Registradores (ARISP) Matrícula: Download de Recibo
Server Details
Registradores (ARISP) Matrícula: Download de Recibo, official-source lookup. Platform-hosted, pay pe
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- mcp-dir/registradores_matric_recibo-mcp
- GitHub Stars
- 0
- Server Listing
- Registradores (ARISP) Matrícula: Download de Recibo
Available Tools
7 toolsauthenticateAIdempotentInspect
MCP.AI for IDE agents (Cursor, etc.): log in in the browser, copy the access token. Best: add it to this server's config as a header Authorization: Bearer <token> for a permanent, non-expiring connection. Or paste it here for a session-only login: call with { token: "" } after the user pastes, or with no args to get the link.
| Name | Required | Description | Default |
|---|---|---|---|
| token | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions the two modes (permanent via config header, session-only via token) and implies idempotency ('non-expiring'), but does not explicitly discuss security implications or side effects of storing tokens. It does not contradict 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 concise yet comprehensive, packing all necessary details into three sentences with clear structure (main method, best method, alternative method).
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 complexity (authentication with two modes), the description covers all necessary aspects: how to invoke it, the token parameter, and the two usage contexts. It does not require an output schema explanation as none is provided.
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 one optional token parameter with no description, but the tool description explains its meaning ('jwt') and usage ('call with { token: '<jwt>' }'), fully covering the parameter's purpose and optional nature.
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 is for authentication ('log in', 'access token', 'login') and distinguishes it from other tools like connect, marketplace, and report_bug by focusing on credential handling.
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 provides explicit usage instructions: log in via browser, copy token, and either add to config as a header or pass it as a parameter, with details on when to use each method (permanent vs. session-only).
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 indicate readOnlyHint, idempotentHint, destructiveHint all safe. The description adds useful context about the two possible states (all connected vs missing credentials) and what URLs are returned, which goes beyond the bare annotations. It does not contradict 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 sentences, no unnecessary words. The description is front-loaded with 'Returns connection status and URLs' and immediately explains the two scenarios. Highly concise and well-structured.
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 tool with safe annotations and no output schema, the description fully addresses what the tool does and the different outputs under different conditions. It's complete for the agent to understand invocation and expected results.
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 schema coverage is 100% trivially. The baseline for 0 params is 4. The description adds value by explaining what the tool returns, though it doesn't elaborate on any parameters (none exist). This is adequate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns connection status and URLs, with specific conditions for different output (authenticated:true vs connect_url). It distinguishes from sibling 'authenticate' which likely handles the connection process, so purpose is specific and differentiated.
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 explains what happens under different conditions but does not explicitly state when to use this tool versus alternatives. It implies it's for checking connection status, but does not mention excluding cases like when authentication is needed (which the sibling 'authenticate' might handle). No explicit alternatives or when-not guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
marketplaceAInspect
The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them. Covers capability requests like "find an MCP that does X", "consulta um CPF", "is there a tool for Y". Core flow: action=search discovers MCPs by intent → describe returns one MCP's full profile (every tool with its id + params, pricing, auth) so you pick the right tool_id → invoke RUNS that tool. KEY: invoke works even when the MCP is NOT installed — it runs the tool pontualmente (one-off), without adding the MCP to the toolkit and without bloating the tool list. If the MCP needs a credential/login, invoke returns a connect link; if it is paid and the wallet is empty, invoke returns a checkout/top-up link (the user opens it, then you retry). Use install only to make an MCP PERMANENT in the active toolkit (its tools then show up natively in future sessions); prefer invoke for a single/occasional use. list_tools lists what is callable right now. subscribe/cancel handle per-MCP billing; report_bug sends feedback; request_mcp asks us to build a NEW MCP when nothing fits. Search/describe flag installed_in_toolkit vs installed_in_workspace. Writes (install/uninstall/subscribe/cancel and the one-off install behind invoke) require workspace owner/admin. It also carries the mcp.ai PROMPT LIBRARY, which is about ready-made prompt TEXT rather than MCPs: search_prompts finds one, get_prompt returns its full text with {{variables}} filled, and publish_prompt saves a prompt and returns a shareable mcp.ai/p/ link that opens without login.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | No | ||
| action | No | search | |
| mcp_id | No | ||
| message | No | ||
| tool_id | No | ||
| arguments | No | {} | |
| immediate | No | ||
| tier_slug | No | ||
| prompt_body | No | ||
| prompt_slug | No | ||
| prompt_tool | No | ||
| prompt_vars | No | {} | |
| conversation | No | [] | |
| prompt_title | No | ||
| request_name | No | ||
| cancel_reason | No | ||
| cancel_comment | No | ||
| prompt_targets | No | ||
| report_context | No | ||
| prompt_category | No | ||
| request_details | No | ||
| prompt_description | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations, the description discloses key behaviors: invoke runs tools even when not installed, returns connect links for missing credentials, returns checkout/top-up links for unpaid tools, and requires owner/admin for writes. It also explains the prompt library's shareable links open without login. 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 well-organized around the core flow, key invoke behavior, install vs. invoke, permissions, and the prompt library. Every sentence adds value, though the dense single-paragraph format could be improved with clearer separation of sections.
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 multi-action gateway with no output schema, the description covers the main workflows, permission requirements, billing/credential behavior, and the prompt library. It is incomplete on some parameters and omits the 'resume' action, but overall it is substantially complete for selecting and invoking the 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?
With 0% schema description coverage and 23 parameters, the description carries a heavy burden. It explains the action enum and core parameters (mcp_id, tool_id, arguments) through the workflow, but many parameters (limit, immediate, tier_slug, prompt_*, cancel_reason, etc.) are not addressed. It partially compensates but leaves significant gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as the mcp.ai marketplace, the in-platform catalog of MCPs/tools and the way to run them, with a concrete core flow (search → describe → invoke). It is clear but broad and does not explicitly differentiate from sibling tools like report_bug or connect, though it mentions report_bug as a sub-action.
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 gives explicit when-to-use guidance: use search/describe to discover, invoke for one-off runs, install only for permanent toolkit additions, list_tools for currently callable tools, and request_mcp when nothing fits. It also states that writes require workspace owner/admin, providing clear context for authorization-sensitive operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
registradores_matric_recibo_consultarBRead-onlyIdempotentInspect
Registradores (ARISP) Matrícula: Download de Recibo, 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 |
|---|---|---|---|
| No | |||
| senha | No | ||
| tipo_login | No | ||
| pkcs12_cert | No | ||
| pkcs12_pass | No | ||
| numero_pedido | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, covering safety. The description adds useful behavioral context: it's a paid query, hosted by the platform, returns non-confidential data, and includes LGPD compliance notes. This goes beyond the structured hints, though it doesn't detail side effects or return 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?
The description is a single informative paragraph covering purpose, hosting, payment, data source, and legal note. It's front-loaded with the main action and includes essential context without excessive verbosity, though some legal clauses could be considered extraneous.
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 does not explain the six input parameters (all optional), nor does it describe the output format or error conditions. Given 0% schema coverage and no output schema, the description fails to compensate for missing parameter documentation, leaving the agent without enough context to properly invoke the 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 description provides zero explanation of the 6 parameters (email, senha, tipo_login, pkcs12_cert, pkcs12_pass, numero_pedido). Schema coverage is 0%, and the description doesn't mention any of them, leaving the agent with no semantic guidance for parameter usage.
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 action ('Download de Recibo') and resource ('Registradores (ARISP) Matrícula'), distinguishing it from sibling tools like 'authenticate' or 'connect'. It's specific enough to know it's a receipt download/query for registration, though it could be more explicit about the query nature vs download.
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 some context (hosted by platform, paid per query, no platform credentials) but does not explicitly state when to use this tool vs. alternatives like 'authenticate' or 'connect'. It mentions it's a paid consult but lacks clear exclusion or alternative guidance.
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?
The description clearly indicates that the tool is for reporting and does not contradict the annotations of idempotent and non-destructive. It explicitly states the action (reporting) without implying unintended side effects, so the behavior is transparent.
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 extremely concise, consisting of two short sentences. It conveys the purpose and a key usage hint without any redundant 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 feedback submission tool, the description is sufficient. It explains what to report and what to include, and since there is no output schema, no return value explanation is required. It covers the essential context for an agent to use 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?
The description explains the 'conversation' parameter ('Include the conversation array') but does not clarify the 'message' or 'context' parameters. Since schema coverage is only about one of three parameters (0% overall coverage), the description adds value for that one but leaves the others 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 with a specific verb 'report' and the targets 'bug, missing feature, or send feedback.' It distinguishes itself from sibling tools like 'authenticate' or 'connect' by focusing on feedback submission.
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 actionable guidance on how to use the tool: 'Include the conversation array with recent messages for reproduction.' It implies the proper context (reporting issues) but does not explicitly state when to prefer this over alternatives, though the sibling tools are clearly unrelated.
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, fully covering the safety profile. The description adds that it returns current version information, but does not disclose output format or potential edge cases; it does not contradict 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, front-loaded sentence with no wasted words. It concisely communicates the action and the exact information returned.
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 low complexity, zero parameters, and strong annotations, the description is sufficiently complete for an agent to understand its purpose. It could optionally mention whether the result is plain text or structured data, but that is not essential for this trivial introspection 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 zero parameters, so schema coverage is effectively 100% and no parameter explanation is needed. The absence of parameter documentation is acceptable, supporting the baseline score of 4.
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 the explicit verb 'Show' with a specific resource: 'current MCP platform and adapter versions.' This clearly states what the tool does and distinguishes it from sibling tools like toolkit_info 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 description implies usage by naming the information returned, but it does not explicitly say when to use this tool versus alternatives. For a zero-parameter version inspection tool, this is adequate but lacks direct when-to-use or when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
toolkit_infoARead-onlyIdempotentInspect
Returns the current toolkit state: installed MCPs, their connection status, the accounts connected to each one, and how many catalog tools each exposes.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows this is a safe read operation. The description adds the specific content of the state (installed MCPs, connection status, accounts, catalog tool counts) which is useful context beyond the annotations. However, it doesn't describe return format or potential latency, but with strong annotations, a 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the purpose ('Returns the current toolkit state') and then enumerates the specific elements included. Every word earns its place 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 zero-parameter, read-only informational tool with strong annotations, the description is complete. It clearly states what the tool returns and the scope of that information. The lack of an output schema is acceptable since the description enumerates the key data points. It could potentially mention that this is a diagnostic tool, but the purpose is clear enough.
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 description doesn't need to explain parameter semantics. The baseline for 0 params is 4, and the description correctly focuses on what the tool returns rather than parameters. No additional parameter information is needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns the current toolkit state, listing specific elements: installed MCPs, connection status, connected accounts, and catalog tool counts. This is a specific verb+resource (returns state) and distinguishes it from siblings like authenticate, connect, and show_version.
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 this is a diagnostic/informational tool for checking the toolkit's current state, which is clear context. It doesn't explicitly state when not to use it or name alternatives, but the sibling tools (authenticate, connect, etc.) are clearly different actions, so the usage context is reasonably clear.
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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Add one secure layer between your agents and this server.
TDQS
The tool set mixes platform-level utilities (authenticate, connect, marketplace, report_bug, show_version, toolkit_info) with a single domain-specific tool (registradores_matric_recibo_consultar). The platform tools have overlapping purposes (connect vs toolkit_info vs authenticate all deal with connection state), and the marketplace tool is overloaded with many sub-actions (search, describe, invoke, install, subscribe, etc.) that could be separate tools.
Naming is inconsistent: platform tools use generic verbs (authenticate, connect, marketplace, report_bug, show_version, toolkit_info) with no consistent pattern, while the domain tool uses a long snake_case name (registradores_matric_recibo_consultar). The marketplace tool name is a noun rather than a verb_noun pattern, and there's no clear convention across the set.
7 tools is a reasonable count, but the set is unbalanced: 6 tools are platform infrastructure and only 1 is the actual domain tool (Registradores matrícula receipt). The platform tools could be consolidated (e.g., connect and toolkit_info overlap), making the count feel padded for a server whose stated purpose is a single receipt download service.
For the stated purpose (download receipt from Registradores/ARISP), the surface is severely incomplete: there is only one consult tool with no explicit download, history, or payment/credit management tools. The platform tools (marketplace, authenticate, etc.) are generic and don't cover the domain lifecycle, so an agent cannot complete a full receipt download workflow without external steps.