Intelligent Artifact Generation Engine (v1.7.3) - AI-Driven Backlog Synthesis

Project Artifact Generator MCP instantly constructs detailed agile roadmaps (Epics, Features, User Stories, Minimum Viable Product components) or isolated feature sets from plain text requirements, seamlessly deployable in Windsurf, Cascade, or Cursor environments without requiring specialized technical expertise.

Revision 1.7.3 Highlights: - MCP Mode Fix for generateFeature: Fortified extraction logic for granular user narratives. - Enhanced Structuring Protocol (RULE 3): Ensured consistent creation hierarchy for artifact directories (epics/features/stories). - Windows Compatibility Patch: Standardized I/O stream handling (stderr/stdout) within MCP execution context. - Verbose Diagnostics: Implemented richer logging for streamlined issue resolution. - Source Code Organization: Refined placement of testing and transient files. - Documentation Updates: Comprehensive operational manuals for Windsurf, Claude, and Cursor integration. - Consult CHANGELOG.md for comprehensive modifications.

Prior Revision (v1.7.1): - Server Architecture Documentation Overhaul: Complete overhaul of MCP server documentation, incorporating Mermaid sequence diagrams. - Reduced Cognitive Load via Refactoring: Significant code modernization across core modules (JSON parsing, routing). - Improved System Resilience: Advanced error interception mechanisms and optimized end-to-end verification procedures. - Refer to CHANGELOG.md for specifics.

❌ Manual Artifact Creation Pain Points

Developing agile artifacts manually incurs significant overhead and increases systemic inconsistency:

• ❌ Consumption of extensive time crafting acceptance criteria, narratives, and sub-tasks.
• ❌ Variability in structural formatting and project governance adherence.
• ❌ Lack of embedded directive guidance for AI code generation agents.
• ❌ Arbitrary prioritization lacking strategic scaffolding.

✅ Benefits of the Artifact Generator MCP

Unified Error Reporting

• All exceptions originating from generateBacklog and generateBacklogDirect are standardized via handleBacklogError, guaranteeing JSON conformity for auditing purposes.
• Standard error payload format: { success: false, error: { message: ... } }

AI-driven generation delivers polished, logically organized agile frameworks in moments:

• ✅ Comprehensive Artifact Nesting: Full structure including primary Epics, Features, User Stories, and unassigned items.
• ✅ ML-Tuned Directives: Implementation guidance embedded within annotations for step-by-step AI execution.
• ✅ Velocity Monitoring Hooks: Integrated task checklists and prerequisites mapping.
• ✅ Designated Output Zoning: Persistence within a controlled .agile-planner-backlog structure.
• ✅ Intelligent Association: Automatic linkage of functional features to appropriate parent epics.

📑 Knowledge Base

This repository's documentation structure has been optimized for rapid access:

User Manuals

• MCP Deployment Guide - Integrating with Claude, Cursor, and Windsurf IDE environments.
• Best Practices Guide - Detailed operational procedures.
• Version Upgrade Handbook - Guidance for transitioning from legacy releases.

Engineering Documentation

• Contribution Guidelines - Instructions for developers.
• Protocol Specification - Formal definition of the MCP interface.
• Known Impediments Log - Current limitations and technical debt register.
• Code Modernization Strategy - Detailed plan for code evolution.
• Test Suite Remediation Plan - Strategy for test infrastructure improvement.
• Future Iterations Timeline - Roadmap for upcoming capabilities.
• System Architecture Overview - Complete server topology.
• Markdown Formatting Pipeline - Architecture of the document creator.
• Output Data Schema - Specification of the resulting JSON artifact schema.

Utility Functions

• createApiMessages(project) - Constructs the paired system/user prompt payload for the generative model. The project input accepts either a string format ("Title: details") or an object ({ name, description }).

TDD Enforcement Note: Error handling assertions must rigorously validate the uniform { success: false, error: { message: ... } } structure. Any deviation in this format necessitates corresponding updates to integration suite tests.

Design Documentation

• Conceptual Design - Overarching project conceptualization.
• Generated Artifact Format - Specification of the resultant artifact structure.
• Artifact Validation Flowchart - Diagram illustrating validation sequence.
• Cross-Model Compatibility - Details on supporting diverse Large Language Models.

🚦 Provisioning in Windsurf / Cascade / Cursor

To activate this MCP server, collaborate with your administrator to integrate it into the workspace configuration: 1. Duplicate .env.example to .env and input your requisite API credentials (OPENAI_API_KEY or GROQ_API_KEY).

Deployment Method A: Local Node Execution

{ "mcpServers": { "artifact-generator": { "command": "node", "args": ["D:/path/to/agile-planner/server/index.js"], "env": { "MCP_EXECUTION": "true", "OPENAI_API_KEY": "sk-..." } } } }

Deployment Method B: Utilizing the NPM Registry Package

{ "mcpServers": { "artifact-generator": { "command": "npx", "args": ["agile-planner-mcp-server"], "env": { "MCP_EXECUTION": "true", "OPENAI_API_KEY": "sk-..." } } } }

🧠 Operational Workflow

1. Supply Project Blueprint using natural language, providing maximum contextual detail.

txt Enterprise task coordination platform targeting integration with Slack APIs, cross-platform mobile access, and strict adherence to international data privacy mandates.

1. Artifact Generator MCP Ingestion Pipeline subjects the input to rigorous validation:
2. 🤖 Orchestrates OpenAI or Groq inference engines to blueprint the required artifact hierarchy.
3. 🧪 Validates the output structure against a comprehensive JSON serialization contract.
4. 🔍 Enriches features with acceptance criteria and actionable tasks.
5. 📝 Systematically maps narratives to functional epics and feature groupings.

6. 🏗️ Instantiates a complete organizational directory tree populated with Markdown documentation.

7. Receive Fully Conformed Agile Artifact Set within seconds:

Generated Directory Map

.agile-planner-backlog/ ├── epics/ │ └── [epic-slug]/ │ ├── epic.md │ └── features/ │ └── [feature-slug]/ │ ├── feature.md │ └── user-stories/ │ ├── [story-1].md │ └── [story-2].md ├── orphan-stories/ │ ├── [story-orpheline-1].md │ └── [story-orpheline-2].md └── backlog.json

Schema Note : The planning/mvp and planning/iterations subdirectories are deprecated. All user narratives are now consolidated under the appropriate epic/feature structure or within orphan-stories if orphaned. The top-level backlog.json omits obsolete mvp and iterations sections.

All resulting files contain machine-readable directives to guide subsequent implementation phases. Refer to the samples directory for specimen outputs.

Supported Interface Calls

The Artifact Generator supports the following invocation methods:

Generate Entire Product Roadmap

javascript // Windsurf or Cascade Context mcp0_generateBacklog({ projectName: "Product Alpha", projectDescription: "A rich narrative detailing the entire system scope...", outputPath: "optional/custom/path" })

// CLI Execution npx agile-planner-mcp-server backlog "Product Alpha" "A rich narrative detailing the entire system scope..."

Synthesize Discrete Feature Set

javascript // Windsurf or Cascade Context mcp0_generateFeature({ featureDescription: "A focused description of the specific capability required", storyCount: 3, // Optional: Desired narrative count (minimum: 3) businessValue: "High", // Optional: Perceived return on investment iterationName: "iteration-2", // Optional: Target sprint assignment (default: 'next') epicName: "Associated Epics Name", // Optional: Anchor epic or allow auto-discovery outputPath: "optional/custom/path" // Optional: Alternative output location })

// CLI Execution npx agile-planner-mcp-server feature "A focused description of the specific capability required"

🔄 Environment Configuration Variables

Parameter	Purpose	Default Value
MCP_EXECUTION	Mandatory Flag - Must be set to "true" to enable MCP processing	-
OPENAI_API_KEY	Credential for accessing OpenAI services	-
GROQ_API_KEY	Alternate credential for Groq inference engine	-
DEBUG	Activates verbose operational logging	false
TEST_MODE	Enables stubbed generation for validation runs	false
AGILE_PLANNER_OUTPUT_ROOT	Root location for all generated artifacts	Current Working Directory

📜 Legal Terms

This system is distributed under the terms of the MIT License, supplemented by the Commons Clause. Full text is available in the LICENSE file.

👥 Operational Support

For technical assistance, please file an issue on the GitHub repository or engage your platform support channels (Windsurf/Cascade/Cursor).

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☕️ Support Development Efforts

Your patronage via BuyMeACoffee directly fuels ongoing enhancement.

🚀 Obtain Windsurf Access

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