Lista os CT-e (Conhecimento de Transporte eletrônico) da empresa, paginado, com filtro por data de emissão. Retorna número, série, UF inicial/final, valor do frete, remetente/destinatário, status, datas e status de averbação.
Bulk support: accepts empresa_ids for batched execution.
| Name | Required | Description | Default |
|---|---|---|---|
| account | No | ||
| pageSize | No | ||
| data_final | No | ||
| empresa_id | No | ||
| pageNumber | No | ||
| empresa_ids | No | ||
| data_inicial | No |
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, covering the safety profile with a low bar. The description adds value by disclosing the return fields (número, série, UF inicial/final, valor do frete, remetente/destinatário, status, datas, status de averbação) and the bulk execution behavior. This is useful context beyond the annotations, especially with no output schema.
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 reasonably efficient (~50 words), front-loads the core purpose and return values, then appends the bulk note. The minor structural issue is the language mixing (Portuguese main body with English bulk sentence), which could cause slight processing inconsistency, but it's not overly verbose.
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 7-parameter tool with no output schema and 0% schema coverage, the description covers return values (compensating for missing output schema), main behavior, and bulk mode. However, it leaves gaps around parameter semantics (account/empresa_id roles, date formats), pagination defaults, and any filtering caveats. It's adequate for selecting the tool but insufficient for fully 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?
Schema description coverage is 0%, so the description must compensate. It partially does: 'filtro por data de emissão' implies data_inicial/data_final as a date range, 'paginado' implies pageNumber/pageSize, and 'Bulk support: accepts empresa_ids' clarifies that param. However, 'account' and 'empresa_id' are unexplained, their relationship to 'empresa_ids' is unclear, and no date format or pagination defaults are specified.
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 ('Lista os CT-e') and resource (Conhecimento de Transporte eletrônico), and specifies scope (da empresa, paginado, com filtro por data de emissão). This clearly distinguishes it from siblings like hivecloud_get_cte (singular fetch), hivecloud_list_mdfes, and hivecloud_list_dces, which target different document types or granularity.
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 context is implied: it's a paginated list operation with date filtering, and the bulk support note ('accepts empresa_ids for batched execution') gives some guidance. However, there is no explicit when/when-not guidance contrasting with alternatives (e.g., when to use get_cte for a single document vs this list tool), and no mention of default pagination values or authentication prerequisites.
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.