SINTEGRA: PE
Server Details
SINTEGRA: PE, official-source lookup. Platform-hosted, pay per query with prepaid credit.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- mcp-dir/sintegra_pe-mcp
- GitHub Stars
- 0
- Server Listing
- SINTEGRA: PE MCP Server
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?
Beyond the annotations (idempotentHint=true, readOnlyHint=false), the description discloses session vs. permanent token behavior, non-expiring config-based auth, and that no-arg calls return a link. This adds useful context about side effects and token lifecycle, which is not present in the annotations alone.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and information-dense, covering config setup, session-only usage, and no-args behavior in two sentences. The first clause 'MCP.AI for IDE agents (Cursor, etc.)' is somewhat odd as a lead-in, but the content is efficient and front-loaded with the core login action.
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?
There is no output schema, and the description only mentions that no-args calls return the login link. It does not describe the outcome of a token call, error handling for invalid tokens, or what happens after successful authentication, leaving some gaps for an auth tool with no structured output definition.
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 compensates by explaining the token parameter as a JWT pasted from the browser and how it is used (call with { token: "<jwt>" }). It also clarifies the no-arg alternative, giving the parameter meaning beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as an authentication mechanism for IDE agents, specifying 'log in in the browser, copy the access token' and accepting a JWT. It distinguishes itself from sibling 'connect' by focusing on token-based login and link generation, though the opening phrase 'MCP.AI for IDE agents' is slightly cryptic.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit usage modes: best practice is to add the token to server config for a permanent connection, while pasting the token allows session-only login. It also explains that calling with no args retrieves the login link, providing clear when-to-use guidance for each scenario.
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 readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is known. The description adds behavioral context by explaining the conditional responses: when all providers are connected, it returns authenticated:true and empty pending[], and when credentials are missing, it returns connect_url. This goes beyond what annotations provide, adding valuable state-dependent behavior 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 two concise sentences, front-loading the main purpose ('Returns connection status and URLs'). Every sentence adds necessary information about the conditional outputs, with no fluff 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?
Given the tool's simplicity (no parameters, no output schema), the description adequately covers the expected outputs and conditions. It explains the two primary states—connected and missing credentials—and the relevant URLs, making it complete enough for an agent to understand the tool's behavior without additional context.
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 baseline for parameter semantics is 4. The description does not need to explain parameters, and since there are none, it correctly omits any parameter-related details. No additional meaning is required beyond the empty schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: it returns connection status and URLs. This is a specific verb-resource pair and is distinct from sibling tools like authenticate, marketplace, and show_version, 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 provides clear context on what the tool does, describing the outputs under different conditions (all providers connected vs. missing credentials). It implies usage for checking connection status, but does not explicitly state when to use it versus alternatives like authenticate. There are no exclusions, so it qualifies as clear context without exclusions.
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 are sparse (readOnlyHint: false, destructiveHint: false), so the description carries the burden — and it delivers. It discloses critical runtime behaviors: invoke runs one-off without installing ('runs the tool pontualmente'), returns connect links for auth, checkout links for empty wallets, openWorldHint=true aligns with the arbitrary capability requests stated. No contradiction with annotations, and substantial value is added beyond what the annotations state.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A ~300-word single unbroken paragraph with no bullets, line breaks, or examples. Mixed-language usage ('consulta um CPF', 'pontualmente') creates ambiguity. Dense semantically, but the structural choices force multiple re-reads to extract the flow. The information deserves 4s, but the presentation badly needs formatting.
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 exceptional complexity (23 params, no required fields, 14-action dispatcher, 3 sub-flows), the description covers capability discovery, one-off invocation, permanence semantics, billing/auth edge cases, permission requirements, and prompt library features. Very few gaps exist in content — mostly gaps in navigation/structure.
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% with 23 parameters and only 2 enums, putting a heavy burden on the description. The description does excellent work explaining the 'action' enum values (search→describe→invoke flow, search_prompts/get_prompt/publish_prompt), which is the semantic core. However, 16+ parameters (conversation, cancel_reason, prompt_targets, request_details, arguments, etc.) receive zero explanation, and the mcp_id/tool_id relationship is only implied, not stated.
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 opener 'The official mcp.ai marketplace — the in-platform catalog of every MCP/tool, AND the way to run them' clearly establishes identity and scope. It defines coverage boundaries ('Covers capability requests like...') which aids sibling differentiation, though the purpose is inherently diffuse across 14 actions and 3 sub-flows, and no single verb captures it.
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 when-to-use logic: 'Use install only to make an MCP PERMANENT in the active toolkit... prefer invoke for a single/occasional use.' Also covers edge cases (auth connect links, payment top-up then retry) and permission requirements ('Writes... require workspace owner/admin'). Loses a point by not explicitly naming alternative tools or a decision tree for sibling differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
report_bugAIdempotentInspect
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 cover the basic safety profile (readOnlyHint=false, idempotentHint=true, destructiveHint=false), so the description only needs incremental behavioral context. It adds the conversation/reproduction detail but does not explain side effects, responses, or what happens after submission.
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 short, focused sentences: the first names the action, the second gives the critical reproduction instruction. There is no filler or redundant restatement of annotations.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with no output schema and 3 parameters, the description covers the core workflow and highlights reproduction data. However, it under-specifies the message and context parameters and the conversation serialization mismatch with the schema creates a real usability gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds meaning only to 'conversation' by calling it an 'array' with recent messages, but the schema defines it as a string with default '[]'; it also leaves 'message' and 'context' 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 uses the specific verb 'Report' and clearly identifies the resource ('a bug, missing feature, or send feedback'). It is easily distinguishable from sibling tools like authenticate, marketplace, 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 gives clear usage context by instructing the user to include the conversation array with recent messages for reproduction. It does not explicitly mention alternatives or exclusions, but no sibling tool overlaps with bug reporting.
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, and destructiveHint=false, covering the safety profile. The description adds only the minor qualifier 'current' and the specific scope (platform and adapter versions), which is consistent with the annotations but not a substantial behavioral disclosure.
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 with no filler or repetition. Every word contributes meaning, making it highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, read-only version lookup, the description is complete: it identifies exactly what information will be shown. The strong annotations cover safety and idempotency, and no output schema is needed given the simple subject matter.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and the schema description coverage is 100%, so there are no parameter semantics for the description to add. This matches the baseline for a no-parameter tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Show') and a clear resource ('current MCP platform and adapter versions'). It unambiguously states what the tool does and is easily distinguishable from siblings by focusing specifically on version information.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as toolkit_info. It does not mention exclusions, prerequisites, or situational advice, leaving the agent to infer usage from the tool's name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sintegra_pe_consultarBRead-onlyIdempotentInspect
SINTEGRA: PE, 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 | ||
| login_cpf | No | ||
| login_senha | No | ||
| pkcs12_cert | No | ||
| pkcs12_pass | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as read-only and idempotent. The description adds meaningful context beyond that: prepaid billing per query, non-confidential data classification, and the client's data-controller responsibility under LGPD. No contradiction with annotations, though the role of login/cert parameters remains ambiguous.
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 concise four-sentence paragraph that front-loads the essential purpose. Each sentence adds value, covering source, hosting, billing, data classification, and legal responsibility; a little restructuring could improve scannability, but overall length and density are reasonable.
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 adding important source, billing, and legal context, the tool has 7 parameters, no output schema, and no parameter guidance. An agent cannot infer which identifier is required, whether authentication credentials are needed, or what the return value looks like, leaving a significant completeness gap for real 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 schema has 7 parameters with 0% description coverage, and the description does not explain any of them. It never clarifies the roles of ie, cpf, cnpj, login fields, or pkcs12 parameters, nor hints at valid combinations, so the agent receives no semantic guidance for constructing a call.
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 opens with 'SINTEGRA: PE, consulta em fonte oficial' and clarifies it queries information from official Brazilian sources, giving a specific verb and resource scope. It is distinguishable from generic siblings like authenticate and connect, though it could more explicitly state the exact SINTEGRA registration data returned.
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 useful operational context: hosted by the platform, no platform credentials required, prepaid credit per query, and LGPD compliance obligations. This implies when it is appropriate to use and differentiates it from authentication-oriented siblings, but it does not name explicit alternative tools or state when-not-to-use conditions.
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, idempotentHint=true, and destructiveHint=false, establishing a safe read operation. The description adds meaningful context by specifying exactly what state is reported, which is especially valuable given there is no output schema to clarify the return payload.
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 core purpose and then uses a colon to enumerate the specific data points. Every phrase earns its place, and there is no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, read-only status tool with rich annotations and no output schema, the description fully covers the expected behavior and return contents. It lists all the key state components (installed MCPs, connection status, accounts, catalog tool counts) with no significant 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 tool has zero parameters, so the schema is trivially complete (100% coverage). The description correctly focuses on the return value rather than parameters, which is the appropriate behavior for a no-argument tool. Baseline 4 applies because there is nothing to clarify.
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 ('Returns') and names the exact resource ('current toolkit state'), then enumerates the concrete contents: installed MCPs, connection status, connected accounts, and catalog tool counts. This clearly distinguishes it from sibling tools like show_version (version-only) and connect/authenticate (actions rather than state reporting).
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 clearly implies when to use this tool: whenever you need an overview of the toolkit's state, including connections and installed MCPs. It does not explicitly state when not to use it or name alternatives, but the context is unambiguous for a read-only info tool.
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
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TDQS
Most tools have distinct purposes: authenticate/connect handle auth, marketplace is the catalog/execution hub, sintegra_pe_consultar is the actual data lookup, and report_bug/show_version/toolkit_info are auxiliary. Some overlap between connect and toolkit_info regarding connection status, but descriptions clarify the difference.
Naming mixes lowercase single-word verbs (authenticate, connect, marketplace, report_bug, show_version, toolkit_info) with one snake_case Portuguese tool (sintegra_pe_consultar). The pattern is not uniform, but the names are mostly readable and follow a verb-first or noun-verb structure.
Seven tools is a reasonable count for a hybrid platform server that handles auth, catalog/search, execution orchestration, and one domain-specific lookup. It is slightly heavy because the marketplace tool bundles many sub-actions (search, describe, invoke, install, subscribe, list_tools, prompts) into one description, but the overall scope justifies the count.
The server covers the core lifecycle of platform management: auth, connection status, catalog discovery, one-off execution, permanent installation, billing controls, bug reporting, and version info. A minor gap is no explicit tool for managing multiple accounts or retrieving detailed per-install credentials beyond connect, but the described flows handle most needs.