Prefeitura BA Salvador: Clearance Certificate, official-source lookup. Platform-hosted, pay per quer
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 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description implies side effects (e.g., permanent config changes) and mentions token handling, but does not clearly state whether the tool modifies state or just returns a link. Annotations indicate non-read-only, but behavior is not fully disclosed.
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 run-on with mixed instructions and alternatives, making it difficult to parse. It lacks clear structure and could be more concise and organized.
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?
It explains usage and parameter behavior, but does not describe the return value or error scenarios. The description is adequate for a simple authentication tool but leaves some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Even though the schema has no description, the tool description explains the token parameter as a JWT and clarifies it is optional (no args returns a link). This adds meaningful context 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 indicates the tool is for authentication, but the phrasing is convoluted, mixing instructions and alternatives. It distinguishes from siblings by its focus on login/token.
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 explicit usage options (pass a token or call with no args to get a link), and explains permanent vs. session-only authentication. However, it does not explicitly state when to choose this over other tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish read-only, idempotent, non-destructive behavior. The description adds meaningful response context: authenticated:true with empty pending[] when connected, and connect_url plus per-install URLs when credentials are missing. 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?
Two front-loaded sentences deliver the core behavior and the two relevant conditional outcomes without waste. Every sentence earns its place.
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 a zero-parameter read-only status check with no output schema, and the description adequately explains the return conditions and URLs. This is sufficient for an agent to invoke and interpret the result.
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 covers 100% of properties (none exist), so the baseline 4 applies. The description adds no parameter semantics because none are 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 uses a specific verb+resource ('Returns connection status and URLs') and details conditional results, making its purpose unambiguous. It clearly differentiates from siblings like authenticate by indicating this is a status read, not an auth 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?
It gives clear context: use this tool to check connection state and obtain connect URLs when credentials are missing. It does not explicitly name alternatives or exclusions, but the conditional behavior implies appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite annotations indicating readOnlyHint:false and openWorldHint:true, the description adds substantial behavioral detail: it explains that invoke runs tools on a one-off basis without adding to the toolkit, that it returns connect links for missing credentials and checkout/top-up links for insufficient wallet, and that writes require admin. It also notes that search/describe flag installation state. This goes well beyond annotations and clarifies 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 long (over 300 words) and dense, covering numerous actions and edge cases. It is structurally logical (starts with purpose, then core flow, then exceptions, then prompt library) and every sentence carries information, but it is not concise. It is front-loaded with the key purpose and flow, but could be more compact. Given the tool's complexity, the length is somewhat justified but not ideal.
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 multi-action tool with 23 parameters and no output schema, the description is remarkably complete. It covers the entire workflow, exception handling (credentials, wallet), permissions, the prompt library, and even distinguishes installed state flags. It explains the billing actions and report paths. It provides sufficient context for an agent to decide which action to use and what to expect, leaving no major gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With zero schema descriptions, the description must compensate for parameter meaning. It explains the core flow and mentions key parameters (action, mcp_id, tool_id, arguments, message) and outlines prompt library actions (search_prompts, get_prompt, publish_prompt). However, it does not explicitly cover all 23 parameters (e.g., limit, query, immediate, tier_slug, prompt_vars) leaving some vagueness, though the context implies their usage. It adds meaning for the primary parameters but not exhaustively.
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 as the official mcp.ai marketplace, covering both MCP discovery and execution plus a prompt library. It distinguishes itself from siblings like 'authenticate' and 'connect' by explicitly listing its core flow (search → describe → invoke) and its unique feature of running MCPs without installation. The verb is specific ('is', 'covers', 'runs') and the resource is well defined.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use guidance: 'prefer invoke for a single/occasional use', 'use install only to make an MCP PERMANENT', and explains that invoke works even when MCP is not installed. It also mentions prerequisites like permissions ('require workspace owner/admin') and gives exact scenarios for search/describe vs install. Alternatives are named (like 'request_mcp asks us to build a NEW MCP when nothing fits').
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Prefeitura BA Salvador: Nada Consta, 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 |
|---|---|---|---|
| renavam | Yes |
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 description need not repeat those. It adds meaningful context beyond annotations: payment via prepaid credit, no platform credentials required, and LGPD data-controller responsibilities. This extra information enriches the agent's understanding of the tool's operational characteristics.
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, consisting of three sentences that cover the core purpose, payment method, and legal obligations. It is front-loaded with the primary action and avoids unnecessary verbosity, though it packs a lot of information into a few lines.
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?
While the description explains the purpose, payment, and legal aspect, it does not describe the expected output or clarify the 'renavam' parameter. Given there is no output schema, the description should have at least hinted at what the tool returns or the input format, leaving a gap for correct invocation.
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 'renavam' has zero schema description coverage (the schema provides no description field), and the description does not explain its meaning, format, or domain. The agent is left to guess that 'renavam' refers to a Brazilian vehicle registration number, which may not be obvious. The description fails to compensate for the low schema coverage.
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 'Prefeitura BA Salvador: Nada Consta, consulta em fonte oficial' (Salvador BA City Hall: No record, query in official source), clearly defining a specific verb-resource pair and distinguishing it from the generic sibling tools (authenticate, marketplace, etc.).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context that this is a paid query using prepaid credit and that it is hosted by the platform, implicitly indicating its purpose. However, it does not explicitly state when to use it over other tools or include any exclusions, but given the unrelated siblings, the usage context is sufficiently clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 | [] |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover safety (readOnly=false, destructive=false, idempotent=true). The description does not contradict these and adds a hint about including conversation for reproduction, but it does not disclose potential side effects or outcomes (e.g., confirmation, report creation). Thus, transparency is moderate.
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, succinct sentence that packs all essential information without any unnecessary words or redundancy. It is well structured 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?
Given the tool's simplicity, the description is adequate but not complete. It does not specify expected behavior after submission (e.g., confirmation, error handling) or the role of the 'context' parameter. Since there is no output schema, this might be acceptable, but more detail would improve completeness.
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 has 0% description coverage, so the description must compensate. It explains 'conversation' as an array for reproduction, but 'context' and 'message' are not described. This leaves ambiguity about the exact content and purpose of the message and context 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 the tool's purpose: to report a bug, missing feature, or send feedback. It also specifically instructs to include the conversation array for reproduction, which is distinct from sibling tools like authenticate or 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?
It explicitly tells when to use the tool (when reporting a bug/feature/feedback) and provides an important usage instruction (include conversation array for reproduction). This is sufficient guidance for an agent to decide when to invoke it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Show 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, idempotentHint=true, and destructiveHint=false, providing the safety profile. The description adds no extra behavioral context (e.g., output format, authentication needs). Since annotations cover the main traits, a 3 is the baseline for not adding beyond 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, concise sentence immediately stating the purpose. No filler or redundant phrasing; every word earns its place.
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, high annotation coverage), the description fully conveys the function. It leaves no ambiguity about what the tool does.
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 there is nothing to describe. Per rubric, 0 params yields a baseline of 4. The description correctly omits parameter details as 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 action ('Show') and the specific resources ('current MCP platform and adapter versions'). It is unambiguous and distinguishes from sibling tools like authenticate or report_bug, which serve 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 implies usage when version information is needed, which is clear from context. However, it does not explicitly mention when not to use it or name alternatives, but given the uniqueness of the tool among siblings, this is adequate. A 4 is appropriate as it has clear context without explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 | |||
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 description doesn't need to restate that. It adds value by detailing the exact nature of the returned information (installed MCPs, statuses, accounts, tool counts), which goes beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the purpose ('Returns the current toolkit state') and then lists what is included. No wasted words or redundancy.
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 no-parameter, read-only info tool, the description is complete: it enumerates exactly what will be returned (installed MCPs, connection status, accounts, and catalog tool counts). No output schema is needed, as the description sufficiently covers the return contents.
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 baseline score is 4. The description correctly implies that no input is needed, and there are no parameters to explain or augment.
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 components (installed MCPs, connection status, connected accounts, catalog tool counts). This distinguishes it from sibling tools like authenticate, connect, or show_version, 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 context is clear: this tool is for fetching overall toolkit status, while siblings handle authentication, connection, marketplace, or version reporting. However, it doesn't explicitly state when not to use it or mention alternatives, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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.
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 as io.github.acme/server also 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.json on 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.
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Prefeitura BA Salvador: Clearance Certificate (Debts), official-source lookup. Platform-hosted, pay
SEFAZ BA: Clearance Certificate (Debts), official-source lookup. Platform-hosted, pay per query with
Prefeitura BA Ilheus: Clearance Certificate (Debts), official-source lookup. Platform-hosted, pay pe
Prefeitura RN Natal: Clearance Certificate (Debts), official-source lookup. Platform-hosted, pay per
Add one secure layer between your agents and this server.
Tools are mostly distinct, but authenticate and connect both deal with authentication/connection, which could cause slight confusion. The rest are clearly differentiated.
Naming is inconsistent: single-word verbs (authenticate, connect), nouns (marketplace), a long descriptive name (pref_ba_salvador_nada_consta_consultar), and compound verbs/nouns (report_bug, show_version, toolkit_info) break any clear pattern.
Seven tools is a reasonable size for a platform server that covers authentication, marketplace search, feedback, and info. Not too few or too many.
The set covers core actions but lacks explicit install/uninstall or management operations for MCPs, relying on marketplace to implicitly handle them. This leaves a notable gap for a full lifecycle.