-
securityA
license-
qualityServes as a guardian of development knowledge, providing AI assistants with curated access to latest documentation and best practices.
Last updated -
89
77
MIT License
The ContextEngine MCP Server is a Model Context Protocol server that enables Documentation Driven Development (DDD) through structured AI-human collaboration workflows and intelligent context management.
Core Capabilities:
Initialize & Setup: Use
start_context_engineto automatically create local documentation structure (implemented/,requirements/,config/directories) and configure settingsExecute Workflows: Access 9 standardized documentation-driven workflows for development, supporting, and system activities
Manage Context: Leverage context engineering, knowledge graphs, and persistent documentation repositories to eliminate repetitive context provision
Quality Assurance: Align code generation with documented requirements and specifications through structured documentation hierarchies
Health Monitoring: Check API connectivity and system health with dedicated tools (
check-health,greet)
Integration Features:
Compatible with MCP clients like Cursor, Claude Code, VS Code, and Windsurf
Supports API key authentication and comprehensive structured logging
Enables dynamic context composition and hierarchical documentation organization
The server transforms development workflows by making documentation the foundation for AI-assisted coding, ensuring consistency and reducing context overhead.
ContextEngine MCP Server
A Model Context Protocol (MCP) server that provides an interface to the ContextEngine system - a comprehensive Documentation Driven Development (DDD) methodology. This MCP server enables AI assistants to access ContextEngine's structured workflows, context management tools, and knowledge graph system for documentation-first development processes, eliminating repetitive context provision and ensuring code generation follows documented requirements.
š What is ContextEngine?
ContextEngine is an MCP server that implements a comprehensive Documentation Driven Development (DDD) system. It provides structured workflows, context management, and tools that enable AI assistants and humans to collaborate effectively through documentation-first development methodologies.
Core Philosophy
ContextEngine addresses the fundamental challenges of AI-human collaboration in software development:
Context Management: Eliminates repetitive context provision by creating persistent documentation repositories
Quality Assurance: Ensures code generation follows documented requirements and specifications
Scalability: Handles 3x to 30x more information per person than traditional development methods
Business Alignment: Maintains clear connection between technical implementation and business value
Features
Documentation-Driven Workflows: 9 standardized workflows for different development activities
Context Engineering: Dynamic context composition and provision through knowledge graph
Structured Documentation: Plan and task documents with hierarchical organization
Local Documentation Setup: Automatic creation of organized folder structure and configuration files
TypeScript: Full type safety and modern development experience
Authentication: Built-in support for API keys and authentication
Comprehensive Logging: Structured logging with proper MCP compatibility
š ļø Installation
Requirements
Node.js >= v18.0.0
Cursor, Claude Code, VSCode, Windsurf or another MCP Client
Connecting to MCP Clients
"mcp": {
"servers": {
"context-engine": {
"type": "stdio",
"command": "npx",
"args": ["-y", "context-engine", "--api-key", "YOUR_API_KEY"]
}
}
}
šØ Available Tools
ContextEngine provides tools for DDD workflow execution:
1. start_context_engine
Starts the ContextEngine system and automatically sets up the local documentation structure. This tool:
Initializes the ContextEngine via API call to establish system awareness
Creates local documentation structure with organized folders for DDD workflows
Sets up configuration files with default settings and workflow definitions
Provides comprehensive feedback about both remote and local setup status
The tool creates a .context-engine directory structure:
.context-engine/
āāā implementation/ # For completed documentation and implementations
āāā requirements/ # For requirements and specifications
āāā config/ # For configuration files
āāā settings.json # ContextEngine settings
āāā workflows.json # Workflow configurations
Response Format: Returns a combined status showing both API response and local setup results with clear emoji indicators:
š Success: Documentation structure setup completed
ā ļø Warning: Setup completed with issues
ā Error: Setup failed (but API call succeeded)
CLI Arguments
Your MCP server accepts the following CLI flags:
--transport <stdio|http>ā Transport to use (stdioby default)--port <number>ā Port to listen on when usinghttptransport (default3000)--api-key <key>ā API key for authentication (if needed)--server-url <url>ā Custom server URL (defaults to https://contextengine.in)
š Usage
Start ContextEngine: Use the
start_context_enginetool to initialize the DDD system and set up local documentation structure and local documentation setup resultsSelect Workflow: Choose from 9 available workflows based on your development objective
Execute Workflow: Follow the structured workflow phases to complete your development task
Integrate with AI assistants: Connect to Cursor, VS Code, Claude Code, etc.
š License
MIT
hybrid server
The server is able to function both locally and remotely, depending on the configuration or use case.
Tools
Provides real-time access to up-to-date library documentation and code examples for any programming library. Helps AI coding assistants deliver accurate, current information instead of relying on outdated training data.
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