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0.8.3

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accordo-workflow-mcp

Accordo MCP server with dynamic YAML workflow support

Published20 Jun 2025
Direct dependencies12
Transitive dependenciesNot calculated

README

Version 0.8.3 documentation
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Accordo MCP Server

PyPI - Version GitHub Actions Workflow Status GitHub Release Date Quality Gate Status

A powerful MCP (Model Context Protocol) server that provides dynamic YAML-driven workflow guidance for AI coding agents. Features structured development workflows with progression control and decision points.

What This Does

This server guides AI agents through structured, schema-driven development workflows:

  • 📋 Dynamic YAML Workflows: Custom workflows defined in YAML with schema-driven execution
  • 🔍 Discovery-First: Automatically discovers and selects appropriate workflows based on task
  • ⚡ Real-time State: Live workflow state tracking with comprehensive session management
  • 🎯 Mandatory Guidance: Authoritative phase-by-phase instructions agents must follow
  • 🤖 Agent-Generated Workflows: Unique capability for agents to create custom YAML workflows on-the-fly

Two Workflow Approaches

Built-in Workflow Discovery Process

  1. Automatic Discovery - System scans .accordo/workflows/ for available YAML workflows
  2. Intelligent Matching - Analyzes task description against workflow capabilities and goals
  3. Workflow Selection - Agent chooses the most appropriate workflow from discovered options
  4. Immediate Execution - Selected workflow starts with full state management and progression control

This provides instant access to proven workflows for common development patterns - coding, documentation, debugging, and more!

Agent Workflow Generation Process

  1. Analyze Task Requirements - Agent understands specific needs
  2. Get Creation Guidance - Comprehensive templates and best practices provided
  3. Generate Custom YAML - Agent creates workflow tailored to exact requirements
  4. Start Execution - Custom workflow runs with full state management

This enables agents to create workflows for any domain - web development, data science, DevOps, research, documentation, testing, and more!

Quick Start

Installing accordo CLI

The accordo CLI provides easy configuration and management of MCP servers. Install it directly with:

# Download and run the installation script
curl -fsSL https://raw.githubusercontent.com/AndurilCode/accordo/refs/heads/main/install.sh | bash

The installer will:

  • ✅ Detect your environment (virtual env, available tools)
  • 🌍 Global installation (recommended): Uses pipx for system-wide access
  • 📦 Virtual environment: Uses uv or pip if you're in a venv
  • 🔧 Auto-setup: Handles dependencies and PATH configuration

CLI Usage

# Configure MCP servers interactively
accordo configure

# Quick setup for specific platforms
accordo configure -p cursor -y
accordo configure -p claude-code -y

# Deploy workflow guidelines to AI assistants
accordo bootstrap-rules              # All assistants
accordo bootstrap-rules cursor       # Cursor only
accordo bootstrap-rules --force all  # Overwrite existing

# List supported platforms and manage servers
accordo list-platforms
accordo list-servers -p cursor
accordo validate -p cursor

# Get help
accordo --help

Manual MCP Configuration

Alternatively, install uv for Python package management and configure your MCP client manually: For Cursor (.cursor/mcp.json):

{
  "mcpServers": {
    "accordo": {
      "command": "uvx",
      "args": ["accordo-workflow-mcp"]
    }
  }
}

Or use the following link to install the MCP server (Cursor Installed):

Install MCP Server

Getting Help

📚 Documentation

🎯 Examples

License

This project is licensed under the MIT License - see the LICENSE file for details.

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Declared dependencies 12

Native requirements
12 direct targetsNot calculated transitive count
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Distribution files

2 collected
accordo_workflow_mcp-0.8.3-py3-none-any.whl

bdist_wheel · 142.03 KB · Python py3

Source file
accordo_workflow_mcp-0.8.3.tar.gz

sdist · 133.74 KB · Python source

Source file

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package_version:5ac19c846dcaa5ce980286f2d16bc57efa196332ea884aea2f9bdb1c3bd9bfbb

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