Skip to main content
Glama
mondaycom

monday MCP Server

Official
by mondaycom

Plan Workflow

plan_workflow
Read-onlyIdempotent

Analyzes a described process to plan monday.com workflows, identifying required boards, columns, triggers, and actions, returning a structured implementation plan.

Instructions

Plans one or more monday.com workflows for a described process using an AI agent.

The agent analyzes the prompt, decides how many workflows are needed, identifies the required boards and columns, selects the correct trigger and action blocks (with their IDs), and returns a structured implementation plan with Mermaid diagrams and build notes for each workflow.

Use this before create_workflow to understand how to break a complex process into individual workflows and which resources to create first.

Parameters:

  • prompt: describe the full end-to-end process in plain English. Maximum 2000 characters.

Returns:

  • result: structured markdown plan with workflow breakdowns, block IDs, resource definitions, and a list of assumptions and gaps

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesNatural-language description of the process to plan. Describe the full end-to-end process in plain English (e.g. "When a deal is marked Won, create a task in the onboarding board and notify the account manager"). The agent will decompose this into one or more monday.com workflows, identify all required boards and columns, and return a structured implementation plan. Maximum 2000 characters.
Behavior5/5

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

Annotations indicate read-only, non-destructive, idempotent behavior. The description adds significant context: the AI analyzes prompts, decides workflow count, identifies boards/columns, selects trigger/action blocks with IDs, and returns a structured plan with diagrams. No contradiction.

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 well-structured: overall purpose, agent behavior, usage guidance, parameter details, return value. It is concise with no fluff, front-loading the core purpose.

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 single parameter, good annotations, and lack of output schema, the description covers purpose, behavior, usage, and return format comprehensively. It provides enough context for an agent to use the tool correctly.

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% with a good description. The description adds extra value by specifying the maximum 2000 character limit and providing an example phrasing, enhancing the schema's explanation.

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 'plans one or more monday.com workflows' using an AI agent. It uses a specific verb (plans) and resource (workflows), and distinguishes itself from siblings like create_workflow by noting it should be used beforehand.

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

Usage Guidelines5/5

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

Explicitly says 'Use this before create_workflow to understand how to break a complex process into individual workflows and which resources to create first.' This provides clear when-to-use and when-not-to-use guidance, and references an alternative.

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/mondaycom/mcp'

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