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delt4d

MCP Sankhya Community Search Server

by delt4d

sankhya_call_service

Invoke Sankhya services via REST API and receive JSON responses containing status and body.

Instructions

Chama um serviço Sankhya via API REST.

Retorna JSON da resposta incluindo status ('1'=ok, '0'=erro) e responseBody. Use sankhya_list_connections para ver as conexões disponíveis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
moduleNoMódulo Sankhya: 'mge' (padrão), 'mgecom', 'mgeloc', 'mgefin', etc.mge
connectionNoNome da conexão (ver sankhya_list_connections). Default: conexão padrão.
request_bodyNorequestBody da chamada. Campos usam wrapper {"CAMPO": {"$": valor}}
service_nameYesNome do serviço Sankhya, ex: 'CACSP.confirmarNota', 'CRUDServiceProvider.loadRecords'

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

The description adds behavioral context beyond the annotations by explaining the response structure (status with '1'=ok/'0'=erro and responseBody). It does not contradict the readOnlyHint=false annotation. It could include more side-effect warnings, but the annotation already signals possible writes and the openWorldHint gives additional context.

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?

The description is three short, front-loaded sentences with no filler. Each sentence provides distinct value: what the tool does, what the response looks like, and where to find connection details.

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?

Given the tool has a rich input schema, an output schema, and annotations, the description covers the essential behavioral aspects (invocation, response status, connection discovery). It is sufficiently complete for a generic REST service caller, though it could mention error handling or side-effect variability explicitly.

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

Parameters3/5

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

The input schema already provides 100% coverage of parameter descriptions, including examples for service_name and the request_body wrapper format. The tool description does not add further parameter semantics; it mainly reiterates the connection lookup already mentioned in the schema.

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

Purpose5/5

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

The description clearly states the tool calls a Sankhya service via REST API, using a specific verb ('Chama') and resource ('serviço Sankhya via API REST'). It also specifies the response format, which distinguishes it from sibling tools like execute_query or call_procedure.

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

Usage Guidelines3/5

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

The description gives a useful pointer to sankhya_list_connections for discovering connections, which helps with a prerequisite. However, it does not explicitly state when to prefer this tool over alternatives like execute_query or call_procedure, nor does it provide exclusions or alternative guidance.

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

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