Skip to main content
Glama
Sign In
fluig-mcp

fluig-mcp

by alucardigo
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

fluig_dataset_list

Lists TOTVS Fluig datasets with their IDs and types for a chosen test or production environment, and filters results by a substring in the dataset ID or description.

Instructions

Lista datasets do servidor (id + tipo). Aceita filtro (substring em id/descrição).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "env": "<env>"
    },
    "name": "fluig_dataset_list"
  }
}

Input Schema

NameRequiredDescriptionDefault
envYesOBRIGATÓRIO. Ambiente alvo: "teste" (homologação, o host de FLUIG_HOST) ou "prod" (PRODUÇÃO REAL, o host de FLUIG_HOST_PROD). Não há default: a escolha é sempre explícita, para que ninguém leia homologação achando que é produção nem escreva em produção achando que é teste.
filtroNosubstring para filtrar (opcional)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv1.3.0
    • addedInput schema / properties / env
      Added value: +{
+  "description": "OBRIGATÓRIO. Ambiente alvo: \"teste\" (homologação, o host de FLUIG_HOST) ou \"prod\" (PRODUÇÃO REAL, o host de FLUIG_HOST_PROD). Não há default: a escolha é sempre explícita, para que ninguém leia homologação achando que é produção nem escreva em produção achando que é teste.",
+  "enum": [
+    "teste",
+    "prod"
+  ],
+  "type": "string"
+}
    • removedInput schema / properties / filter
      Removed value: -{
-  "description": "Substring to filter by (optional).",
-  "type": "string"
-}
    • addedInput schema / properties / filtro
      Added value: +{
+  "description": "substring para filtrar (opcional)",
+  "type": "string"
+}
    • changedInput schema / required
      Previous value: -[]New value: +[
+  "env"
+]
  2. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the burden alone; "Lista" implies read-only and the parenthetical discloses what comes back (id + type), which is real value since there is no output schema. It says nothing about volume, pagination, or permissions, which matter for a server-wide listing.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences, output shape front-loaded before the optional filter behavior. No filler, no repetition of the name.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a two-parameter read tool with no output schema and no annotations, the description covers what the tool returns and how filtering behaves, which is the essential missing structured information. It never mentions the mandatory env parameter's test/prod consequence, but the schema documents that exhaustively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline would be 3, but the description adds meaning the schema lacks: it specifies that the filter substring matches against both the dataset id and its description, whereas the schema only says "substring para filtrar". That clarification directly improves filter usage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Names a specific verb+resource ("Lista datasets do servidor") and states the shape of each item (id + tipo), so an agent knows this is an enumeration of dataset definitions rather than execution or detail. It does not explicitly distinguish itself from the many dataset siblings (get, run, structure, history), leaving that to the reader.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No when-to-use or when-not-to-use guidance is given; nothing says to reach for fluig_dataset_get for one dataset or fluig_dataset_run to execute one. The optional filter hint is the only contextual cue about appropriate use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

Other Tools