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 arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
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 valuable return-state details (authenticated:true with empty pending[] when all connected, and connect_url when credentials missing), which enriches understanding beyond the annotations without contradicting them.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences: the first states the core function, and the second covers conditional outputs. No fluff, front-loaded with the main action, and every word adds value.
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, the description fully covers observable behavior, including both success and partial-failure states. Since there is no output schema, explaining the return values is essential and done well.
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 of 4 is used. The description correctly focuses on behavior rather than parameters, and no additional parameter information is 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 the tool 'Returns connection status and URLs' with a specific verb and resource, and the conditional behaviors (authenticated:true vs connect_url) distinguish it from sibling tools like 'authenticate' or 'toolkit_info'. This is a specific, unambiguous purpose.
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 this is for checking connection status and handling missing credentials, but it does not explicitly state when to use this over alternatives or mention any exclusions. There is no direct comparison to siblings like 'authenticate', so usage context is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tools overlap around authentication and connection state: `authenticate`, `connect`, and `toolkit_info` all surface credentials/connection/status information. The large `marketplace` tool also contains sub-actions like invoke, list_tools, and report_bug, creating competing paths to actions that have dedicated top-level tools.
Naming is mixed between bare verbs (`authenticate`, `connect`), snake_case verb phrases (`report_bug`, `show_version`), noun-style labels (`marketplace`, `toolkit_info`), and one long Portuguese domain operation. There is no consistent verb-noun or name-based pattern across the set.
Seven tools is within a reasonable size, and most platform tools have a clear operational role. However, it is slightly over-scoped: only one tool is genuinely domain-specific, while the rest are generic platform/admin helpers that could feel redundant outside the MCP.AI environment.
The core read-only domain need — consulting a TRT1 case — is covered by `tribunal_trt1_processo_consultar`, and marketplace/payment/auth machinery covers surrounding concerns. Deeper court-process operations are not represented, but for a single-source public consultation server there is no obvious severe domain gap.