SINTEGRA: RN
Server Details
SINTEGRA: RN, official-source lookup. Platform-hosted, pay per query with prepaid credit.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- mcp-dir/sintegra_rn-mcp
- GitHub Stars
- 0
- Server Listing
- SINTEGRA: RN
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 mark idempotent and non-destructive. The description adds that no-arg calls return a link, token calls enable session-only login, and config-based header provides permanent access. It clarifies behavioral traits like token handling and session scope without contradicting 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 moderately sized and front-loaded with purpose. It uses structured formatting ('Best:' and 'Or') to organize permanent vs session-only options, and every sentence adds necessary information about the authentication flow.
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 auth tool with one optional parameter and no output schema, it explains both invocation modes and their outcomes (link vs session). It does not specify the exact return payload on success, but the provided details are sufficient for an agent to call the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema only has an optional 'token' with no description (0% coverage). The description compensates by explaining the token as '<jwt>' to paste for session login, and also explains the no-args alternative to obtain a link, thus covering the parameter's meaning and usage.
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 is for authentication with 'log in in the browser, copy the access token.' It clearly identifies the action and the resource (IDE agents), and distinguishes it from siblings by focusing on the login/token 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?
It provides explicit usage scenarios: 'Best: add it to this server's config as a header ... for permanent ... Or paste it here for session-only login' and 'call with no args to get the link.' This gives clear guidance on when to use each invocation mode, though it doesn't mention alternatives among siblings.
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 declare readOnly and idempotent. The description adds behavioral detail, such as returning connect_url when credentials are missing and authenticated:true when all providers are connected, which enriches transparency 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 two sentences long, concise, and well-structured. It directly conveys the tool's behavior without unnecessary verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the main outputs (authenticated status, pending list, connect URLs) but does not explicitly mention error scenarios or other edge cases. It is sufficiently complete for typical use, though additional detail on failure modes could enhance 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?
The tool has no parameters, so schema coverage is 100%. The description adds no parameter-specific information, which is acceptable since there are none; baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns connection status and URLs, distinguishing it from sibling tools like authenticate or marketplace. It specifies the exact outputs under different conditions, making its purpose 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 for checking connection status but does not explicitly compare with alternatives or state when to prefer this tool over others. It lacks explicit when/when-not guidance, though its behavior is described.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
marketplaceAInspect
The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them. Covers capability requests like "find an MCP that does X", "consulta um CPF", "is there a tool for Y". Core flow: action=search discovers MCPs by intent → describe returns one MCP's full profile (every tool with its id + params, pricing, auth) so you pick the right tool_id → invoke RUNS that tool. KEY: invoke works even when the MCP is NOT installed — it runs the tool pontualmente (one-off), without adding the MCP to the toolkit and without bloating the tool list. If the MCP needs a credential/login, invoke returns a connect link; if it is paid and the wallet is empty, invoke returns a checkout/top-up link (the user opens it, then you retry). Use install only to make an MCP PERMANENT in the active toolkit (its tools then show up natively in future sessions); prefer invoke for a single/occasional use. list_tools lists what is callable right now. subscribe/cancel handle per-MCP billing; report_bug sends feedback; request_mcp asks us to build a NEW MCP when nothing fits. Search/describe flag installed_in_toolkit vs installed_in_workspace. Writes (install/uninstall/subscribe/cancel and the one-off install behind invoke) require workspace owner/admin. It also carries the mcp.ai PROMPT LIBRARY, which is about ready-made prompt TEXT rather than MCPs: search_prompts finds one, get_prompt returns its full text with {{variables}} filled, and publish_prompt saves a prompt and returns a shareable mcp.ai/p/ link that opens without login.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | No | ||
| action | No | search | |
| mcp_id | No | ||
| message | No | ||
| tool_id | No | ||
| arguments | No | {} | |
| immediate | No | ||
| tier_slug | No | ||
| prompt_body | No | ||
| prompt_slug | No | ||
| prompt_tool | No | ||
| prompt_vars | No | {} | |
| conversation | No | [] | |
| prompt_title | No | ||
| request_name | No | ||
| cancel_reason | No | ||
| cancel_comment | No | ||
| prompt_targets | No | ||
| report_context | No | ||
| prompt_category | No | ||
| request_details | No | ||
| prompt_description | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description far exceeds the annotations' disclosure. It reveals auth-required behavior ('if the MCP needs a credential/login, invoke returns a connect link'), payment edge cases ('if it is paid and the wallet is empty, invoke returns a checkout/top-up link'), permission requirements ('Writes... require workspace owner/admin'), and side effects (invoke runs 'without adding the MCP to the toolkit and without bloating the tool list'). No contradiction with annotations exists — description's write-oriented behavior is consistent with readOnlyHint: 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?
It's a wall of text with no bullet points or headers, yet nearly every sentence earns its place — there's almost no filler. The 'KEY:' marker provides a useful emphasis in an otherwise flat structure. The density is justified given the tool covers 14 actions and two distinct subsystems (MCP catalog + prompt library), but it would benefit from paragraph breaks or bullet lists for scannability.
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 23-parameter, 14-action dispatcher with no output schema, the description covers an impressive amount: the core flow, install-vs-invoke distinction, auth and payment edge cases, prompt library, permission model, and the role of every sibling-worthy action (report_bug, request_mcp, list_tools). Minor omissions: no error-handling guidance (e.g., invalid tool_id, network failures) or rate-limit expectations, and the installed_in_toolkit vs installed_in_workspace flags are mentioned but not explained. Still, this is near-complete coverage for an exceptionally 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 coverage and 23 parameters, the description carries the full semantic burden. It does explain the action enum thoroughly in prose (each of the 14 values gets contextual meaning), which is the most important parameter. However, concepts like arguments, prompt_vars, conversation, tool_id, and mcp_id are never explicitly mapped to the actions that need them — it's inferred. The prompt library parameter names (prompt_title, prompt_body, prompt_slug) are guessable but undocumented. The description earns a solid middle score for nailing the action parameter but leaving the remaining 19 parameters unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a clear definition: 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them.' It uses specific verbs (search, describe, invoke, install) and explains the action-dispatch pattern. It differentiates from siblings by explicitly scoping what each action family does and names the distinguishing behavior 'KEY: invoke works even when the MCP is NOT installed' — the kind of detail that sets it apart.
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?
Usage guidance is exemplary: 'Use install only to make an MCP PERMANENT in the active toolkit... prefer invoke for a single/occasional use' provides an explicit when-to-use vs. when-to-avoid directive. It also names alternatives for sibling tools ('list_tools lists what is callable right now', 'request_mcp asks us to build a NEW MCP when nothing fits') and describes the decision flow: search → describe → invoke/install.
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 already indicate readOnly=false, idempotent=true, and destructive=false, so the description does not need to repeat these. However, it adds no extra behavioral context—such as what happens after reporting (e.g., sent to developers, stored in a system) or whether any side effects occur beyond the action. With annotations present, the bar is lower, but the description still lacks useful behavioral details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that front-loads the purpose and adds the key usage tip about including conversation data. There is no redundant information, and it is appropriately brief for a simple reporting tool.
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 low complexity (3 parameters, no output schema), the description covers the core purpose and one essential usage hint. However, it omits the meaning of the 'context' parameter and does not clarify the format of the 'conversation' string, leaving some gaps. It is minimally adequate but not 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 schema has 0% description coverage, so the tool description must compensate for parameter meanings. It only mentions the 'conversation' parameter ('Include the conversation array...') and implicitly the 'message' as the content of the report, but the 'context' parameter is entirely unaddressed. This is insufficient for a tool with three parameters and no 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 reports bugs, missing features, or feedback, and it is distinct from sibling tools like authenticate or show_version. The verb 'report' combined with the resource 'bug/feature/feedback' is specific enough, though it could be more precise about the exact channel or 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?
The description implies when to use this tool (for reporting issues) but does not explicitly contrast with alternatives or provide exclusion criteria. The instruction to 'Include the conversation array with recent messages for reproduction' is a usage hint but not a full guideline on 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.
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 and idempotentHint=true, so the description doesn't need to restate safety traits. The description adds specific context about what 'show' means (platform and adapter versions), which goes slightly beyond 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, front-loaded sentence: 'Show the current MCP platform and adapter versions.' Every word earns its place, with no filler or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters, no output schema, and comprehensive annotations (read-only, idempotent, non-destructive), the description fully covers the tool's purpose and scope. There is nothing more an agent needs to know 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 tool has 0 parametersanding the schema is empty with 100% coverage. The baseline for 0 parameters is 4, and the description adds no parameter-related information, which is appropriate given there are none.
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 shows the current MCP platform and adapter versions, using a specific verb (show) and resource (versions). It distinguishes from siblings like authenticate, connect, marketplace, and 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 you need version information. It provides clear context (checking platform/adapter versions) but does not explicitly state when not to use it or mention alternatives like toolkit_info, which may also provide version info.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sintegra_rn_consultarBRead-onlyIdempotentInspect
SINTEGRA: RN, 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 |
|---|---|---|---|
| ie | No | ||
| cpf | No | ||
| cnpj | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnly, idempotent), the description adds behavioral context: the tool is hosted, requires payment per query, and the client is responsible for LGPD compliance. This enhances transparency about side effects (cost) and data handling.
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 paragraph that includes necessary functional information but also verbose legal disclaimers (LGPD, data control). It is not excessively long, but the legal content could be condensed to improve focus on the tool's core 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?
The description provides some context: it is a query, requires payment, and involves public data. However, it omits output format, error handling, and parameter usage details, leaving the tool's full behavior under-specified. Given the sparse schema, the description does not fill the 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?
The schema lists three parameters (ie, cpf, cnpj) with no descriptions, and the tool description provides no explanation of these fields. Users cannot determine their meaning, format, or which are mutually exclusive, making the parameters effectively undocumented.
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 that the tool performs a query against the official SINTEGRA RN source, distinguishing it from sibling tools like authentication or marketplace. However, it does not explicitly define what SINTEGRA RN is, which could reduce clarity for unfamiliar users.
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 practical usage notes such as requiring prepaid credit and not needing platform credentials, but it does not explicitly state when to use this tool versus alternatives. It implies usage for legitimate queries but lacks clear selection criteria.
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: true and idempotentHint: true, so the description does not repeat that. It adds value by specifying the exact content returned (state components). No contradictions. The description complements annotations without redundancy.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, front-loaded with the action ('Returns'), and every clause contributes meaning. No filler or redundant wording.
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 parameters and no output schema, the description fully specifies what the tool returns, covering all relevant aspects of the toolkit state. There is no missing information for an agent to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parametersaca, so the description need not elaborate on parameter meanings. Per rubric, the baseline for 0 params is 4; the description adds no param info but also does not need to.
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 current toolkit state and enumerates specific components (installed MCPs, connection status, accounts, catalog tool counts). This is a specific verb+resource and clearly differentiates from siblings like 'connect' (action) and 'show_version' (version only).
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 for retrieving status information, which is clear in context. However, it does not explicitly state when to use it over alternatives or versus other tools. Despite no explicit exclusions, the purpose is unambiguous, so a score of 4 is appropriate.
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
Each tool has a clear, distinct role: authenticate handles login, connect checks connection status, marketplace discovers/invokes MCPs, report_bug sends feedback, show_version reports versions, toolkit_info shows installed state, and sintegra_rn_consultar performs the actual query. Some overlap exists between connect and toolkit_info (both report status), but they emphasize different details (auth URLs vs. installed MCPs), so confusion is unlikely.
Tool names follow no single convention: some are bare verbs (authenticate, connect, report_bug), some are noun phrases (marketplace, toolkit_info), one is verb+noun (show_version), and one is domain-specific snake_case (sintegra_rn_consultar). The mixing of verb-first, noun-first, and domain-prefixed names makes the set feel inconsistent and harder to predict.
Seven tools is within a reasonable range, but the count is imbalanced relative to the server's stated purpose ('SINTEGRA: RN'). Six of the seven tools are generic MCP platform management tools, while only one tool actually handles SINTEGRA consultation. The number isn't extreme, but the composition suggests a scope mismatch.
As a platform management server, the coverage is solid: authentication, connection status, marketplace search/invoke/install, toolkit state, version, and bug reporting are all present. However, for the domain implied by the server name, the only capability is a single SINTEGRA query—no other operations are exposed. This leaves the actual domain under-covered while over-covering platform plumbing.