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Cin7 Core Meta MCP Server

by tzenderman

invoke_api_endpoint

Validate and invoke any Cin7 Core API endpoint by providing method, path, optional query parameters, and request body. Returns success data or validation errors.

Instructions

Validate, then execute, a Cin7 Core REST API call.

Args: method: HTTP verb (GET, POST, PUT, PATCH, DELETE). Case-insensitive. path: Endpoint path, e.g. "Product", "advanced-purchase", "sale/order". Leading slashes are stripped. query_params: Query-string parameters. Validated against the endpoint's declared params. body: JSON request body. Validated against the endpoint's required body fields (extras are permitted).

Returns: Success: {"status": 200, "data": <json>, "rate_limit_remaining": "59"}. Cin7 4xx response: {"status": 4xx, "data": <body or null>, "errors": [...]}. Validation failure: {"status": null, "data": null, "errors": [...]}.

Raises: Cin7AuthError | Cin7NotFoundError | Cin7RateLimitError | Cin7APIError: Transport-level failures the model cannot fix.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
methodYes
pathYes
query_paramsNo
bodyNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

With no annotations provided, the description fully discloses behavior: validation then execution, specific return structures for success, 4xx errors, and validation failures, plus a list of transport-level exceptions. It also mentions case-insensitivity and leading-slash stripping.

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

Conciseness4/5

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

The description is somewhat lengthy but well-structured with bullet points. It front-loads the purpose, then details args, returns, and exceptions. Every sentence is informative, though slight trimming could be done while maintaining clarity.

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

Completeness5/5

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

Given the tool's complexity (4 parameters, validation, multiple return types, exceptions) and the presence of an output schema (not shown), the description provides comprehensive coverage: parameter semantics, return value formats, error handling, and exceptions. No gaps remain.

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

Parameters5/5

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

Schema coverage is 0%, but the description thoroughly explains all four parameters: method (case-insensitive, allowed verbs), path (example, leading slashes stripped), query_params (validated against endpoint schema), and body (validated, extras permitted). It compensates fully for the schema's lack of descriptions.

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 validates then executes a Cin7 Core REST API call. It lists the HTTP method and endpoint path, distinguishing it from sibling tools that retrieve schemas or list endpoints.

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

Usage Guidelines4/5

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

The description provides detailed parameter explanations, validation steps, and expected return formats. It does not explicitly contrast with alternatives like get_api_endpoint_schema, but it gives sufficient context for when to invoke this tool.

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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