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PRD-MCP-Server-Artifact

A dedicated Model Context Protocol (MCP) engine engineered to synthesize comprehensive, standards-compliant Product Requirements Documentation (PRD) leveraging a repository of adaptable specification blueprints.

Author

PRD-MCP-Server-Artifact logo

Saml1211

MIT License

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GitHub GitHub Stars 26
NPM Weekly Downloads 0
Tools 1
Last Updated 2026-02-19

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prdsprddocumentationdocuments prdsrequirements documentssaml1211 prd

Artifact for PRD Generation via MCP Server

Build Status NPM Version License: MIT GitHub Issues Tracked

This specialized service, operating under the Model Context Protocol (MCP), is built to facilitate the automated creation of detailed Product Requirement Specifications. It allows connected AI agents to output high-fidelity documentation adhering to established industry benchmarks, utilizing a suite of pre-defined, configurable schemas.


Initial Access

Execution via NPX (Recommended Method): sh npx -y prd-creator-mcp

Containerized Deployment: sh docker pull saml1211/prd-creator-mcp docker run -i --rm saml1211/prd-creator-mcp

Credential Setup: 1. Duplicate the example environment file (.env.example) to .env and populate necessary credentials and model endpoints. 2. Alternatively, adjust service provider credentials dynamically during runtime via the update_provider_config MCP endpoint.

Assistance Retrieval: sh npx prd-creator-mcp --help

Core Capabilities

  • Specification Drafting: Constructing end-to-end PRDs based on initial product concepts, user narratives, and functional mandates.
  • Cognitive Augmentation: Leveraging advanced Artificial Intelligence models for superior quality document assembly.
  • Multi-Source Connectivity: Support for major LLM backends, including OpenAI, Google Gemini, Anthropic Claude, and self-hosted deployments.
  • Endpoint Customization: Granular control over parameters for each invocation of a generation service.
  • Resilience: Automatic failover to static, template-driven output when generative services encounter unavailability.
  • Integrity Verification: A built-in mechanism to audit finalized documentation against established quality criteria and configurable rule sets.
  • Schema Repository: Access to a comprehensive collection of reusable documentation structures for various product domains.
  • MCP Compliance: Full adherence to the Model Context Protocol specification for straightforward integration with client frameworks.

Setup Procedure

Prerequisites

  • Runtime Environment: Node.js version 16 or newer
  • Package Manager: npm or yarn

Installation from Source Code

  1. Clone the repository location: bash git clone https://github.com/Saml1211/prd-mcp-server.git cd prd-mcp-server

  2. Acquire necessary dependencies: bash npm install

  3. Compile the source files: bash npm run build

  4. Initiate local execution: bash npm start

  5. For development with live code reloading: bash npm run dev

Interface Specification

The PRD Creator MCP Server exposes the following operational interfaces (tools):

generate_prd

Orchestrates the creation of a full PRD, defaulting to AI synthesis or falling back to schema rendering.

Input Arguments (Parameters): - productName: Nomenclature of the resulting product. - productDescription: Narrative summary of the offering. - targetAudience: Profile of the intended end-user base. - coreFeatures: Enumerated list of primary functionalities. - constraints (optional): Any limiting factors or boundary conditions. - templateName (optional): Identifier for the structural blueprint to employ (default: "standard"). - providerId (optional): Identifier for the desired generation source (e.g., openai, gemini, template). - additionalContext (optional): Supplementary directives provided to the generative model. - providerOptions (optional): Model-specific configuration parameters (e.g., tuning controls).

Demonstration Payload: javascript { "productName": "TaskMaster Pro", "productDescription": "A task management application that helps users organize and prioritize their work efficiently.", "targetAudience": "Busy professionals and teams who need to manage multiple projects and deadlines.", "coreFeatures": [ "Task creation and management", "Priority setting", "Due date tracking", "Team collaboration" ], "constraints": [ "Must work offline", "Must support mobile and desktop platforms" ], "templateName": "comprehensive", "providerId": "openai", "additionalContext": "Focus on enterprise features and security", "providerOptions": { "temperature": 0.5, "maxTokens": 4000 } }

validate_prd

Assesses a provided documentation artifact against defined quality benchmarks.

Input Arguments: - prdContent: The raw string content of the document requiring review. - validationRules (optional): A subset of identifiers specifying which conformance checks to execute.

Demonstration Payload: javascript { "prdContent": "# My Product\n\n## Introduction\n...", "validationRules": ["has-introduction", "minimum-length"] }

list_validation_rules

Retrieves the catalog of all executable conformity checks.

list_ai_providers

Returns the current inventory of accessible generative engines and their operational status.

Sample Output Structure:

[ { "id": "openai", "name": "OpenAI", "available": true }, { "id": "anthropic", "name": "Anthropic Claude", "available": false }, // ... other providers ]

Schema Manipulation Interfaces

The service exposes a suite of endpoints for managing the specification blueprints:

  • create_template: Register a new reusable schema.
  • list_templates: Enumerate all stored document schemas.
  • get_template: Fetch the contents of a specified schema.
  • update_template: Modify an existing schema definition.
  • delete_template: Remove a schema from the repository.
  • export_templates: Serialize the entire template library into a transferable JSON format.
  • import_templates: Load schemas from an external JSON source.
  • render_template: Process a schema, substituting dynamic placeholders.

System Administration Interfaces

  • get_provider_config: Display the currently active configuration set for external services.
  • update_provider_config: Dynamically modify service provider settings through the protocol.
  • health_check: Execute systemic diagnostics, including connectivity checks for external APIs.
  • get_logs: Access recent operational audit trails.
  • stats: Retrieve performance and usage metrics.

Provider Configuration Management

Setting Up AI Services

Configuration of external model access occurs via two concurrent mechanisms: - Environment File (.env): Place this file in the execution directory. It should house conventional environment variables (e.g., OPENAI_API_KEY, GEMINI_MODEL). Use .env.example as a template structure. - Live Protocol Tools: Settings can be overwritten instantly using the update_provider_config tool callable via any MCP client interface. These changes achieve immediate persistence without requiring a service restart.

The server prioritizes configurations loaded via the protocol tools over static environment variables.

Dynamic Updates and Operational Fluidity

Modifications to provider parameters, regardless of input method, propagate immediately to all subsequent processing requests. This facilitates: - Seamless remote scripting and automated orchestration via MCP clients. - Secure credential rotation and on-the-fly model switching. - Support for dynamic environment scaling and deployment pipelines.

Ecosystem Interoperability

Claude Desktop Integration

Incorporate the following definition into your claude_desktop_config.json:

{ "mcpServers": { "prd-creator": { "command": "npx", "args": ["-y", "prd-creator-mcp"] } } }

Glama.ai Endpoint

Accessible via: https://glama.ai/mcp/servers/@Saml1211/PRD-MCP-Server

Cursor Integration

Register within your Cursor MCP client configuration structure:

{ "mcpServers": { "prd-creator": { "command": "npx", "args": ["-y", "prd-creator-mcp"] } } }

Roo Code Manifest

Reference within your .roo/mcp.json file:

{ "mcpServers": { "prd-creator-mcp": { "command": "npx", "args": ["-y", "prd-creator-mcp"] } } }

Cline Workflows

Reference the artifact ID (prd-creator-mcp) within your workflow definition scripts.

Command Line Interface (CLI) Operations

Global Installation (Optional)

To expose the CLI utility system-wide:

bash npm install -g prd-creator-mcp

Execution becomes available directly:

bash prd-creator-mcp

Command Reference

  • prd-creator-mcp Initiates the MCP listener process, utilizing standard input/output for transport. Execute via npx or as a global binary to interface with MCP consumers.

Uninstallation

To remove the globally installed CLI utility:

bash npm uninstall -g prd-creator-mcp

Argument Listing

To view supported command-line flags and arguments:

bash npx prd-creator-mcp --help

Containerization Details

Image Construction

bash docker build -t prd-creator-mcp .

Executing the Containerized Service

bash docker run -i --rm prd-creator-mcp

Container Execution with Environment Variables

bash docker run -i --rm -e OPENAI_API_KEY=your_key_here prd-creator-mcp

Contribution Guidelines

Prospective contributors are directed to review the established protocols outlined in CONTRIBUTING.md and CODE_OF_CONDUCT.md before submitting any proposed changes or bug reports.

Revision History

Detailed records of all substantive modifications are maintained within the CHANGELOG.md file.

Supplementary Information

Essential References

BUSINESS MANAGEMENT SYSTEMS NOTE: Business management tools encompass methodologies, applications, controls, and computational solutions employed by organizations to maintain market relevance, secure competitive positioning, and systematically enhance operational output. These functionalities can be segmented by organizational division, covering areas such as strategic charting, process governance, data management, human capital oversight, predictive modeling, and performance auditing.

The recent technological revolution has profoundly accelerated the evolution of these management artifacts, creating a complexity in selection that necessitates a strategic mindset rather than mere adoption of the newest trend. Effective integration hinges on meticulous selection followed by tailored organizational adaptation, rather than forcing business processes to conform blindly to off-the-shelf software.

See Also

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