show_version
Show the current MCP platform and adapter versions.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Show the current MCP platform and adapter versions.
| 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 and idempotentHint=true, covering safety. The description adds the specific types of versions (platform and adapter) but does not disclose any additional behavior like error conditions or output format. This is acceptable for a simple query tool.
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 conveys exactly what the tool does with no unnecessary words.
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 no-parameter, read-only version tool, the description fully specifies its behavior. No output schema is needed, and the provided annotations and description cover all necessary information.
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. The description adds no parameter details because none exist. Baseline 4 applies for zero-parameter tools.
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 and resource. It is distinct from sibling tools, which are primarily action-oriented or domain-specific, making the 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?
No explicit when-to-use guidance is given, but the purpose is trivial: it is the tool for checking versions. No alternatives or exclusions are mentioned, so it relies on user inference.
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.
The server mixes two distinct domains (HiveCloud fiscal documents and mcp.ai platform controls) with several similarly-named tools (hivecloud_list_ctes vs hivecloud_get_cte vs hivecloud_cte_xml; hivecloud_list_mdfes vs hivecloud_get_mdfe). The generic 'authenticate', 'connect', and 'toolkit_info' overlap in connection/account status purposes, creating ambiguity about which to call for setup.
Tools mostly follow a 'hivecloud_<domain>_<action>' pattern (e.g., hivecloud_cte_emitir, hivecloud_cte_cancelar), but there are exceptions like 'hivecloud_avaliar' (short verb without domain), 'get_cte' vs 'list_ctes' (tense/plural inconsistency), and generic tools 'authenticate', 'connect', 'report_bug' that don't follow the pattern. Mixed Portuguese/English verbs further reduce consistency.
With 33 tools, this is on the heavy side. The domain spans CT-e, MDF-e, NF-e, DC-e, plus platform management (marketplace, toolkit, bug reporting, versioning) — it bundles too many concerns into one server. Several tools (report_bug, show_version, marketplace) feel unrelated to HiveCloud fiscal document handling, making the count feel bloated.
For the CT-e and MDF-e lifecycle, the surface is quite complete: create from NF-e, emit, cancel, edit (carta de correção), delete drafts, print DACTE/DAMDFE, export XML, list/get, and even a travel report. DC-e and NF-e are lighter (only list/query), and missing tools like 'create_mdfe' (no draft creation for MDF-e) or 'update_mdfe' (only cancel/end) are notable gaps. However, core workflows are well covered.