are needed, and no parameter explanation is required.
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 verb ('Show') and the specific resource ('current MCP platform and adapter versions'). It is unambiguous and distinguishes this from sibling tools like authenticate or marketplace.
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 intended context (checking versions) is obvious from the description. It does not explicitly mention alternatives or exclusions, but no real alternatives exist for a version-info tool. This is clear context without missing guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
toolkit_infoARead-onlyIdempotentInspect
Returns the current toolkit state: installed MCPs, their connection status, the accounts connected to each one, and how many catalog tools each exposes.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, covering the safety profile. The description adds useful context about the exact content of the returned state (installed MCPs, connection status, etc.), going beyond annotations without contradicting them.
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 a single, well-structured sentence that is front-loaded with the main purpose and includes specific details. Every word adds value, and there is no redundancy or 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 simple read-only tool with no parameters and no output schema, the description sufficiently explains what the agent will receive. It enumerates the key elements of the returned state, making it complete for the tool's complexity level.
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 tool has zero parameters, so the schema trivially covers 100% of them. Per the rubric, a baseline of 4 is appropriate since there is nothing for the description to document beyond the fact that no input is needed.
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 toolkit state, enumerating specific data (installed MCPs, connection status, accounts, catalog tool counts). It uses a specific verb ('Returns') and identifies a distinct resource, differentiating it from siblings like show_version which likely only provides version info.
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 on what the tool offers but does not explicitly state when to use it versus alternatives. Since siblings like authenticate and connect serve different purposes, the intended use is implied rather than explicitly contrasted, missing a definitive when-not guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
No tool schema history has been recorded yet.
Frequently Asked Questions
Claiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as
io.github.alice/server, link the matching GitHub user, then choose Claim with GitHub. An organization namespace such asio.github.acme/serveralso needs that organization to have installed the Glama AI GitHub App and approved its permissions, because GitHub discloses organization membership only to apps it has installed. Use HTTP or DNS when it has not.HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at
/.well-known/glama.jsonon the same origin as the connector, then choose Check HTTP challenge.DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
Discussions
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Glama MCP Gateway
Add one secure layer between your agents and this server.
TDQS
The set mixes platform utilities (authenticate, connect, show_version), a bug reporter, and one domain-specific Brazilian vehicle-docs query tool (ecrvsp_docs_escolher_placa_consultar). The `marketplace` tool is the worst offender: its description claims it can search, describe, invoke, install, subscribe, and handle prompts—an entire parallel application that an agent would have no reason to distinguish from the main server. authenticate/connect also blur around connection state vs. action.
Conventions are mixed: single-word bare verbs (`connect`, `authenticate`), snake_case `verb_noun` (`report_bug`, `show_version`), a noun phrase (`toolkit_info`), and a long Portuguese snake_case string (`ecrvsp_docs_escolher_placa_consultar`). The inconsistent Portuguese/English mix and inconsistent verb-first vs. noun-first patterns make the surface unpredictable.
At 7 tools, the count is right in the sweet spot, and most are generic platform utilities that plausibly need to exist. However, six of the seven are generic infrastructure, leaving only one tool to represent the actual product domain, while `marketplace` crams dozens of capabilities into a single mis-sized tool. The count looks fine numerically but is lopsided in practice.
The domain (ECRVSP plate selection/consultation) has exactly one operation: `consultar` (query). There is no way to save a plate, view historical lookups, retrieve a document/receipt, handle multiple document types, or resolve a failed lookup—so any multi-step workflow hits a dead end immediately. The `marketplace`'s wrapper capabilities don't fill these gaps, and the actual product surface feels like just one CRUD read among many missing operations.