DETRAN GO: Débitos
Server Details
DETRAN GO: Debts, official-source lookup. Platform-hosted, pay per query with prepaid credit.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- mcp-dir/detran_go_debitos-mcp
- GitHub Stars
- 0
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 include readOnlyHint=false, destructiveHint=false, and idempotentHint=true. The description adds context by explaining the two modes (config header vs session token), the JWT format, and the browser login flow. It goes beyond the annotations in detailing security aspects and session persistence, though it doesn't describe the return value or side effects beyond the link.
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 one long paragraph with many clauses, making it dense and harder to parse. While all information is relevant, it could be restructured into clearer sections (e.g., configuration vs session-based flow) to improve readability. It front-loads the main purpose but then mixes details of both methods.
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 an authentication tool with no output schema, the description adequately covers the key behaviors: how to obtain a link, how to provide a token, and the persistent vs session options. It gives enough context for an agent to decide how to invoke it, though it could mention what the tool returns (e.g., the link itself) explicitly.
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 schema has 0% description coverage for the token parameter, but the description fully explains its meaning: 'call with { token: "<jwt>" } after the user pastes, or with no args to get the link.' This clarifies that the token is a JWT and optional, directly compensating for the schema gap.
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: 'MCP.AI for IDE agents (Cursor, etc.): log in in the browser, copy the access token.' It defines the action (authenticate) and distinguishes from siblings like connect and marketplace by detailing the token-based authentication flow.
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 explains two usage scenarios: 'Best: add it to this server's config as a header ... for a permanent, non-expiring connection. Or paste it here for a session-only login: call with { token: "<jwt>" } after the user pastes, or with no args to get the link.' This provides clear when-to-use guidance, though it doesn't explicitly state when not to use it or name alternatives beyond these methods.
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?
Despite annotations already indicating read-only and idempotent behavior, the description adds valuable context about conditional responses—e.g., "returns authenticated:true and empty pending[]" vs. "returns connect_url for the toolkit and per-install URLs." This enriches the agent's understanding beyond the structured hints.
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, front-loaded with the core purpose and efficiently adds conditional behavior. There is zero redundancy, making every word earn 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?
Given the tool's simplicity, the description covers both success and failure scenarios (all providers connected vs. missing credentials). Combined with rich annotations and no output schema, it is fully self-contained for an agent to 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?
The tool has zero parameters, triggering the baseline of 4 as per the rubric. The description does not need to add parameter-specific details since none exist, and the baseline appropriately reflects the minimal burden.
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," which is a specific verb+resource combination. It distinguishes itself from siblings like authenticate, show_version, and toolkit_info by focusing on connection state, with no ambiguity.
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 checking connection status and handling missing credentials, but it does not explicitly mention when not to use it or name alternatives. While context is clear, there are no exclusions or alternative referrals, warranting a 4.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
detran_go_debitos_consultarBRead-onlyIdempotentInspect
DETRAN GO: Débitos, 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 |
|---|---|---|---|
| placa | Yes | ||
| renavam | Yes | ||
| login_cpf | No | ||
| login_senha | No | ||
| pkcs12_cert | No | ||
| pkcs12_pass | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is clear. The description adds valuable context: it's hosted by the platform, requires prepaid credit per query, no platform credentials needed, and data is not confidential. It also clarifies the client's LGPD responsibility. This goes beyond 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 paragraph, reasonably concise, and front-loaded with the core purpose. It includes necessary legal and payment context. It's not overly verbose, though it could be more structured. Every sentence adds value.
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 6 parameters with 0% schema coverage and no output schema, the description should explain more. It covers the purpose and some operational context (payment, LGPD) but leaves parameter semantics and expected output unclear. For a query tool with readOnlyHint, it's adequate but not 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 description coverage is 0%, so the description must compensate. It mentions 'placa' and 'renavam' implicitly by context (vehicle debts) but doesn't explain any parameters. The optional login_cpf, login_senha, pkcs12_cert, pkcs12_pass are completely unexplained. The description fails to clarify what these parameters mean or when they're 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's purpose: consulting vehicle debts (Débitos) from DETRAN GO official source. It specifies the resource (DETRAN GO debts) and the action (consultar/query). It distinguishes from siblings by being a specific domain tool, though it doesn't explicitly contrast with other tools.
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 context on when to use: for consulting official Brazilian sources, with prepaid credit, and notes it's not confidential data. However, it doesn't explicitly state when not to use it or mention alternatives. The payment model and LGPD compliance are useful but not direct usage guidelines.
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 adds substantial behavioral context beyond annotations: invoke runs one-off without installing, credential gaps return a connect link, empty wallets return a checkout link and require retry, writes require owner/admin, and search/describe expose installed_in_toolkit vs installed_in_workspace. There is no contradiction with 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?
The description is long but information-dense; nearly every clause adds value, especially around the search→describe→invoke flow and install vs invoke decision. However, it is a single dense wall of text without bullets or section breaks, which reduces scannability despite the content being relevant.
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 complex multiplexer with 23 params and no output schema, the description covers discovery, one-off execution, auth/billing redirects, permission requirements, permanent installation, and the prompt library. It is not fully exhaustive—it does not describe return shapes for every action—but it is remarkably complete for the tool's 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?
Schema description coverage is 0%, so the description must compensate. It explains the role of key params like action, mcp_id, tool_id, arguments, and prompt-related fields, but many of the 23 parameters (limit, query, immediate, tier_slug, cancel_reason, request_details, report_context, prompt_targets, etc.) remain undocumented. It gives broad flow-level semantics but not individual parameter meaning.
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 marketplace as mcp.ai's in-platform catalog and execution layer, enumerating a full action set (search, describe, invoke, install, subscribe, prompt library). It distinguishes itself from sibling tools by its central role, but because it is an action-dispatching tool rather than a single verb+resource, purpose is slightly diffuse.
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 guidance is explicit and actionable: prefer invoke for occasional use, install only for making an MCP permanent, list_tools for currently callable tools, and search/describe for discovery. It also states when invoke works even without installation and names alternatives such as subscribe/cancel, report_bug, and request_mcp.
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 idempotentHint=true and destructiveHint=false. The description adds one behavioral detail: the conversation array is used for reproduction. However, it does not explain side effects (e.g., sending data externally) or response behavior, so coverage is modest but not contradictory.
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 concise sentences, front-loaded with the purpose, and contains no fluff. Every sentence adds value: the first states what the tool does, the second instructs on reproduction data.
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 with three parameters and no output schema, the description covers the core purpose and one key parameter, but omits 'context' and any explanation of expected return value or side effects. It is adequate for basic usage but not fully 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 description coverage is 0%, so the description must compensate. It explains the 'conversation' parameter as an array for reproduction, but the schema defines it as a string, creating potential mismatch. The required 'message' and optional 'context' are not described. This is insufficient compensation 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 'Report a bug, missing feature, or send feedback,' using a specific verb and resource. It fully communicates the tool's purpose and is easily distinguishable from the unrelated siblings (authenticate, connect, 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 description provides clear context for when to use the tool (when a bug, missing feature, or feedback exists) and gives a practical instruction: 'Include the conversation array with recent messages for reproduction.' It does not explicitly mention alternatives or exclusions, but no similar sibling tool exists.
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, idempotentHint, and destructiveHint false, covering safety. The description adds no extra behavioral details (e.g., authentication requirements, network calls, or return formatting), so it provides minimal additional value 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?
A single, front-loaded sentence that states exactly what the tool does. No filler or redundancy—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 zero-parameter, read-only version query, the description is fully sufficient. It explains the tool's purpose completely, and since there's no output schema, no return-format details are required. The low complexity and complete annotations make this description adequate.
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 zero parameters and 100% schema coverage (empty properties object), the description doesn't need to explain parameters. Baseline for no parameters is 4, and the description correctly avoids redundant parameter information.
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 ('show') and resource ('MCP platform and adapter versions'), clearly distinguishing it from sibling tools like authenticate, connect, or marketplace. No ambiguity.
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 its use as a version-check utility but provides no explicit guidance on when to use it versus alternatives. No exclusions or context are given, but the tool is simple enough that the intended use is clear.
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 readOnly, idempotent, and non-destructive behavior. The description adds specific detail about the content returned (installed MCPs, connection status, accounts, catalog counts), which goes beyond the annotations and provides useful context about the tool's output.
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 directly states the tool's purpose and output. No unnecessary words or fluff.
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 query tool with no parameters and no output schema, the description is fully complete. It explains what the tool does and what information it returns, leaving no ambiguity.
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 score of 4 applies. There is nothing to explain about parameters, and the description does not need to cover them.
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 that the tool returns the current toolkit state and enumerates exactly what that includes (installed MCPs, connection status, accounts, catalog tool counts). It is specific and distinguishable from sibling tools like authenticate or connect, which perform actions.
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 that this is a read-only query tool, but it does not explicitly state when to use it versus alternatives. There is no direct guidance on use cases or when not to use it, though its purpose is fairly self-evident for checking state.
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
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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
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Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
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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
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Discussions
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Related MCP Connectors
DETRAN GO: Vehicle, official-source lookup. Platform-hosted, pay per query with prepaid credit.
DETRAN GO: Gravame, official-source lookup. Platform-hosted, pay per query with prepaid credit.
DETRAN DF: Debts, official-source lookup. Platform-hosted, pay per query with prepaid credit.
SEFAZ GO: IPVA, official-source lookup. Platform-hosted, pay per query with prepaid credit.
Related MCP Servers
- AlicenseNot gradedqualityCmaintenanceMCP server for querying vehicle debts (débitos) from DETRAN DF's official source. It is read-only and works with any MCP client over HTTP, with pay-per-use prepaid credits.MIT
- AlicenseNot gradedqualityCmaintenanceRead-only MCP server for consulting IPVA (vehicle property tax) data from the official SEFAZ GO source in Brazil, using prepaid credits and compatible with any MCP client.MIT
- AlicenseNot gradedqualityCmaintenanceEnables querying DETRAN Ceará traffic fine issuance data from official sources via a read-only MCP tool, with pay-per-use prepaid credits and magic-link login.MIT
- AlicenseNot gradedqualityCmaintenanceEnables querying vehicle licensing information from DETRAN AL (Alagoas, Brazil) via an official read-only MCP tool, with pay-per-use credit system and no credentials required.MIT
Glama MCP Gateway
Add one secure layer between your agents and this server.
TDQS
The single domain tool is clearly distinct from the platform utilities. authenticate and connect overlap slightly around credentials/connection status, but their descriptions separate login from status checking. No other tools are confusable.
Names mix bare verbs (authenticate, connect), English verb_noun pairs (report_bug, show_version), noun-only names (marketplace, toolkit_info), and a Portuguese snake_case domain verb (detran_go_debitos_consultar). There is no consistent naming convention across the set.
Seven tools is not an excessive number, but six are generic platform/marketplace utilities while only one addresses the server's stated DETRAN GO debts domain. The count is reasonable overall, yet the scope feels mismatched with the server name.
For a debts-consultation server, only one domain operation exists, with no query variety or broader debt-related workflow. The platform tools are fairly complete for managing MCPs, but they do not fill the domain-specific gap implied by the server name.