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 declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable behavioral context by describing the two conditional outcomes: when all providers are connected vs. when credentials are missing, including the specific return fields (authenticated:true, empty pending[], connect_url). This goes beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the main purpose, and no wasted words. Every sentence provides meaningful behavioral detail.
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 tool with no parameters and no output schema, the description covers the essential return scenarios (all connected vs. missing credentials). It is sufficiently complete for an AI agent to understand what to expect without further details.
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 input schema is empty with zero parameters. The description correctly adds no parameter information since none exist. Baseline for 0 parameters is 4, and the description does not need to compensate for any schema gaps.
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 'Returns connection status and URLs' with a specific verb and resource. It distinguishes from the sibling 'authenticate' by focusing on status retrieval rather than the authentication action itself.
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 context for when to use the tool (to check connection status and obtain URLs). However, it does not explicitly mention when not to use it or point to alternatives like 'authenticate', so it lacks explicit exclusions.
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.
Most tools are clearly distinct: renda_estimada_consultar, report_bug, show_version, and toolkit_info each have unique purposes. However, authenticate and connect overlap around authentication/connection status, and marketplace and toolkit_info share some visibility into installed tools, causing minor ambiguity.
Tool names are inconsistent: some are English verbs (authenticate, connect, report_bug, show_version), some are English nouns (marketplace, toolkit_info), and the sole domain-specific tool is in Portuguese with an awkward noun_noun_verb structure (renda_estimada_consultar). No clear naming pattern emerges.
The count of 7 tools is within a reasonable range, but the server's stated purpose is socioeconomic level and income estimation, while only one tool addresses that domain. The rest are generic platform utilities, making the set feel misaligned and somewhat bloated for the claimed focus.
For a server supposedly dedicated to income estimation, there is only a single 'consult' operation and no supporting tools (e.g., batch lookup, validation, or explanation of data sources). The large number of unrelated utility tools does not compensate for the lack of domain coverage, leaving significant gaps for agents seeking comprehensive socioeconomic data.