Skip to main content
Glama

pause_automation

Pause all emails in a classic Mailchimp automation workflow to temporarily stop automated email sequences.

Instructions

Pause all emails in a classic automation workflow.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workflow_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The tool is registered using @mcp.tool() and the function pause_automation handles the API request to Mailchimp to pause the specified automation workflow.
    @mcp.tool()
    async def pause_automation(workflow_id: str) -> str:
        """Pause all emails in a classic automation workflow."""
        mc = get_client()
        await mc.post(f"/automations/{workflow_id}/actions/pause-all-emails")
        return _fmt({"workflow_id": workflow_id, "message": "Automation paused."})
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 the action ('pause') but does not explain what 'pause' entails (e.g., immediate effect, reversibility, impact on scheduled emails, permissions required, or rate limits). This leaves significant gaps for a mutation tool.

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 with no wasted words, making it easy to parse and front-loaded with the core action. It is appropriately sized for the tool's complexity.

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

Completeness2/5

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

Given that this is a mutation tool with no annotations, low schema coverage (0%), and an output schema (which helps but isn't described), the description is incomplete. It lacks details on behavior, parameters, and usage context, making it inadequate for safe and effective tool invocation.

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 description does not mention the 'workflow_id' parameter or provide any details beyond what the schema offers (0% coverage). Since there is only one parameter and schema coverage is low, the baseline is 3, as the description does not compensate for the lack of schema details but doesn't worsen it either.

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 verb ('pause') and resource ('all emails in a classic automation workflow'), making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'start_automation' or 'list_automations', which would be needed for a perfect score.

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 (e.g., 'start_automation' for resuming, 'list_automations' for checking status) or any prerequisites. It lacks context for effective decision-making by an AI agent.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/AlexlaGuardia/mcp-mailchimp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server