About fiveohhwon_workflows
fiveohhwon_workflows is an MCP server published by git+FiveOhhWon in the AI category: mCP Server can execute workflows and complex pipelines, similar to Argo or Github Workflow. It has been installed 0 times through Conduid.
The repository has 7 stars and 3 forks, with the last commit 6 months ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues (0) before depending on it in production.
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README
workflows-mcp
🤖 Co-authored with Claude Code - Building workflows so LLMs can finally follow a recipe without burning the kitchen! 🔥
A powerful Model Context Protocol (MCP) implementation that enables LLMs to execute complex, multi-step workflows with cognitive actions and tool integrations.
🌟 Overview
workflows-mcp transforms how AI assistants handle complex tasks by providing structured, reusable workflows that combine tool usage with cognitive reasoning. Instead of ad-hoc task execution, workflows provide deterministic, reproducible paths through multi-step processes.
🚀 Key Features
- 📋 Structured Workflows: Define clear, step-by-step instructions for LLMs
- 🧠 Cognitive Actions: Beyond tool calls - analyze, consider, validate, and reason
- 🔀 Advanced Control Flow: Branching, loops, parallel execution
- 💾 State Management: Track variables and results across workflow steps
- 🔍 Comprehensive Validation: Ensure workflow integrity before execution
- 📊 Execution Tracking: Monitor success rates and performance metrics
- 🛡️ Type-Safe: Full TypeScript support with Zod validation
- 🎯 Dependency Management: Control variable visibility to reduce token usage
- ⚡ Performance Optimized: Differential updates and progressive step loading
📦 Installation
Using npx (recommended)
npx @fiveohhwon/workflows-mcp
From npm
npm install -g @fiveohhwon/workflows-mcp
From Source
git clone https://github.com/FiveOhhWon/workflows-mcp.git
cd workflows-mcp
npm install
npm run build
🏃 Configuration
Claude Desktop
Add this configuration to your Claude Desktop config file:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
Using npx (recommended):
{
"mcpServers": {
"workflows": {
"command": "npx",
"args": ["-y", "@fiveohhwon/workflows-mcp"]
}
}
}
Using global install:
{
"mcpServers": {
"workflows": {
"command": "workflows-mcp"
}
}
}
Using local build:
{
"mcpServers": {
"workflows": {
"command": "node",
"args": ["/absolute/path/to/workflows-mcp/dist/index.js"]
}
}
}
Development Mode
For development with hot reload:
npm run dev
📖 Workflow Structure
Workflows are JSON documents that define a series of steps for an LLM to execute:
{
"name": "Code Review Workflow",
"description": "Automated code review with actionable feedback",
"goal": "Perform comprehensive code review",
"version": "1.0.0",
"inputs": {
"file_path": {
"type": "string",
"description": "Path to code file",
"required": true
}
},
"steps": [
{
"id": 1,
"action": "tool_call",
"tool_name": "read_file",
"parameters": {"path": "{{file_path}}"},
"save_result_as": "code_content"
},
{
"id": 2,
"action": "analyze",
"description": "Analyze code quality",
"input_from": ["code_content"],
"save_result_as": "analysis"
}
]
}
🎯 Action Types
Tool Actions
- tool_call: Execute a specific tool with parameters
Cognitive Actions
- analyze: Examine data and identify patterns
- consider: Evaluate options before deciding
- research: Gather information from sources
- validate: Check conditions or data integrity
- summarize: Condense information to key points
- decide: Make choices based on criteria
- extract: Pull specific information from content
- compose: Generate new content
Control Flow
- branch: Conditional execution paths
- loop: Iterate over items or conditions
- parallel: Execute multiple steps simultaneously
- wait_for_input: Pause for user input
Utility Actions
- transform: Convert data formats
- checkpoint: Save workflow state
- notify: Send updates
- assert: Ensure conditions are met
- retry: Attempt previous step again
🛠️ Available Tools
Workflow Management
-
create_workflow - Create a new workflow
{ "workflow": { "name": "My Workflow", "description": "What it does", "goal": "Desired outcome", "steps": [...] } } -
list_workflows - List all workflows with filtering
{ "filter": { "tags": ["automation"], "name_contains": "review" }, "sort": { "field": "created_at", "order": "desc" } } -
get_workflow - Retrieve a specific workflow
{ "id": "workflow-uuid" } -
update_workflow - Modify existing workflow
{ "id": "workflow-uuid", "updates": { "description": "Updated description" }, "increment_version": true } -
delete_workflow - Soft delete (recoverable)
{ "id": "workflow-uuid" } -
start_workflow - Start a workflow execution session
{ "id": "workflow-uuid", "inputs": { "param1": "value1" } }Returns execution instructions for the first step and an execution_id.
-
run_workflow_step - Execute the next step in the workflow
{ "execution_id": "execution-uuid", "step_result": "result from previous step", "next_step_needed": true }Call this after completing each step to proceed through the workflow.
-
get_workflow_versions - List all available versions of a workflow
{ "workflow_id": "workflow-uuid" }Returns list of all saved versions for version history tracking.
-
rollback_workflow - Rollback a workflow to a previous version
{ "workflow_id": "workflow-uuid", "target_version": "1.0.0", "reason": "Reverting breaking changes" }Restores a previous version as the active workflow.
🔄 Step-by-Step Execution
The workflow system supports interactive, step-by-step execution similar to the sequential thinking tool:
- Start a workflow with
start_workflow- returns the first step instructions - Execute the step following the provided instructions
- Continue to next step with
run_workflow_step, passing:- The
execution_idfrom start_workflow - Any
step_resultfrom the current step next_step_needed: trueto continue (or false to end early)
- The
- Repeat until the workflow completes
Each step provides:
- Clear instructions for what to do
- Current variable state
- Expected output format
- Next step guidance
Template Variables
The workflow system supports template variable substitution using {{variable}} syntax:
- In parameters:
"path": "output_{{format}}.txt"→"path": "output_csv.txt" - In descriptions:
"Processing {{count}} records"→"Processing 100 records" - In prompts:
"Enter value for {{field}}"→"Enter value for email" - In transformations: Variables are automatically substituted
Template variables are resolved from the current workflow session variables, including:
- Initial inputs provided to
start_workflow - Results saved from previous steps via
save_result_as - Any variables set during workflow execution
🎯 Dependency Management & Performance Optimization
The workflow system includes advanced features to minimize token usage and improve performance for complex workflows:
Dependency-Based Variable Filtering
Control which variables are visible to each step to dramatically reduce context size:
{
"name": "Optimized Workflow",
"strict_dependencies": true, // Enable strict mode
"steps": [
{
"id": 1,
"action": "tool_call",
"tool_name": "read_large_file",
"save_result_as": "large_data"
},
{
"id": 2,
"action": "analyze",
"input_from": ["large_data"],
"save_result_as": "summary",
"dependencies": [] // In strict mode, sees NO previous variables
},
{
"id": 3,
"action": "compose",
"dependencies": [2], // Only sees 'summary' from step 2
"save_result_as": "report"
},
{
"id": 4,
"action": "validate",
"show_all_variables": true, // Override to see everything
"save_result_as": "validation"
}
]
}
Workflow-Level Settings
strict_dependencies(boolean, default: false)false: Steps without dependencies see all variables (backward compatible)true: Steps without dependencies see NO variables (must explicitly declare)
Step-Level Settings
-
dependencies(array of step IDs)- Lists which previous steps' outputs this step needs
- Step only sees outputs from listed steps plus workflow inputs
- Empty array in strict mode means NO variables visible
-
show_all_variables(boolean)- Override for specific steps that need full visibility
- Useful for validation or debugging steps
Performance Features
-
Differential State Updates: Only shows variables that changed
+ variable_name: Newly added variables~ variable_name: Modified variables- Unchanged variables are not displayed
-
Progressive Step Loading: Only shows next 3 upcoming steps
- Reduces context for long workflows
- Shows "... and X more steps" for remaining
-
Selective Variable Display: Based on dependencies
- Dramatically reduces tokens for workflows with verbose outputs
- Maintains full state internally for branching/retry
Best Practices for Token Optimization
- Use
strict_dependencies: truefor workflows with large intermediate outputs - Explicitly declare dependencies to minimize variable visibility
- Place verbose outputs early in the workflow and filter them out in later steps
- Use meaningful variable names to make dependencies clear
- Group related steps to minimize cross-dependencies
Example: Data Processing with Filtering
{
"name": "Large Data Processing",
"strict_dependencies": true,
"inputs": {
"file_path": { "type": "string", "required": true }
},
"steps": [
{
"id": 1,
"action": "tool_call",
"tool_name": "read_csv",
"parameters": { "path": "{{file_path}}" },
"save_result_as": "raw_data"
},
{
"id": 2,
"action": "transform",
"transformation": "Extract key metrics only",
"dependencies": [1], // Only sees raw_data
"save_result_as": "metrics"
},
{
"id": 3,
"action": "analyze",
"criteria": "Identify trends and anomalies",
"dependencies": [2], // Only sees metrics, not raw_data
"save_result_as": "analysis"
},
{
"id": 4,
"action": "compose",
"criteria": "Create executive summary",
"dependencies": [2, 3], // Sees metrics and analysis only
"save_result_as": "report"
}
]
}
In this example:
- Step 2 processes large raw data but only outputs key metrics
- Step 3 analyzes metrics without seeing the large raw data
- Step 4 creates a report from metrics and analysis only
- Token usage is minimized by filtering out verbose intermediate data
📚 Example Workflows
Code Review Workflow
Analyzes code quality, identifies issues, and provides improvement suggestions.
- Sample data:
/workflows/examples/sample-data/sample-code-for-review.js
Data Processing Pipeline
ETL workflow with validation, quality checks, and conditional branching.
- Sample data:
/workflows/examples/sample-data/sample-data.csv
Research Assistant
Gathers information, validates sources, and produces comprehensive reports.
Simple File Processor
Basic example showing file operations, branching, and transformations.
See the /workflows/examples directory for complete workflow definitions.
📁 Manual Workflow Import
You can manually add workflows by placing JSON files in the imports directory:
- Navigate to
~/.workflows-mcp/imports/ - Place your workflow JSON files there (any filename ending in
.json) - Start or restart the MCP server
- The workflows will be automatically imported with:
- A new UUID assigned if missing or invalid
- Metadata created if not present
- Original files moved to
imports/processed/after successful import
Example workflow file structure:
{
"name": "My Custom Workflow",
"description": "A manually created workflow",
"goal": "Accomplish something specific",
"version": "1.0.0",
"steps": [
{
"id": 1,
"action": "tool_call",
"description": "First step",
"tool_name": "example_tool",
"parameters": {}
}
]
}
🏗️ Architecture
workflows-mcp/
├── src/
│ ├── types/ # TypeScript interfaces and schemas
│ ├── services/ # Core services (storage, validation)
│ ├── utils/ # Utility functions
│ └── index.ts # MCP server implementation
├── workflows/
│ └── examples/ # Example workflows
│ └── sample-data/ # Sample data files for testing
└── tests/ # Test suite
🧪 Development
# Install dependencies
npm install
# Run in development mode
npm run dev
# Build for production
npm run build
# Run tests
npm test
# Type checking
npm run typecheck
📝 Changelog
v0.3.3 (Latest)
- ⚡ Added dependency-based variable filtering for token optimization
- ✨ Added
strict_dependenciesworkflow flag for explicit variable control - ✨ Added
dependenciesarray to steps for selective variable visibility - ✨ Added
show_all_variablesstep override for full visibility when needed - 🎯 Implemented differential state updates (shows only changed variables)
- 📊 Added progressive step loading (shows only next 3 steps)
- 🐛 Fixed UUID validation error in update_workflow tool
- 📝 Added explicit instructions to prevent commentary during workflow execution
v0.3.0
- ✨ Added workflow versioning with automatic version history
- ✨ Added
get_workflow_versionstool to list all versions - ✨ Added
rollback_workflowtool to restore previous versions - 📁 Version history stored in
~/.workflows-mcp/versions/
v0.2.1
- ✨ Added template variable resolution (
{{variable}}syntax) - ✨ Fixed branching logic to properly handle conditional steps
- ✨ Enhanced create_workflow tool with comprehensive embedded documentation
- 🐛 Fixed ES module import issues
- 📁 Improved file organization with sample-data folder
v0.2.0
- ✨ Implemented step-by-step workflow execution
- ✨ Added
start_workflowandrun_workflow_steptools - ✨ Session management for workflow state
- 🔄 Replaced
run_workflowwith interactive execution
v0.1.0
- 🎉 Initial release
- ✨ Core workflow engine
- ✨ 16 action types
- ✨ Import/export functionality
- ✨ Example workflows
🔮 Roadmap
- Core workflow engine
- Basic action types
- Workflow validation
- Example workflows
- Step-by-step execution
- Variable interpolation
- Branching logic
- Import/export system
- Advanced error handling and retry logic
- Loop and parallel execution
- Workflow marketplace
- Visual workflow builder
- Performance optimizations
- Workflow versioning and rollback
🤝 Contributing
We welcome contributions! Please see our Contributing Guidelines for details.
📄 License
This project is licensed under the MIT License - see the LICENSE file for details.
🙏 Acknowledgments
Built on the Model Context Protocol specification by Anthropic.
README mirrored from the source repository 3 months ago. The original is authoritative.