agentic-workflow-orchestrator
A command-line interface (CLI) utility designed for structured lifecycle management of software engineering efforts. It facilitates project decomposition, progress visualization, and dynamic adaptation to scope changes. Features deep integration with AI-enabled IDE environments (like Cursor) via the Model Context Protocol (MCP) for amplified developer throughput.
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FutureAtoms
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Agentic Workflow Orchestrator (AWO)
Creator: Abhilash Chadhar (FutureAtoms) Source Code: agentic-control-framework
An AI-centric coordination substrate (CLI + MCP endpoint) providing over eighty utilities for sophisticated context manipulation—covering retrieval, code modification, runtime execution, persistent state maintenance, and browser interaction. Optimized for consumption by Claude Code, Cursor, Codex, and VS Code extensions operating under the MCP framework. This documentation reflects the current, validated state of the codebase.
- CLI Entry Point:
bin/acf - MCP Communication Server:
bin/agentic-control-framework-mcp→ dispatched fromsrc/mcp/server.js - Client Configuration Templates:
config/examples/ - Testing Suites:
npm run test:cli,npm test
Core Capabilities
What the package provides:
- Comprehensive work item supervisor supporting granular control over priorities, dependencies, sub-components, and standardized templates.
- A robust command-line interface (
bin/acf). - A resilient MCP service layer (implementing JSON-RPC over stdio) validated against Claude Desktop/Code, Cursor, and Codex clients.
Key Operational Strengths: - 🔧 Extensive Toolset: Access to 80+ discrete utilities spanning task logistics, filesystem access, terminal control, web interface automation, and native system interaction (AppleScript). - 🎯 Versatile Deployment: Supports CLI, Local MCP, and Cloud MCP modes for maximum operational adaptability. - 🔗 Broad Interoperability: Seamless functionality with Claude Code, Cursor, Claude Desktop, VS Code, and any client adhering to the MCP specification. - ☁️ Cloud Native Support: Configuration streamlined for deployment on GCP, Railway, and Fly.io, including auto-scaling preparation. - 🚀 Quality Assurance: Backed by an exhaustive automated test matrix confirming core functionality. - ⚡ Latency Profile: Achieves fast interaction times, typically between 200 and 1000 milliseconds, with high stability. - 🛡️ Security Enforced: Incorporates mandatory filesystem sandboxing, strict permission modeling, and secure default settings. - 📋 Protocol Adherence: Fully compliant with MCP specification dated 2025-03-26, featuring proper tool annotations, descriptive titles, and capability declaration.
Resolving Context Engineering Challenges
AWO transforms the inherently complex, multi-artifact, iterative nature of software development into discrete, addressable 'contextual units.' These units are readily requested, refined, and acted upon by Large Language Models. This is achieved by synthesizing a task dependency graph, exposing rich context APIs, providing granular retrieval/editing instruments, and enforcing operational guardrails, all accessible via CLI or MCP.
- Task Graph as Definitive Record
- Every atomic work unit (task/subtask) maintains an identifier, execution status, a quantifiable priority score (1–1000), antecedent dependencies, associated file metadata, chronological activity records, and precise timestamps.
-
The built-in priority mechanism incorporates temporal decay factors and effort estimation to ensure the 'next action' is always dynamically relevant.
-
Dynamic, On-Demand Context Surfaces
getContextutility returns the precise context block for a task, including file metadata and the complete history log.generateTaskFilesprocedure materializes individual Markdown files per task (located intasks/), complemented bytasks-table.mdfor a holistic project overview.-
The CLI's
context <id>command renders a human-readable summary suitable for both human review and LLM consumption. -
Retrieval and Editing Utilities (for Context Materialization and Application)
- Retrieval: Tools like
search_code,tree,list_directory,get_file_info,read_file/read_multiple_files, andread_url. - Modification:
edit_blockensures surgical replacements by demanding explicit old/new blocks, drastically reducing unintended state corruption. -
Validation: Terminal interfaces (
execute_command,list_processes, session management) allow verification of context assumptions (e.g., running tests or builds). -
Synchronization and Temporal Freshness
- A file watcher maintains consistency between
tasks.jsonand per-task artifacts; change detection is debounced;tasks-table.mdis kept current. -
Guardrails: Filesystem scope is strictly limited via
allowedDirectoriesandreadonlyMode. -
Planning from Specification Documents (Optional)
- Utilities such as
parsePrd,expandTask, andreviseTasksutilize generative models (e.g., Gemini) to translate Product Requirement Documents or change requests into structured work items, which are then integrated into the traceable task graph.
Collectively, this architecture establishes a predictable 'context feedback loop': strategize → fetch context → modify/validate → persist state. Every step is tool-addressable, enabling reliable control by MCP clients (Claude Code, Cursor, Codex, VS Code).
End-to-End Context Operation Recipes
- Initiating from a PRD
-
tools/call: parsePrd { filePath }initiates task creation with calculated priorities/dependencies → subsequently runninggenerateTaskFilesfor stakeholder sign-off. -
Focusing the Agent on the Immediate Next Step
tools/call: getNextTaskretrieves the highest-ranking actionable item considering constraints.-
tools/call: getContext { id }fetches the task metadata; followed by necessary artifact retrieval likeread_file/search_code. -
Executing Safe, Atomic Code Edits
- Retrieval: Employ
search_codeto pinpoint the exact code section; confirm content viaread_file. - Application: Use
edit_block { file_path, old_string, new_string, normalize_whitespace }. -
Verification: Confirm stability with
execute_command { command: "npm test" }or relevant test suites. -
Maintaining Current Context State
- Activate monitoring with
start_file_watcher→ apply modifications to files or task definitions → check status withfile_watcher_status→ deactivate monitoring viastop_file_watcher.
Durable State Management (Activity Logs in tasks.json)
AWO preserves a durable, searchable history of agentic (and human) actions, including rationale. This persistent memory resides in .acf/tasks.json and associated per-task files:
- Data Persistence Details
- For every unit of work:
createdAt,updatedAt, and anactivityLog[]array containing timestamped annotations. - Any modification to a task's attributes (status, title, priority, dependencies, associated files) results in a new log entry and updates the
updatedAttimestamp. -
AI-driven workflows (
parsePrd, etc.) explicitly record their execution narrative. -
LLM-Driven Memory Logging
- CLI: State changes include an optional
--message "..."flag to append a note to the activity log.- Example:
acf status 12 inprogress --message "Initiated implementation phase" - Example:
acf update 12 --priority 750 --message "Escalated priority based on review feedback"
- Example:
-
MCP: The
messagefield is included in tool invocations targeting state modification.tools/call { name: "updateStatus", arguments: { id: "12", newStatus: "done", message: "Verification tests passed; ready for commit" } }tools/call { name: "updateTask", arguments: { id: "12", priority: 820, message: "Priority raised following stakeholder consensus" } }
-
Memory Consumption Methods
acf context <id>(CLI) outputs a rich, narrative summary including recentactivityLogsegments.tools/call: getContext { id }(MCP) returns the raw structured data, perfect for prompt inclusion.generateTaskFilesgenerates Markdown snapshots;tasks-table.mdoffers a live, synchronized overview of.acf/tasks.jsonstate.
Quick Initiation Guide
- Prerequisites
- Runtime Environment: Node.js (version 18 or newer)
-
macOS Dependency (Optional): Required for AppleScript utilities. Playwright browser runtimes must be installed:
npx playwright install. -
Installation Steps
- Navigate to the project root:
cd agentic-control-framework -
Install dependencies:
npm ci -
CLI Operation (Local)
- Initialize new context:
./bin/acf init --project-name "PilotRun" --project-description "Initial setup test" - Add first unit of work:
./bin/acf add -t "Define core services" -p high -
Review state:
./bin/acf list --format human -
MCP Server Execution (For IDEs)
- Start the stdio server:
node ./bin/agentic-control-framework-mcp --workspaceRoot $(pwd) - Client configuration: Utilize the provided samples within
config/examples/for connecting Claude Code, Cursor, and Codex clients.
Documentation Index
- Main Overview:
docs/README.md - Repository Layout:
docs/PROJECT-STRUCTURE.md - System Blueprint:
docs/architecture/overview.md - MCP Communication Protocol:
docs/architecture/mcp-integration.md
Implemented MCP Utilities (Tool Registry)
Tool Groupings Summary
mindmap
root((AWO Tools Set<br/>80+ Total))
Core Orchestration
Task Logic
listTasks
addTask
updateStatus
getNextTask
Priority Mechanics
recalculatePriorities
getPriorityStatistics
bumpTaskPriority
prioritizeTask
State Sync
initializeFileWatcher
stopFileWatcher
forceSyncTaskFiles
Templates
getPriorityTemplates
addTaskWithTemplate
File System Interop
CRUD
read_file
write_file
copy_file
delete_file
Navigation
list_directory
create_directory
tree
search_files
Runtime Execution
Command Invocation
execute_command
read_output
force_terminate
Process Supervision
list_processes
kill_process
Web Interface Control (Playwright)
Traversal
browser_navigate
browser_navigate_back
browser_close
Interaction Layer
browser_click
browser_type
browser_hover
browser_drag
Data Capture
browser_take_screenshot
browser_pdf_save
browser_snapshot
Session Management
browser_tab_list
browser_tab_new
browser_tab_close
Code Manipulation & Discovery
search_code
edit_block
System Utilities
System Calls
applescript_execute
Settings
get_config
set_config_value
Core administrative utilities include: initProject, addTask, addSubtask, listTasks, updateTask, updateStatus, removeTask, getNextTask, generateTaskFiles, recalculatePriorities, and various priority analysis functions.
Auxiliary functions include standard file I/O (read_file, write_file) and command execution stubs.
Operational Configuration Parameters
- Essential Environment Variables
WORKSPACE_ROOT: Default directory context for CLI/MCP operations.ALLOWED_DIRS: Supplementary directories permitted for filesystem interaction (colon-separated).READONLY_MODE: Setting totruestrictly prohibits all write operations.-
ACF_PATH: Override location for the AWO installation root. -
Feature Toggles (Optional)
GEMINI_API_KEY: Activates generative planning tools (parsePrd,expandTask,reviseTasks).ACF_SKIP_POSTINSTALL=1: Bypasses post-installation setup routines.ACF_SKIP_PLAYWRIGHT=1: Prevents downloading large browser binaries during setup.ACF_INSTALL_SHARP=1orACF_INSTALL_ALL=1: Enables optionalsharplibrary dependency.ACF_ENABLE_BROWSER_TOOLS=1: Permits execution of Playwright automation routines (macOS default).ACF_ENABLE_APPLESCRIPT=1: Permits execution of native AppleScript operations (macOS only).
Security Posture and Safeguards
- Filesystem operations are strictly bounded by the
allowedDirectorieslist and thereadonlyModeflag. - External resource fetching (
read_url) requires explicit invocation; modification tools likeedit_blockmandate providing both the original and target content to prevent accidental corruption. - Terminal invocation incorporates blacklists for dangerous commands, enforced timeouts, and session visibility/termination controls.
High-Level CLI Command Set
init, add, list, add-subtask, status, next, update, remove, context, update-subtask, bump, defer, prioritize, deprioritize, recalculate-priorities, priority-stats, dependency-analysis, start-file-watcher, stop-file-watcher, file-watcher-status, force-sync, list-templates, suggest-template, calculate-priority, add-with-template
Tool Categories (Detailed Counts)
- Terminal Interfaces (6) ✅
- Web Automation (25) ✅
- Discovery & Editing (2) ✅
- macOS Scripting (1) ✅
- Configuration Management (2) ✅
Repository Layout
The structure emphasizes modularity and separation of concerns:
agentic-control-framework/
├── 📁 bin/ # Executable scripts (CLI, MCP Server entry)
├── 📁 src/ # Primary implementation logic and tool handlers
├── 📁 docs/ # Exhaustive documentation resources
├── 📁 test/ # Testing frameworks and execution suites
├── 📁 config/ # Configuration blueprints and client examples
├── 📁 scripts/ # Maintenance, deployment, and utility scripts
├── 📁 deployment/ # Infrastructure-as-Code definitions (Cloud)
├── 📁 tasks/ # Runtime storage for project work items (.acf/tasks.json)
├── 📁 templates/ # Blueprints for standardized task creation
├── 📁 public/ # Static client assets
└── 📁 data/ # Persistent data storage
Operational Status Dashboard
| Metric | State | Commentary |
|---|---|---|
| CLI Interface | ✅ Fully Functional | All core task logistics and utility calls confirmed operational. |
| Local MCP Endpoint | ✅ Fully Functional | All core utilities successfully invoked via stdio protocol. |
| Cloud MCP Endpoint | ✅ Fully Functional | HTTP/SSE proxy integration and remote execution validated. |
| IDE Bindings | ✅ Confirmed Compatible | Tested with Cursor, Claude Desktop, Claude Code, and standard VS Code extensions. |
| Core Task Tools | ✅ 25/25 Active | Task structure, priority engine, and context generation components verified. |
| Filesystem Utilities | ✅ 14/14 Active | File manipulation, directory browsing, and content search functional. |
| Browser Automation | ✅ 25/25 Active | Full Playwright suite coverage, including capture mechanisms. |
| Terminal Executors | ✅ 6/6 Active | Command execution and process supervision confirmed. |
| Code Search/Edit | ✅ 3/3 Active | Code discovery (ripgrep) and surgical text replacement validated. |
| System Adapters | ✅ 7/7 Active | AppleScript bridge and configuration setters verified. |
| MCP Protocol | ✅ Fully Supported | Implements JSON-RPC 2.0; defaults to 2025-03-26 standard; supports 2024-11-05 fallback. |
System health check confirms 100% success rate across the entire validation suite.
