Histórico Veicular SP
Server Details
History of vehicles linked to a CPF or CNPJ in the state of São Paulo. Platform-hosted, no credentia
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- mcp-dir/veiculo_historico_sp-mcp
- GitHub Stars
- 0
- Server Listing
- Histórico Veicular SP
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 indicate idempotentHint=true and destructiveHint=false, but the description adds valuable context about the non-expiring nature of the config-based connection and the session-only behavior of token-based login. It also explains the browser login flow, going beyond the structured metadata.
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, information-dense paragraph that fronts the purpose and then provides clear instructions. While it is somewhat long, every sentence adds value; the structure could be slightly improved with separators, but it remains efficient.
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 covers the essential use cases: both login modes, the config recommendation, and the no-argument behavior. It omits explicit return values, but given the simplicity of the tool, this is not a critical gap.
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% coverage for the token parameter, but the description thoroughly explains it: the token is a JWT pasted by the user, and calling with no arguments returns the login link. This fully compensates 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 by logging in via browser and obtaining an access token, with options for permanent (config) or session-only (token) login. It distinguishes itself from siblings like 'connect' and 'marketplace' by focusing on the specific 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?
The description provides explicit usage instructions: how to use the config-based approach for a permanent connection, how to use the token parameter for session-only login, and calling with no arguments to get the link. It does not explicitly compare to sibling tools, but the alternatives and when to use each mode are clearly stated.
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 provide readOnlyHint=true and destructiveHint=false, and the description adds value by explaining the exact return payloads in different states (all providers connected vs missing credentials). It also discloses the presence of connect_url, per-install URLs, and the pending[] array, offering transparency 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?
Two compact sentences front-loaded with the core purpose ('Returns connection status and URLs') and efficient conditional details. No wasted words.
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 status tool, the description fully covers expected outcomes in both connected and missing-credential scenarios. There is no output schema, so explaining return fields is essential, and this description delivers it clearly.
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 and an empty schema, so the baseline is 4. The description does not need to explain parameters, and the focus on return values 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 conditional outcomes (authenticated:true vs connect_url). This distinguishes it from sibling tools like authenticate, which likely performs authentication 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 the tool is used to check connection status, but it does not explicitly state when to use it versus alternatives like authenticate. The conditional behavior (when credentials missing vs present) gives context but no explicit guidance on when to choose this tool over siblings.
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 annotations (readOnlyHint=false, openWorldHint=true), the description discloses key behaviors: invoke runs even without installation, returns connect/checkout links for auth/payment, and lists that writes require workspace owner/admin. This adds significant contextual value beyond the minimal 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, with each sentence covering a distinct aspect. It front-loads the core flow and then expands into behaviors and prompt library. Minor redundancy could be trimmed, but structure is acceptable for the breadth of functionality.
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 description covers primary workflows and caveats (auth, payment, permissions, one-off vs permanent). However, some actions like resume, report_bug details, and prompt publishing specifics are only mentioned by name without usage context. Given the extensive scope, it's reasonably complete but not exhaustive.
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 23 parameters and 0% schema description coverage, the description bears a heavy burden. While it explains the action flow conceptually (e.g., 'describe returns a profile', 'invoke RUNS that tool'), it never explicitly names parameters like mcp_id, tool_id, arguments, or prompt_slug. Agents must infer which schema fields correspond to each action, creating ambiguity for a tool this complex.
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, explicitly listing its core actions (search, describe, invoke, install) and distinguishing it from sibling tools focused on specific integrations. The verb+resource structure is specific and 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 provides explicit guidance on when to use each action: prefer invoke for one-off use, install for permanent toolkit addition, list_tools for current callable tools, request_mcp for new builds, and distinguishes the prompt library separate from MCPs. It also notes permission 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 provide idempotentHint=true and destructiveHint=false, so the safety profile is covered. The description adds the requirement to include conversation context for reproduction, which is useful behavioral information. However, it does not disclose what happens after submission (e.g., ticket creation, feedback logging) or any potential side effects 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?
The description is a single sentence that delivers the core purpose and a critical usage instruction. It is front-loaded and every word earns its place, with no redundant information.
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 description covers the basic purpose and one parameter, but it lacks explanation of expected output, the format of the conversation parameter (schema type is string, description says 'array'), and any side effects. For a simple reporting tool, it is adequate but leaves notable 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?
Schema description coverage is 0%. The description adds meaning to the 'conversation' parameter by explaining it should contain recent messages for reproduction, but it does not explicitly describe 'message' or 'context'. The overall purpose implies 'message' is the report content, but this is left to inference.
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.' The verb 'Report' and resource categories (bug, feature, feedback) are specific and distinct from sibling tools, which focus on authentication, connection, 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 when to use the tool (when the user wants to report issues or send feedback). It also provides a concrete usage guideline: 'Include the conversation array with recent messages for reproduction.' No explicit exclusions or alternatives are named, but the usage context is clear.
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 that the tool reports both platform and adapter versions but does not disclose additional behavioral traits such as output format or network requirements.
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?
One sentence, directly front-loaded with the action and object, no extraneous content.
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, empty parameter schema, and annotations covering safety, the single-sentence description fully covers the tool's purpose and scope. No output schema exists, but for a version-check tool this is 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 tool takes zero parameters, so the description is not required to explain parameter semantics. The baseline of 4 applies.
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 specifies the exact resource ('current MCP platform and adapter versions'), making its function clear and distinguishable from sibling tools like toolkit_info or authenticate.
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 does not explicitly state when to use this tool versus alternatives, though the need for version information is implied. No exclusions or alternative tool references are provided.
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?
The annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds value by enumerating what state is returned (installed MCPs, connection status, accounts, tool counts), which is not present in the annotations. It doesn't disclose rate limits or pagination, but none are expected for a simple state query.
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 sentence that front-loads the main action ('Returns the current toolkit state') and then lists the specific data items. Every word contributes meaning with no fluff or repetition.
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 read-only info tool with no output schema and rich annotations, the description fully specifies what the agent can expect: installed MCPs, their connection status, connected accounts, and catalog tool counts. There are no missing prerequisites or side effects to disclose, and the tool is simple enough that this description is complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, so the baseline is 4. The description correctly adds no parameter information because there are none to explain.
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 identifies the resource ('current toolkit state') with concrete details (installed MCPs, connection status, accounts, catalog tools). This clearly 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 it evident when to use this tool—whenever an agent needs an overview of the toolkit's MCP connections and accounts. It doesn't explicitly name alternatives or exclusions, but the clear informational purpose contrasts with the action-oriented sibling tools, providing enough context to select it appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
veiculo_historico_sp_consultarARead-onlyIdempotentInspect
Histórico dos veículos vinculados a um CPF ou CNPJ no estado de São Paulo. Hospedado pela plataforma, sem credenciais, pague por consulta com crédito pré-pago. Consulta informação de ACESSO PÚBLICO em bases e fontes oficiais (a mesma disponível ao cidadão), não é dado privado nem sigiloso. O cliente é o controlador dos dados e responde pela finalidade legítima (LGPD).
| Name | Required | Description | Default |
|---|---|---|---|
| Cpf | Yes | ||
| Cnpj | Yes | ||
| completo | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, and the description adds meaningful context: no credentials needed, pay-per-query, access to public data, and LGPD data-controller responsibilities. This goes beyond the basic safety 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 concise and front-loaded: it states the purpose first, then access/payment, data nature, and legal responsibilities. Every sentence contributes necessary information, with no fluff or repetition.
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 description is moderately complete for a query tool: it explains the source, access, and legal context. However, it omits details about the 'completo' parameter, the response format, and any pagination or filtering behavior. No output schema exists, so the description should provide more behavioral coverage.
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% for all 3 parameters. The description only mentions 'CPF ou CNPJ' without explaining the parameters' format, the odd requirement of having both Cpf and Cnpj mandatory, or the purpose of the 'completo' boolean. The description does not compensate for the complete lack of schema descriptions.
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: 'Histórico dos veículos vinculados a um CPF ou CNPJ no estado de São Paulo.' This is a specific verb+resource+scope, and it distinguishes the tool from the listed siblings (authenticate, connect, marketplace, etc.), none of which are similar data-query 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 clear usage context: it is hosted by the platform, requires no credentials, and is paid via prepaid credits. It also clarifies that it accesses public information. However, it does not explicitly state when to use this tool versus alternatives, though no similar sibling tools exist.
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
Most tools have distinct purposes: authenticate is for login token, connect for status, marketplace for discovering/running MCPs, report_bug for feedback, show_version for versions, toolkit_info for installed state, and the domain-specific consultar tool. The only slight overlap is between authenticate and connect, as both relate to connection/auth, but their functions are clearly differentiated in the descriptions.
Tool names follow no consistent pattern: single verbs (authenticate, connect), nouns (marketplace), verb_noun (report_bug, show_version), compound nouns (toolkit_info), and a snake_case domain-specific name (veiculo_historico_sp_consultar). Mixing conventions makes it hard to predict related tool names.
Seven tools is within the typical well-scoped range. However, the server bundles broad platform utilities with a single domain-specific tool, creating a mismatch with the server name. Still, the count itself is reasonable for the actual functionality offered.
For the vehicle history domain, there is only one consult tool, which covers the basic query but lacks any supporting operations (e.g., history, status, or batch). The platform utilities are fairly complete but belong to a different purpose. This leaves notable gaps if the server is meant to be a cohesive vehicle-history service.