SABESP: Download de Conta
Server Details
SABESP: Bill Download, official-source lookup. Platform-hosted, pay per query with prepaid credit.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- mcp-dir/contas_sabesp_download_conta-mcp
- GitHub Stars
- 0
- Server Listing
- SABESP: Download de Conta
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?
Beyond the annotations, it discloses the browser login flow, the permanent/non-expiring nature of the config-header option, the session-only nature of the token paste, and the no-args link behavior. This is rich behavioral context and 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 compact and information-dense, front-loaded with the tool's purpose and audience. It is slightly run-on, but every clause contributes useful guidance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one optional parameter and no output schema, the description covers permanent and session modes, invocation patterns, and the no-arg link behavior. It does not describe response/error details, but those are not essential here.
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 only declares token as an optional string, so the description compensates by explaining that token is a pasted JWT/access token and by showing call shapes with and without it. It could mention invalid-token behavior, but the meaning of the only parameter is clear.
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 names the authentication action for MCP.AI IDE agents and explains the browser login/token flow. It does not explicitly contrast with the 'connect' sibling tool, so sibling differentiation is only implicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly distinguishes usage modes: a permanent config-header approach versus a session-only token paste, and states that no args returns the login link. This gives the agent concrete when-to-use guidance and alternatives within the tool.
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?
The description adds behavioral context beyond the annotations by explaining the two states (connected vs. missing credentials) and the corresponding return fields. This includes what happens when credentials are missing, which is useful. The annotations already declare readOnlyHint and idempotentHint, so the description does not need to repeat safety. No contradictions.
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, with three sentences each providing value: the main purpose and two conditional outcomes. No redundant or filler content. It is front-loaded with the main purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with no parameters and no output schema, the description covers the main behavior and both possible outcomes. It explains the authenticated flag and the URLs returned. Some details like the structure of pending[] are not explained, but overall it is sufficiently complete for an agent to understand what to expect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has no parameters, so the description cannot add parameter semantics. The baseline for zero params is 4, and the description is not penalized for omitting parameter details.
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, using the specific verb 'returns' and resource 'connection status'. The mention of 'authenticated:true' and 'connect_url' clarifies the output states. It distinguishes from the sibling 'authenticate' by focusing on status/URLs rather than performing authentication, though not explicitly.
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 for checking connection status, particularly when credentials are missing or after setup. It describes conditional behavior but does not explicitly say when to use this over alternatives like 'authenticate'. There is no mention of when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
contas_sabesp_download_conta_consultarCRead-onlyIdempotentInspect
SABESP: Download de Conta, 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 |
|---|---|---|---|
| cnpj | No | ||
| ano_mes | No | ||
| login_cpf | Yes | ||
| login_senha | Yes | ||
| fornecimento | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description states it uses official sources, is hosted by the platform, and emphasizes data privacy and LGPD compliance. It also notes that no platform credentials are required. However, it does not describe the exact behavior of the download (e.g., whether it returns a file, what format) or any potential side effects beyond payment.
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 somewhat verbose and repetitive, with multiple sentences that could be condensed. It repeats the idea of official source and data privacy, making it less concise than necessary.
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 lacks essential details such as the meaning of parameters, expected output, and how the tool fits into the overall workflow. It does not mention the return format or any constraints, leaving the agent with insufficient information to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description provides no information about the parameters (cnpj, ano_mes, login_cpf, login_senha, fornecimento) or how they should be used. Since the schema has no descriptions, the agent has to guess what each field means.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is for downloading an account from SABESP via an official source, which is a specific action. However, it could be more precise about the exact type of account (e.g., bill, statement) but overall it conveys the primary function.
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 provide guidance on when to use this tool compared to other tools. It mentions that it requires login credentials and payment, but does not explain the scenario for using this tool over alternatives like 'authenticate' or 'connect'.
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 the annotations: invoke works even when an MCP is not installed, runs one-off without bloating the toolkit, and requires owner/admin for writes. It also discloses credential-link and payment-link behavior, installation flags, and prompt-link visibility. The annotations (readOnlyHint=false, openWorldHint=true) are consistent with this description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense and front-loaded with the core flow, then covers write actions, prompt library, and permission context. Though it is a long single paragraph, most sentences add necessary information for a large multi-action tool. Formatting into sections would improve scannability, but the content is not wasteful.
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 high complexity, 23 optional parameters, and no output schema, the description covers the main workflow, auth/permission requirements, billing edge cases, and the prompt-library subdomain. It does not describe return shapes or enumerate every action (e.g., resume is not mentioned), but it provides enough context for an agent to operate effectively.
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 carries a heavy burden and largely delivers: it explains action=search, describe returning tool_id + params + pricing + auth, invoke running a tool, install vs invoke semantics, and prompt-related actions. However, several parameters remain under-explained, such as immediate, tier_slug, conversation, prompt_targets, cancel_reason, and the JSON string formats for arguments/prompt_vars.
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 and catalog/execution layer, distinguishing it from sibling tools like authenticate, connect, and report_bug. It provides concrete capabilities (search, describe, invoke, install, prompts) and explicitly frames the core flow from discovering MCPs to running them.
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 strong when-to-use guidance: use invoke for one-off runs, install only to make an MCP permanent, list_tools for currently callable tools, request_mcp when nothing fits, and report_bug for feedback. It also explains conditional flows (connect link for credentials, checkout/top-up for paid tools) and 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 communicate idempotency, non-destructiveness, and non-read-only behavior. The description adds the purpose of the conversation parameter ('for reproduction') but does not disclose side effects, response behavior, or prerequisites. It is consistent with annotations and provides a moderate amount of extra context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, compact sentence that front-loads the tool's purpose before giving the key usage instruction. There is no filler, redundancy, or schema 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 simple tool with three plain parameters and no output schema, the description is mostly sufficient: it identifies the purpose, the key required input, and why the conversation data matters. Minor gaps are the unexplained context parameter and the precise serialization of the conversation value.
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, the description must compensate, and it partially does: it explains the conversation parameter's role for reproduction. The required message parameter is reasonably implied by 'Report a bug...', but the context parameter is never explained, and saying 'conversation array' is slightly ambiguous given the schema defines it as a string (default '[]').
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 opens with the specific verb 'Report' and names concrete resource types: a bug, missing feature, or feedback. It also adds the reproduction detail about including the conversation array, which makes the tool's scope clear and distinct from unrelated siblings like authenticate or connect.
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 reporting a bug, missing feature, or feedback—and gives a concrete instruction to include recent messages for reproduction. However, it does not provide explicit when-not-to-use guidance or name alternatives, leaving usage largely implied.
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?
The description is consistent with the annotations (readOnly, idempotent, non-destructive). The verb 'Show' correctly indicates a read-only operation, and no contradictions exist. Annotations already cover these aspects, so the description adds minimal but accurate context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that conveys the essential purpose without unnecessary detail. It is well-structured and directly to the point.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is complete for its simplicity: it specifies what is shown (MCP platform and adapter versions) and implies no return format is needed. With no output schema and no parameters, the description fully covers the tool's function.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has no parameters, and the schema coverage is trivially 100%. According to the rubric, zero parameters warrants a baseline of 4. The description adds no extra parameter information, which is appropriate since none exist.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: showing the current MCP platform and adapter versions. It uses a specific verb ('Show') and identifies the resource (versions), distinguishing it from sibling tools like authenticate or connect.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage (when you need version information) but does not explicitly contrast with alternatives. Since it's a simple query tool with no side effects, the context is sufficient, though it could explicitly mention 'use this when checking version compatibility or environment details.'
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
toolkit_infoARead-onlyIdempotentInspect
Returns the current toolkit state: installed MCPs, their connection status, the accounts connected to each one, and how many catalog tools each exposes.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds value by specifying exactly what information is returned (installed MCPs, connection status, accounts, catalog tools), which goes beyond the annotations and clarifies the tool's 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, well-structured sentence that front-loads the main purpose ('Returns the current toolkit state') followed by concise enumeration of the specific data it provides. Every phrase adds information and there is no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, read-only inspection tool with no output schema, the description fully conveys what the tool does and what it returns. It includes all necessary details to understand the tool's behavior without requiring additional context.
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 according to the rule the baseline is 4. There is nothing to describe, and the schema already reflects the absence of parameters with an empty properties object.
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 specific verb 'returns' and names the exact resource ('current toolkit state'), then enumerates the components: installed MCPs, connection status, accounts, and catalog tool counts. This clearly distinguishes it from sibling tools like authenticate or connect, which are action-oriented.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use guidance is provided, but the description's nature as a state-inspection tool makes the use case obvious. It does not mention alternatives or exclusions, so it lacks the explicit guidance needed for a 5, yet the purpose alone conveys the appropriate context for a 3.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
No tool schema history has been recorded yet.
Frequently Asked Questions
Claiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as
io.github.alice/server, link the matching GitHub user, then choose Claim with GitHub. An organization namespace such asio.github.acme/serveralso needs that organization to have installed the Glama AI GitHub App and approved its permissions, because GitHub discloses organization membership only to apps it has installed. Use HTTP or DNS when it has not.HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at
/.well-known/glama.jsonon the same origin as the connector, then choose Check HTTP challenge.DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
Discussions
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Glama MCP Gateway
Add one secure layer between your agents and this server.
TDQS
The tools have distinct purposes: authentication, connection status, a specific SABESP consult, marketplace discovery, bug reporting, version display, and toolkit info. However, 'connect' and 'toolkit_info' both report connection status, causing minor overlap.
Naming is inconsistent: generic verbs like 'authenticate', 'connect', 'report_bug' mix with the verbose 'contas_sabesp_download_conta_consultar' and noun-based names like 'marketplace' and 'toolkit_info'. There is no uniform verb-noun pattern.
Seven tools is within the typical 3–15 range. However, the server's stated purpose (SABESP download) is served by only one tool, while the rest are platform utilities, making the set feel slightly over-scoped for the promised domain.
For the SABESP query, only a single consult operation exists, lacking other likely actions (e.g., list accounts, download history). The marketplace and toolkit tools provide extensibility, but within the server's own domain, coverage is minimal.