INPI: Processo de Registro de Marca (Completa)
Server Details
INPI: Court Case de Registro de Marca (Completa), official-source lookup. Platform-hosted, pay per q
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- mcp-dir/inpi_marcas_processo-mcp
- GitHub Stars
- 0
- Server Listing
- INPI: Processo de Registro de Marca (Completa)
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?
Annotations already indicate idempotency and non-destructiveness. The description adds valuable behavioral detail by explaining the token's persistence (non-expiring vs session-only) and the two distinct call modes, which is not captured in 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, dense sentence that packs a lot of actionable information. It is front-loaded with the purpose and effectively uses 'Best:' and 'Or' to structure options, though breaking into separate sentences would improve readability.
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 simple tool with one optional parameter and no output schema, the description covers all necessary aspects: authentication flow, token persistence, usage options, and initialization via config. It is complete for an agent to invoke 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?
With 0% schema description coverage, the description fully explains the optional 'token' parameter: how to supply it after the user pastes a JWT, and that omitting it will return an authentication link. This provides complete semantic meaning beyond the bare schema definition.
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 authenticates the user by logging into a browser and obtaining an access token. It distinguishes itself from sibling tools by focusing solely on the authentication flow, with explicit mention of the token acquisition and usage.
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 guidance on when and how to use the tool: it recommends adding the token to the server config for permanent access, or passing a token for session-only login, or calling with no args to get a link. This clarifies the preferred approach and alternatives clearly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
connectARead-onlyIdempotentInspect
Returns connection status and URLs. When all providers are connected, returns authenticated:true and empty pending[]. When credentials are missing, returns connect_url for the toolkit and per-install URLs.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only and idempotent behavior. The description adds value by detailing the response structure and conditional fields, which is beyond the annotation hints.
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, two sentences, with no unnecessary words. It is well-structured and directly addresses the tool's behavior.
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 no input parameters and an implicit output, the description covers the two primary outcomes (authenticated and missing credentials). It is complete enough for typical use cases, though it doesn't mention error handling.
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?
There are no parameters, so the baseline is 4. The description doesn't need to explain parameters and doesn't add anything about them.
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 connection status and URLs, with explicit conditional outcomes. This distinguishes it from sibling tools like 'authenticate' and 'toolkit_info'.
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 checking connection status, and the two scenarios (all connected vs. missing credentials) give clear context. It doesn't explicitly contrast with alternatives but the purpose is unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
inpi_marcas_processo_consultarARead-onlyIdempotentInspect
INPI: Processo de Registro de Marca (Completa), 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 |
|---|---|---|---|
| numero_processo | Yes |
TDQS
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 beyond this by disclosing the prepaid billing model, lack of platform credentials, official/public data source, non-confidential nature, and LGPD data-controller responsibility. It does not disclose rate limits or exact return format, preventing a perfect score.
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 front-loaded with the core purpose and remains relatively short. Each sentence adds some useful context, though there is mild redundancy around 'fonte oficial' and 'fontes e órgãos oficiais brasileiros', and the LGPD sentence is more legal boilerplate than tool behavior.
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 one-parameter read-only query tool, the description provides enough context for an agent to select and invoke it: it states the source, the data type, payment requirements, credential requirements, and legal context. However, with no output schema, it does not describe return payload or error behavior, which keeps it from being 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?
Schema coverage for the only parameter, 'numero_processo', is 0%, and the description must compensate but does not. It only implies that the parameter is an INPI trademark-registration process number, without specifying format, examples, or valid patterns. Some value is added through domain context, but the gap remains significant.
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 querying a trademark registration process at INPI, using a specific verb ('consulta') and a specific resource ('Processo de Registro de Marca'). It is clearly distinct from the generic sibling tools (authenticate, connect, marketplace, etc.) and explicitly mentions the official source.
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 operational context: it is hosted on the platform, requires no platform credentials, is paid per query with prepaid credits, and accesses official Brazilian public data. It does not explicitly state when to use versus alternatives, but there are no close sibling tools, so the context is sufficient.
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?
Annotations already mark readOnlyHint=false and openWorldHint=true, and the description adds substantial operational context: invoke works even when the MCP is not installed, returns connect/checkout links for auth or payment, and writes require workspace owner/admin. It does not contradict the annotations; uninstall/cancel are permission-gated mutations consistent with destructiveHint=false.
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 dense paragraph but front-loads the value proposition and uses a clear search→describe→invoke narrative, with the prompt library cleanly separated at the end. It is somewhat run-on with capitalized connectors, but every major sentence earns its place given the tool's breadth.
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?
Despite 23 parameters and no output schema, the description gives a strong mental model: discovery, profiling, one-off invocation, permanent installation, permissions, auth/payment fallbacks, and the separate prompt library. It does not spell out return payloads or every action's exact behavior, but it is substantially complete for such a complex tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must compensate, and it does by explaining the action enum semantics (search, describe, invoke, install, prompt actions) and the prompt_vars flow ('get_prompt returns full text with {{variables}} filled'). However, several parameters such as tier_slug, immediate, prompt_targets, and cancel_reason are left to schema defaults/enums without much narrative, so compensation is good but not exhaustive.
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 'official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them' and then enumerates concrete capability requests ('find an MCP that does X', 'consulta um CPF', 'is there a tool for Y'). This clearly marks it as a catalog-plus-execution dispatcher rather than a single-purpose utility, and it differentiates itself from siblings like authenticate/connect/report_bug.
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 lays out an explicit core flow: action=search discovers MCPs → describe returns profiles → invoke runs the chosen tool, and it gives direct preference rules such as 'prefer invoke for a single/occasional use' and 'Use install only to make an MCP PERMANENT'. It also clarifies that list_tools shows what is callable right now, giving the agent concrete when-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
report_bugBIdempotentInspect
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 declare idempotentHint=true and destructiveHint=false, which are helpful. The description adds that the conversation array should be included for reproduction, which is a behavioral expectation. However, it doesn't disclose what happens after reporting (e.g., no response, confirmation), or any potential side effects beyond idempotency. The description doesn't contradict annotations, so no contradiction flag.
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 one sentence, front-loaded with the action. It includes a functional note about the conversation parameter. It's concise, though it could be slightly more structured (e.g., listing parameters) but that's not 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 tool has 3 parameters, one required, and no output schema. The description is sparse. It doesn't explain the expected format of 'conversation' (string? maybe JSON) or what 'context' is for. It also doesn't mention any response or behavior after submission. Given the tool's complexity (simple form submission), it might be adequate, but for an AI agent, more detail on parameter semantics would help. The description covers the essentials but leaves out important details for successful 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?
Schema coverage is 0%, so the description must explain parameters. The description mentions 'conversation array' but doesn't explain the 'message' or 'context' fields. It tells users to include the conversation array but doesn't clarify the format or how 'context' is used. This is a gap since the schema provides no descriptions for 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 states the tool's purpose: 'Report a bug, missing feature, or send feedback.' It uses a specific verb (report/send) and resources (bug, feature, feedback). It doesn't explicitly distinguish from siblings, but the sibling list includes unrelated tools like authenticate and marketplace, so ambiguity is low.
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 tells users to include the conversation array for reproduction, which implies when to use it (when providing repro context). However, it doesn't explicitly state when not to use alternatives or contrast with any other feedback mechanism. The guidance is clear but limited.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
show_versionARead-onlyIdempotentInspect
Show the current MCP platform and adapter versions.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the agent knows this is a safe, idempotent read operation. The description adds specific detail: it shows 'MCP platform and adapter versions', which is beyond the annotations. This clarifies what kind of information is returned. It does not describe the exact output format, but since the tool is read-only and simple, this is acceptable. No contradictions. The description adds value by specifying the exact scope of the version information.
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 one sentence, concise, and to the point. It is front-loaded with the action verb 'Show'. It wastes no words. Could be slightly more informative, but it's effective. Given the simplicity of the tool, it is appropriately concise. Justification for 4: It's not overly verbose, but it doesn't include any additional context about output or usage. Yet, for a tool with zero params and a clear purpose, a single sentence is acceptable. It earns a 4.
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 (0 parameters, no output schema, read-only), the description is complete enough. It tells the agent what the tool does and what it returns (current versions). It doesn't specify the structure of the return value, but the agent can infer it's a list or object of version strings. The annotations cover safety, and the description covers the purpose. There's no missing parameter information. Compared to the calibration example of a filtered-list tool, this is similar in completeness. A 4 is warranted; it could explicitly mention that it returns version numbers for both the platform and adapters, but the description already says that. I rate it 4.
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 0 parameters, and schema description coverage is effectively 100% (no properties). There is no parameter semantics to worry about. The description doesn't mention parameters because there are none. For a zero-parameter tool, the baseline is 4 per the rubric. The description accurately implies that no arguments 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 clearly states what the tool does: 'Show the current MCP platform and adapter versions.' This is a specific verb (show) plus a specific resource (versions). It distinguishes itself from siblings like 'authenticate' or 'connect' since none of those imply version information. It could be slightly more explicit about what 'adapter versions' refers to, but the purpose is unambiguous. It does not explicitly mention that it is a read-only informational tool, but the annotations cover that. Since it doesn't explicitly differentiate from a hypothetical sibling that also shows versions (none exist here), it merits a 4 rather than a 5.
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 the context for use: checking current versions. It implies this is for informational purposes, probably before troubleshooting or verifying compatibility. However, it doesn't state when NOT to use it or mention alternatives. Sibling tools include 'toolkit_info' which might also provide version-related info, but the description doesn't clarify when to choose 'show_version' over 'toolkit_info'. Thus, it has a clear context but lacks explicit exclusions or alternative guidance, placing it at 3.
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. The description adds value by specifying exactly what snapshot is returned (installed MCPs, statuses, accounts, tool counts) without contradicting the annotations. It does not discuss edge cases like stale state or permission requirements, but these are less critical for a read-only info call.
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?
Single sentence with the main action front-loaded and a compact list of return categories. Every clause adds information; no filler or repetition of the tool name.
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 low-complexity, zero-parameter info tool with annotations covering safety, the description is fully adequate. It lists the main facets of the toolkit state, which substitutes for an output schema by telling the agent 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 zero parameters, so the schema cannot benefit from additional parameter descriptions. Per baseline for zero-parameter tools, a 4 is appropriate; the description correctly focuses on return content 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?
Description uses specific verb 'Returns' and names the resource 'current toolkit state', then enumerates concrete contents: installed MCPs, connection status, connected accounts, and catalog tool counts. This clearly distinguishes it from siblings like connect, authenticate, and show_version.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for inspecting current toolkit/connection state but provides no explicit when-to-use guidance or comparison against sibling tools such as connect or authenticate. It does not mention exclusions or prerequisites, leaving usage context implicit.
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 are mostly distinct: authenticate, connect, marketplace, report_bug, show_version, and toolkit_info each have clear roles, and the sole domain tool (inpi_marcas_processo_consultar) is unique. Minor overlap exists between connect and toolkit_info both reporting connection status, but they differ in scope and output.
All tool names use snake_case, but the pattern is inconsistent: some are verb-based (authenticate, connect, report_bug, show_version), while others are noun phrases (marketplace, toolkit_info, inpi_marcas_processo_consultar). The long domain-specific name also deviates from the short utility names.
The server is named for a specific INPI trademark process domain, yet has only one domain-specific tool and six platform utilities. This is disproportionate: the domain coverage is minimal, and the utility tools dominate, making the count inappropriate for the stated purpose.
Despite the server name suggesting a complete trademark registration process, only a single consultation tool exists. Missing list, status, filing, or other process-related operations, so the domain coverage is severely incomplete.