Prefeitura SP São Paulo: AIT, official-source lookup. Platform-hosted, pay per query with prepaid cr
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Average 4.2/5 across 7 of 7 tools scored. Lowest: 3.3/5.
Most tools have distinct jobs, but `connect` and `toolkit_info` both expose connection/account status, and `marketplace` is a broad catch-all whose `invoke` flow can also run the AIT consultation tool. The descriptions are detailed enough to reduce risk, but some boundary overlap remains.
Names are readable and consistently lowercase, but they do not follow one predictable pattern: bare verbs (`authenticate`, `connect`), nouns (`marketplace`, `toolkit_info`), verb-noun compounds (`report_bug`, `show_version`), and a long domain-prefixed name (`pref_sp_sao_paulo_ait_consultar`) are mixed together.
Seven tools is not a large count, but only one tool is actually domain-specific for the AIT/public-data feature; the other six are platform, authentication, and feedback tools. From a platform-wrapper perspective this is reasonable, but from an AIT server perspective the domain surface feels thin.
The core use case is a read-only consultation of official AIT data, so missing create/update/delete tools are not a serious gap in this context. The marketplace tool also lets an agent discover additional MCPs if needed, though the native domain surface is only a single query tool.
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?
With annotations declaring idempotentHint=true and destructiveHint=false, the description adds behavioral context: explains how the token is used, distinguishes permanent vs session login, and indicates that calling with no args yields a login link. This goes beyond 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?
Three sentences, front-loaded with the core action, and no redundant information. The structure is efficient, though slightly dense in the middle.
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 the authentication flow, the meaning of the token, and the two modes of use, making it functionally 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 schema has 0% coverage for the token parameter, but the description explains that token is a JWT pasted by the user, and that it is optional (no args gets the link). This fully compensates for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: authenticate via browser login, obtain an access token, and optionally accept that token as a JWT. It distinguishes itself from siblings by focusing on the authentication flow and token 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 guidance: recommends adding an Authorization header to the server config for a permanent connection, or passing a token for session-only login, or calling with no args to get the link. This tells the agent when and how to use the tool, though it doesn't explicitly name alternative tools.
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 mark this as read-only, idempotent, and non-destructive. The description adds valuable behavioral detail about return values under different conditions (all connected vs. missing credentials), but it does not cover partial connection states or error scenarios, leaving a small transparency gap.
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, composed of two sentences that immediately front-load the primary purpose. Every sentence adds value 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?
For this simple, zero-parameter tool, the description covers the main behaviors: authenticated state, pending array, and connect URLs. However, it does not explain what 'pending' contains or how partial connections are handled, which would make it fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the schema provides no parameter information. The description correctly focuses on the output behavior, which is the only meaningful semantic content. Baseline 4 is appropriate for no-parameter tools.
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 with a specific verb ('Returns') and resource ('connection status and URLs'). It distinguishes itself from sibling tools like 'authenticate' by focusing on status retrieval rather than initiating an auth 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 clear context for when to use the tool: to check connection status and get URLs, especially when credentials are missing. It does not explicitly mention alternatives or when not to use it, but the behavior is well scoped.
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?
Annotations are limited (readOnlyHint=false, openWorldHint=true), but the description adds substantial behavioral context: invoke runs one-off without installing, returns connect/checkout links for auth/payments, and that writes require owner/admin. It also explains the prompt library distinct from MCPs. No contradiction with 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 extremely long (two dense paragraphs) and covers a wide array of actions. It is well-structured with action breakdown and flow, but could be more concise by breaking into bullet points. Every sentence adds value, but the density makes it harder to parse quickly.
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 (14 actions, 23 params, no output schema), the description is remarkably complete. It covers the full lifecycle, permission requirements, auth/wallet handling, fallback behavior, and the separate prompt library. It leaves little ambiguity for an agent.
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 coverage is 0%, so the description compensates by explaining action semantics (e.g., 'action=search discovers MCPs', 'describe returns a full profile'). It implicitly maps key params (mcp_id, tool_id, arguments, prompt fields) to actions, but does not systematically document all 23 parameters. Still provides meaningful usage context beyond the raw 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 explicitly states it is the official mcp.ai marketplace catalog and runtime, covering capability requests ('find an MCP that does X'). It clearly outlines the core flow (search → describe → invoke) and delineates each action's role, distinguishing itself from siblings by its comprehensive scope.
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 gives explicit when-to-use guidance: 'prefer invoke for a single/occasional use' versus 'Use install only to make an MCP PERMANENT', and explains when invoke returns connect/checkout links and to retry. It also notes write actions require owner/admin. This is detailed and actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pref_sp_sao_paulo_ait_consultarAPrefeitura SP São Paulo: AIT, consulta em fonte oficial. Hospedado pela plataforma, sem credenciais da plataforma, pague por consulta com crédito pré-pago. Consulta informação de fontes e órgãos oficiais brasileiros (a mesma disponível ao cidadão), não é dado sigiloso. O cliente é o controlador dos dados e responde pela finalidade legítima (LGPD).
| Name | Required | Description | Default |
|---|---|---|---|
| placa | Yes | ||
| renavam | Yes | ||
| login_cpf | No | ||
| login_cnpj | No | ||
| login_senha | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds valuable context beyond annotations: no platform credentials are needed, prepaid credits are consumed per query, the data is official and non-confidential, and the client takes LGPD data-controller responsibility. This is rich behavioral and legal transparency.
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 composed of four sentences, each carrying distinct useful information: the official source, hosting/payment model, data accessibility, and LGPD responsibility. It is not especially concise but every sentence adds value and the opening immediately identifies the tool's 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 paid data-consultation tool with no output schema and five parameters, the description covers the key commercial, legal, and source-legitimacy aspects. It does not explain the required parameters or expected response shape, but it provides enough context for an agent to understand the tool's nature and constraints.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage and the tool description does not explain any of the five parameters. Parameter names like 'placa', 'renavam', and 'login_senha' give some inferable meaning, but the description itself adds no explicit semantics, formats, or relationships between the 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 clearly states this is a consultation ('consulta') of AIT data from the official Prefeitura SP São Paulo source. It identifies both the action and the resource, and the siblings are unrelated generic tools, so there is no ambiguity about what this tool does.
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 clear operational context: the tool is hosted by the platform, does not use platform credentials, is paid per query with prepaid credit, and is intended for accessing the same official citizen-available information. It does not explicitly name alternatives or exclusion cases, but the context is specific enough to guide appropriate use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
report_bugBReport 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?
Annotations indicate non-readOnly (false), non-destructive, and idempotent, but the description adds the behavioral note that it requires reproduction details (conversation array). This adds value beyond annotations, which are relatively generic. However, it does not detail what happens after reporting (e.g., response, tracking) or any side effects. Given annotations cover the basic safety profile, a score of 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 two sentences: one stating the purpose and one instructing on the conversation array. It is front-loaded with the main purpose and contains no fluff. Each sentence serves a distinct function (purpose and key 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?
The tool is relatively simple with 3 params and no output schema. The description conveys the main purpose and gives one essential guidance (include conversation for reproduction). However, it lacks details on what the 'message' parameter should contain, what 'context' is for, and what the user can expect after submission (e.g., no confirmation). Given the low complexity, a score of 3 is fair - it covers the core but misses some practical details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. However, the description only mentions the 'conversation' parameter implicitly ('Include the conversation array') and doesn't explain the 'message' (required) or 'context' parameters. The meaning of 'message' is implied but not explicit, and 'context' is not described at all. This is insufficient given the 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: report a bug, missing feature, or send feedback. It is specific about the action and resource (reporting issues), and it differs from sibling tools like 'authenticate' or 'show_version' by being user feedback-oriented. However, it doesn't explicitly distinguish itself from all siblings, such as 'toolkit_info' which might also handle feedback, but the core purpose is clear.
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 a hint on when to use the tool (to report a bug, missing feature, or feedback) and implicitly says to include the conversation array for reproduction. However, it does not explicitly state when not to use it or mention alternatives. The context is clear but lacks exclusions.
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 this as a safe, read-only, idempotent operation (readOnlyHint: true, idempotentHint: true, destructiveHint: false). The description adds the detail that it shows 'current' versions, implying a live system query, but provides no additional behavioral context beyond that. The description does not contradict the annotations, and the bar is lower with annotations present, but it still doesn't significantly extend 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 entire description is one concise sentence that is immediately understandable and front-loaded with the action ('Show'). There is zero wasted wording or redundant information, making it a model of conciseness.
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—no parameters, no output schema, and clear annotations—the description is complete. It fully covers what an agent needs to know to use the tool, and no additional details about return values or behavior are necessary for this low-complexity 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 the parameter semantics are trivially satisfied. The description confirms that no input is needed to get the version info, which is consistent with the empty schema. As per the rubric, this gives a baseline 4, since there are no parameter details to elaborate on.
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 'show' and identifies the resource as 'current MCP platform and adapter versions,' clearly stating exactly what the tool does. It distinguishes itself from siblings by specifying the exact type of version information returned, making it 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 implies usage by stating what the tool does but provides no explicit guidance on when to use this tool over alternatives like 'toolkit_info' or 'connect'. There is no mention of exclusions or alternative tools, so the usage context is only implied, not explicitly stated.
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?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds value by detailing the exact content of the return (installed MCPs, connection status, accounts, catalog tool counts), which informs the agent of what to expect without needing an output schema.
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 that starts with the action ('Returns') and clearly enumerates the data components. No unnecessary words or ambiguity.
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?
With no output schema and no params, the description carries the full burden of explaining the response. It lists all major categories of returned information, making it sufficient for an agent to decide when to call. It could slightly improve by noting that results reflect current state, but it's complete for typical use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the description needs no parameter explanation. Baseline for 0 params is 4, and the description appropriately focuses on output rather than inputs.
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 explicitly states the tool returns the toolkit state with a specific list of components (installed MCPs, connection status, accounts, catalog tool counts). This verb+resource scope is clear and distinguishes it from siblings like 'authenticate' or 'connect' which imply 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 use for inspecting toolkit status, but does not explicitly state when to use it (e.g., before connecting) or exclude alternatives. While siblings are action-oriented, there's no direct 'use this instead of X' guidance.
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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