workflows-mcp

Create a new workflow with specified steps and configuration.

WORKFLOW STRUCTURE:

• name: Descriptive workflow name
• description: What the workflow accomplishes
• goal: The end result or outcome
• version: Semantic version (default: "1.0.0")
• tags: Array of categorization tags
• inputs: Object defining input parameters with type, description, required, and optional default
• outputs: Array of expected output variable names
• required_tools: Array of MCP tools this workflow needs
• steps: Array of workflow steps (see below)
• strict_dependencies: Boolean to enable strict dependency mode (default: false)
  • false: Steps without dependencies see all variables (backward compatible)
  • true: Steps without dependencies see NO variables (must explicitly declare dependencies)

AVAILABLE ACTIONS:

• tool_call: Execute an MCP tool (requires tool_name and parameters)
• analyze: Analyze data and extract insights
• consider: Evaluate options or possibilities
• research: Gather information on a topic
• validate: Check data quality or correctness
• summarize: Create a summary of information
• decide: Make a decision based on criteria
• wait_for_input: Request user input (requires prompt)
• transform: Transform data (requires transformation description)
• extract: Extract specific information
• compose: Create new content
• branch: Conditional branching (requires conditions array)
• checkpoint: Save progress checkpoint
• notify: Send a notification (requires message)
• assert: Verify a condition (requires condition)
• retry: Retry a previous step (requires step_id)

STEP STRUCTURE: { "id": 1, // Sequential number starting from 1 "action": "action_type", "description": "What this step does", "save_result_as": "variable_name", // Optional: save result "error_handling": "stop|continue|retry", // Default: "stop" "dependencies": [1, 3], // Optional: only show outputs from these step IDs "show_all_variables": true, // Optional: override to show all variables

// For tool_call: "tool_name": "mcp_tool_name", "parameters": { "param": "value" },

// For cognitive actions (analyze, consider, research, etc): "input_from": ["variable1", "variable2"], // Input variables "criteria": "Specific criteria or focus", // Optional

// For branch: "conditions": [ { "if": "variable.property > value", "goto_step": 5 } ],

// For wait_for_input: "prompt": "Question for the user", "input_type": "text|number|boolean|json",

// For transform: "transformation": "Description of transformation" }

TEMPLATE VARIABLES: Use {{variable_name}} in any string field to reference:

• Input parameters from workflow inputs
• Results saved from previous steps via save_result_as
• Any variables in the workflow state

EXAMPLES:

• "path": "output_{{format}}.txt"
• "prompt": "Process {{count}} items?"
• "description": "Analyzing {{filename}}"

DEPENDENCY MANAGEMENT:

• Use "dependencies" array to specify which previous steps' outputs are needed
• In strict_dependencies mode, steps without dependencies see NO variables
• Steps with dependencies only see outputs from those specific steps + workflow inputs
• Use "show_all_variables": true to override and see all variables for a specific step

PERFORMANCE FEATURES:

• Only relevant variables are shown based on dependencies (reduces token usage)
• Variable changes are highlighted (+ for new, ~ for modified)
• Only next 3 steps are previewed (progressive loading)

BEST PRACTICES:

1. Each step should have a single, clear responsibility
2. Use descriptive variable names for save_result_as
3. Consider error handling for each step (stop, continue, or retry)
4. Branch conditions should cover all cases
5. Order steps logically with proper dependencies
6. Use strict_dependencies for workflows with large/verbose outputs
7. Explicitly declare dependencies to minimize context and improve performance