SENATRAN: Validar CNH
Server Details
SENATRAN: Validar CNH, official-source lookup. Platform-hosted, pay per query with prepaid credit.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- mcp-dir/senatran_validar_cnh-mcp
- GitHub Stars
- 0
- Server Listing
- SENATRAN: Validar CNH
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?
Annotations already declare idempotentHint=true and non-destructive behaviorchen, so the description adds detail about permanent vs session-only login and the need for user interaction (browser login). It doesn't explain what the tool returns, but that's less critical for auth. With annotations covering safety, this is adequate.
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 pack in purpose, two usage modes, and the argument contract without redundancy. Every clause earns its place, and the description is front-loaded with the key 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?
Given the tool has only one optional parameter and no output schema, the description covers the essential usage scenarios and distinguishes between permanent and session-based auth. It doesn't discuss edge cases like re-authentication or error handling, but for this simplicity it 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?
Schema coverage is 0%, so description must compensate. It explains the 'token' parameter meaning (JWT to paste for session-only login) and clarifies that calling without args returns the auth link. This adds meaningful semantics beyond the bare string type.
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 explicitly states it authenticates the user for MCP.AI via browser login or token, and distinguishes from siblings like 'connect' and 'marketplace' which serve other purposes. The verb 'authenticate' is specific and the resource context is clear.
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?
It gives explicit when-to-use guidance (first-time setup, session vs. permanent auth) and alternatives (config header vs. token param). Even explains the no-arg call for getting the link, covering all invocation modes.
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?
With readOnlyHint and idempotentHint annotations already declaring the read-only, safe nature, the description adds value by detailing the return structure for both connected and missing-credential scenarios. It stops short of covering all possible edge cases but provides meaningful insight into expected behavior.
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, both meaningful and concise. The description front-loads the purpose and efficiently explains two distinct behavioral outcomes without unnecessary detail.
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 status-checking tool with no parameters and no output schema, the description covers the primary states (all connected, missing credentials) but does not mention error conditions or partial connectivity beyond missing credentials. It strikes a good balance for a straightforward tool.
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 no parameters, and the schema coverage is 100% (vacuous). Per the rubric, a baseline of 4 applies when there are zero parameters, and the description does not add any parameter-related information since none exists.
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 details about return values in different states. However, it does not distinguish itself from sibling tools like 'authenticate' or 'toolkit_info', missing the opportunity to highlight unique use cases.
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 to check connection status, and the behavior in two states gives context on when it's relevant. However, it lacks explicit guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or conditions for invoking it.
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?
The description discloses rich behavioral traits: invoke runs one-off without installing, install makes permanent, writes require owner/admin, and invoke returns connect/checkout links for auth/payment. This goes well beyond the minimal annotations (readOnlyHint=false, openWorldHint=true), detailing side effects and error paths.
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 and front-loaded with the core flow, using caps for emphasis ('PERMANENT', 'KEY') to aid scanning. However, it's a single long paragraph that could be better structured with sentence breaks or bullets for readability, though it remains information-rich.
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 23 parameters and multiple sub-actions, the description covers discovery, invocation, installation, billing, auth, and the prompt library comprehensively. It addresses key decision points (invoke vs install, when to use list_tools) and auth requirements, making it highly complete for its complexity.
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?
While the description explains the action enum (search, describe, invoke, etc.) and mentions tool_id, arguments, and prompt-related params, it does not document most of the 23 parameters (e.g., limit, immediate, tier_slug). With 0% schema coverage, it partially compensates by explaining the core flow but leaves many parameters ambiguous.
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: 'the in-platform catalog of every MCP/tool, AND the way to run them.' It details the core flow (search → describe → invoke) and distinguishes from siblings like list_tools and report_bug, using specific verbs and resources.
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 explicitly instructs when to use this tool: 'Use install only to make an MCP PERMANENT... prefer invoke for a single/occasional use' and names alternatives like list_tools for 'what is callable right now' and request_mcp for 'a NEW MCP when nothing fits.' It also clarifies auth requirements for writes.
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 indicate non-read-only, idempotent, and non-destructive behavior. The description adds that it sends feedback and includes reproduction data, but does not detail side effects or outcomes. Adequate given 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?
The description is a single, clear sentence that front-loads the purpose and provides a key usage hint. No redundancy or unnecessary detail.
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 reporting tool, it covers essential context: what it does and a key parameter hint. It doesn't mention the role of 'context', but that is a minor omission. Overall sufficient.
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 description explains the purpose of the 'conversation' parameter (for reproduction) but leaves 'message' and 'context' implicit. With zero schema descriptions, this partial coverage is moderate.
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: 'Report a bug, missing feature, or send feedback.' It is distinct from sibling tools (authenticate, connect, marketplace, etc.) which serve unrelated functions.
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?
It explicitly indicates when to use (for reporting bugs/feedback) and gives a specific usage instruction ('Include the conversation array...'). It does not explicitly compare with alternatives, but the purpose is self-evident.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
senatran_validar_cnh_consultarARead-onlyIdempotentInspect
SENATRAN: Validar CNH, 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 |
|---|---|---|---|
| cpf | Yes | ||
| nome_mae | No | ||
| registro | Yes | ||
| login_cpf | No | ||
| login_senha | No | ||
| pkcs12_cert | No | ||
| pkcs12_pass | No | ||
| nome_condutor | No | ||
| codigo_seguranca | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Behavioral context goes well beyond annotations: it discloses paid consumption with prepaid credits, absence of platform credentials, official-source nature, non-confidential status, and LGPD accountability. This is meaningful additional context on top of readOnlyHint/idempotentHint.
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 compact and front-loaded with the core purpose, followed by payment and legal context. Each sentence contributes meaningfully, though the LGPD sentence, while relevant, adds context rather than operational guidance.
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 high parameter count, zero schema coverage, and absence of an output schema, the description is incomplete. It does not explain how parameters should be populated, what constitutes a valid response, or which optional fields are required under different consultation modes.
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?
Input schema description coverage is 0% and the description does not explain any of the 9 parameters, including the 3 required ones (cpf, registro, codigo_seguranca). It also fails to clarify the authentication-related optional parameters (login_cpf/login_senha, pkcs12_cert/pkcs12_pass), leaving the agent without guidance on which parameters to use in which scenario.
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 identifies the tool as a CNH validation/consultation against official SENATRAN sources, using an explicit verb and resource. The scope ('Validar CNH') differentiates it from generic sibling tools like connect 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 context of use is clear: the tool is for querying CNH data from official Brazilian sources. There are no explicit exclusion statements or alternative tool recommendations, but no sibling performs a similar function, so a 'when to use' guidance is already sufficient; only the 'when not to use' part is missing.
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, destructiveHint=false, covering the safety profile. The description adds that it returns platform and adapter versions, but doesn't detail output format or additional behavior. It adds some value beyond annotations but not rich context.
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 concise sentence that fully conveys the purpose with zero waste. It is front-loaded and to the point.
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 no parameters, no output schema, and strong annotations, the description is complete enough. It states exactly what the tool does and is sufficient for an agent to select and invoke it 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?
There are zero parameters, so the baseline is 4. No parameter explanation is needed, and the description doesn't need to compensate. It correctly has no parameter details since none exist.
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: showing current MCP platform and adapter versions. This is a specific verb (show) + resource (versions) and is distinct from sibling tools like authenticate, connect, marketplace, etc.
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 (when you need to check versions) but provides no explicit guidance on when to use it vs alternatives, nor any exclusions. For a simple version tool, this is acceptable but not explicit.
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 indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds meaningful behavioral context by specifying exactly what state information is returned (installed MCPs, connection status, accounts, catalog tool counts). It does not contradict the annotations and provides useful detail beyond 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, front-loaded sentence that begins with the action ('Returns') and the object ('current toolkit state'), then lists the key components in a compact list. Every clause earns its place with 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?
Given the tool's simplicity (no parameters, no output schema), the description is fully complete. It tells the agent what the tool does and what the return value contains, which is sufficient to select and invoke it correctly. The annotations cover side-effect safety, and the description covers the informational content.
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 is complete and there is nothing for the description to explain about parameter semantics. The baseline of 4 applies, and the description appropriately focuses on the output rather than nonexistent inputs.
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 uses a specific verb ('Returns') and clearly identifies the resource ('current toolkit state'), then enumerates the exact contents: installed MCPs, connection status, connected accounts, and catalog tool counts. This distinguishes it from sibling tools like authenticate or connect, which perform actions rather than report state.
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 makes the tool's purpose and context clear: it is a read-only informational tool for inspecting toolkit state. It does not explicitly state when to use it instead of alternatives like show_version, but the enumerated output strongly implies its use as a status/diagnostic tool, so the context is clear without exclusions.
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
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Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
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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
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Claim ownership of the server listing
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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
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Discussions
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TDQS
The CNH query tool is clearly distinct from the platform utilities, and each utility has a generally separate role. The main ambiguity is between connect, authenticate, and toolkit_info, which all revolve around connection/status but still have enough detail to distinguish them in most cases.
Naming is inconsistent: some tools are single-word verbs (authenticate, connect), some are underscore verb phrases (report_bug, show_version), one is a bare marketplace noun, and the domain tool uses an awkward Portuguese-style mixed name (senatran_validar_cnh_consultar). There is no predictable naming convention.
Seven tools is not an unreasonable count, but only one tool actually serves the stated SENATRAN CNH purpose while the other six are generic platform, marketplace, connection, version, and toolkit utilities. The set feels padded with platform infrastructure rather than being scoped to the CNH validation domain.
The domain is essentially consult/validate CNH, and the single domain tool does cover that core need. Some auxiliary CNH features such as quota/balance visibility or batch validation are not present, but they are partly handled by the surrounding platform tools, so there is no critical dead end.