Prefeitura RS Três Coroas: Clearance Certificate (Debts), official-source lookup. Platform-hosted, p
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Average 4.2/5 across 7 of 7 tools scored.
The single domain tool is clear, but the platform tools blur together: marketplace also handles auth/connect-style flows and includes a report_bug action that duplicates the standalone report_bug, while toolkit_info overlaps with marketplace's list_tools. An agent could easily pick the wrong meta-tool for connection/status/tool-discovery tasks.
Names mix bare verbs (authenticate, connect, report_bug), nouns (marketplace, toolkit_info), and a very long domain-specific snake_case name (pref_rs_tres_coroas_cnd_consultar). There is no consistent verb_noun or domain-prefix convention across the set.
Seven tools is not excessive by raw count, but six are generic platform/meta tools bolted onto a one-tool municipal CND service. For a server named after a specific prefeitura certificate, the set feels over-scoped and unfocused.
The one domain tool, pref_rs_tres_coroas_cnd_consultar, plausibly covers the entire named purpose: querying the official negative-debt certificate from the Prefeitura. There are no domain CRUD requirements, so only minor extras such as explicit certificate-status or PDF-download helpers could be considered missing.
authenticateAMCP.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 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses persistence behavior (permanent vs session-only), the mechanism of obtaining a token via browser, and the impact on connection lifetime. This goes beyond the idempotent and destructive hints, adding valuable context about side effects.
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 yet comprehensive, packing multiple usage scenarios into two sentences without redundancy. All information is necessary for correct usage.
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 provides complete operational context: how to authenticate, when to use each method, and what the tool does (returns a link or accepts a token). No output schema exists, but the return behavior is implied sufficiently.
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 only parameter 'token' is explained as the JWT to paste for session login, and the optional nature is clarified by saying 'with no args to get the link'. This fully covers parameter meaning and optionality.
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: authentication for MCP.AI in IDE agents. It explains the two methods (browser login with token paste, or no args to get link) and distinguishes it from sibling tools like connect and 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?
Explicitly explains when to use each mode: add token to config for permanent connection, or pass token for session-only login, and calling with no args to get the login link. This provides clear guidance on invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
connectAReturns 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 | |||
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 value by explaining conditional return states (authenticated:true vs connect_url) and per-install URLs, which goes beyond the annotations without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose, and efficiently conveys key behavioral details without redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only tool with no parameters, the description adequately explains the main return states and URL outputs. It is reasonably complete given the low complexity, though it could mention partial connectivity scenarios, but that's not critical.
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 correctly does not address parameter usage. Per the rubric, baseline for 0 params is 4, and the schema is fully self-explanatory for an empty property set.
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 conditional behavior based on provider connection state. It's specific and distinguishes from siblings like authenticate and show_version, though it doesn't explicitly name alternatives.
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 no explicit guidance on when to use this tool versus alternatives. It implies a connection-checking purpose but does not state scenarios like 'use this before authentication' or contrast with sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
marketplaceAInspectThe 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 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds substantial behavior beyond annotations: 'invoke works even when the MCP is NOT installed — it runs the tool pontualmente,' invoke returns connect or checkout links, install makes MCPs permanent, and writes 'require workspace owner/admin.' It also discloses prompt-link sharing behavior. The annotations include readOnlyHint=false and destructiveHint=false, and the description's statements are consistent with them; no contradiction exists.
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 every clause carries meaningful information, but it is a single long paragraph with no bullet separations or per-action breakdown. The 'KEY:' marker and 'Core flow:' phrasing help structure it mentally. Given the large action enum and the absence of schema descriptions, the length is justified, but it would be clearer with explicit headers or bullets.
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 14-action tool with no output schema, the description is unusually complete: it covers the search/describe/invoke lifecycle, installation trade-offs, auth and billing edge cases, permissions, prompt-library usage, and troubleshooting via report_bug/request_mcp. It does not explain what invoke or search return, and some actions/parameters like resume, immediate, and conversation remain undocumented, so it is strong but not fully 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?
Schema description coverage is 0%, so the description carries the burden, and it compensates well by naming many parameters through prose: action, mcp_id, tool_id, arguments, prompt_body, prompt_slug, prompt_vars, prompt_targets, prompt_category, prompt_description, tier_slug, cancel_reason, request_name/details, and report_bug-related input. However, some parameters such as limit, query, immediate, conversation, and resume are not explicitly explained, leaving gaps for a 23-parameter tool.
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 a clear statement: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It identifies the resource (marketplace), its main purpose (discover, describe, and invoke MCPs), and also covers the prompt library. It is specific, but the tool is deliberately broad with fourteen distinct actions, so it lacks the crisp single-verb focus of simpler tools; it still distinguishes itself from sibling tools by framing itself as the catalog/execution layer.
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, including the core flow 'action=search → describe → invoke', and directly contrasts alternatives: 'prefer invoke for a single/occasional use' versus 'use install only to make an MCP PERMANENT.' It also states when invoke is preferred even if the MCP is not installed, covers billing actions, and explains the prompt-library branch. This exceeds basic guidance and addresses selection among multiple actions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pref_rs_tres_coroas_cnd_consultarAPrefeitura RS Três Coroas: Certidão Negativa de Débitos, consulta em fonte oficial. Hospedado pela plataforma, sem credenciais da plataforma, pague por consulta com crédito pré-pago. Consulta informação de fontes e órgãos oficiais brasileiros (a mesma disponível ao cidadão), não é dado sigiloso. O cliente é o controlador dos dados e responde pela finalidade legítima (LGPD).
| Name | Required | Description | Default |
|---|---|---|---|
| cpf | No | ||
| cnpj | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
As anotações já declaram readOnlyHint, destrutivo falso e idempotente, e a descrição acrescenta detalhes úteis: necessidade de crédito pré-pago, ausência de credenciais da plataforma, natureza não sigilosa dos dados e responsabilidade LGPD. Nenhuma contradição; agrega contextos importantes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A descrição é um parágrafo único e direto, começando pelo propósito principal e depois adicionando informações sobre hospedagem, pagamento e LGPD. Cada sentença agrega valor, sem excesso de detalhes irrelevantes.
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?
Para uma operação simples de consulta, a descrição cobre propósito, fonte oficial, condições de acesso e responsabilidade legal. Não detalha o formato de retorno, mas a ausência de schema de saída torna isso menos crítico. Faltam apenas orientações explícitas sobre os parâmetros.
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?
A cobertura da descrição do schema é 0%, e a descrição não menciona os parâmetros 'cpf' e 'cnpj'. O contexto implícito de CND sugere a necessidade de um dos identificadores, mas sem explicação explícita de formato ou obrigatoriedade, a descrição não compensa a falta de informações.
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?
A descrição afirma claramente que a ferramenta realiza consulta de Certidão Negativa de Débitos na Prefeitura de Três Coroas, usando verbo 'consulta' e recurso específico. Diferencia-se dos irmãos (autenticação, conexão, marketplace, etc.) por ser uma consulta tributária específica.
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?
A descrição indica implicitamente quando usar (para consultar CND) e menciona condições de pagamento pré-pago, mas não discrimina quando não usar, nem apresenta alternativas. Não há orientação sobre pré-requisitos como CPF/CNPJ, apenas contexto geral.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
report_bugAReport 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 | [] |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description hints that conversation data is used for reproduction but does not explicitly state side effects or outcomes. Annotations cover some behavioral traits, but description could add more.
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, one sentence, and front-loaded with the main purpose before mentioning the essential parameter instruction.
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 simplicity and annotations, the description is fairly complete, but could be more explicit about what happens after reporting, e.g., whether a ticket is created or data is sent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description explains the purpose of the conversation parameter by instructing to include it for reproduction, adding meaning beyond the schema.
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: reporting bugs, missing features, or sending feedback. It distinguishes 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?
Provides a specific guideline to include the conversation array for reproduction, but does not explicitly compare with alternatives. However, since sibling tools are distinct, it's implied when to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
show_versionAShow the current MCP platform and adapter versions.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, covering the safety profile. The description adds no additional behavioral context beyond restating the action itself, such as whether authentication is required or what exact version strings are returned. It is consistent with annotations, but does not enrich them.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no filler or redundant wording. It front-loads the verb and resource, making it immediately scannable and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, read-only version-checking tool with strong annotations, the description fully covers the purpose. There is no output schema or complex behavior to disclose, so the description is complete as-is.
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 the schema is trivially covered at 100%. With no parameters to describe, the baseline score is 4, and the description appropriately avoids mentioning any parameters.
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 clearly identifies the resource ('MCP platform and adapter versions'), making the tool's purpose unmistakable. It also distinguishes itself from sibling tools like authenticate and marketplace, which serve entirely different functions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
While there is no explicit when-to-use or alternative mention, the context is clear: this is the go-to tool for checking versions. Given the trivial nature of the tool and absence of similar siblings, explicit exclusionary guidance is unnecessary, but the description could have stated 'Use this when you need version info' for maximum clarity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
toolkit_infoAReturns 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 | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already indicates no side effects. The description does not add context about rate limits, authentication requirements, or potential impacts beyond stating it returns the current state. It neither contradicts nor significantly enhances the annotation.
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 efficiently conveys the tool's purpose without unnecessary detail. It is well-structured and easy to understand.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only status tool, the description is complete in summarizing what is returned. It does not outline the exact output format, but given the absence of an output schema, this is acceptable. The information provided is sufficient for basic usage.
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 schema coverage is effectively 100%. The description does not need to explain parameters, and no additional semantic information is provided. Baseline score 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 clearly states the tool's function: returning the current toolkit state, and specifies the included details (installed MCPs, connection status, accounts, catalog tool counts). It distinguishes this from sibling tools like authenticate or connect, which have different purposes.
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 the tool does but does not explicitly state when to use it over alternatives. While it is implicitly a read-only information tool, there is no guidance on when it would be preferable to other tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
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