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jupiterbak

AYX-MCP-Wrapper

by jupiterbak

get_all_schedules

Retrieve all scheduled workflows from Alteryx Server to monitor and manage automated task execution.

Instructions

Get the list of all schedules of the Alteryx server

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The core handler function in the AlteryxTools class that retrieves all schedules from the Alteryx server API using schedules_api.schedules_get_schedules() and returns a pretty-formatted response or error message.
    def get_all_schedules(self):
        """Get the list of all schedules of the Alteryx server"""
        try:
            api_response = self.schedules_api.schedules_get_schedules()
            return pprint.pformat(api_response)
        except ApiException as e:
            return f"Error: {e}"
  • MCP tool registration in the register_tools method using @self.app.tool() decorator, which creates a wrapper function that delegates execution to the underlying tools instance's get_all_schedules method.
    def get_all_schedules():
        """Get the list of all schedules of the Alteryx server"""
        return self.tools.get_all_schedules()
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states it 'gets' a list, implying a read operation, but doesn't specify whether it's paginated, sorted, filtered, or includes metadata. For a list-retrieval tool with zero annotation coverage, this leaves significant behavioral gaps.

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 a single, efficient sentence that directly states the tool's purpose without any fluff or redundancy. It's appropriately sized for a simple tool and front-loads the key information effectively.

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

Completeness3/5

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

Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is adequate but minimal. It covers the basic purpose but lacks details on behavior, output format, or usage context, which could be helpful for an AI agent despite the low complexity.

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?

The tool has 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description doesn't need to compensate for any gaps, and it appropriately avoids unnecessary parameter details, aligning with the baseline for zero parameters.

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?

The description clearly states the action ('Get') and resource ('list of all schedules of the Alteryx server'), making the purpose understandable. However, it doesn't explicitly distinguish this from sibling tools like 'get_schedule_by_id' or 'get_all_collections', which would require more specific differentiation to earn a 5.

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?

The description provides no guidance on when to use this tool versus alternatives like 'get_schedule_by_id' for specific schedules or 'get_all_collections' for other resources. It lacks context about use cases, prerequisites, or exclusions, offering minimal usage direction.

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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