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ContextEngine
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7 months ago
First Indexed
3 months ago
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Documentation & install
Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.
Installation
Add the following to your MCP client configuration file.
Configuration
View docs{
"mcpServers": {
"livelifelively-context-engine-mcp": {
"command": "npx",
"args": [
"-y",
"context-engine",
"--api-key",
"YOUR_API_KEY"
]
}
}
}ContextEngine MCP Server provides a dedicated interface to the ContextEngine system, enabling documentation-driven development workflows, persistent context management, and knowledge graph access for AI-human collaboration. You can connect via MCP clients, initialize local documentation structures, and run standardized workflows to keep implementations aligned with documented requirements.
How to use
You connect your MCP client to the ContextEngine MCP Server using a stdio-based configuration. This preserves a persistent link between your local documentation workspace and the remote server, so you can execute predefined workflows and access context management tools without repeatedly supplying context.
How to install
Prerequisites you need before starting:
-
Node.js >= v18.0.0
-
Cursor, Claude Code, VSCode, Windsurf or another MCP Client
Connecting to the MCP server from your client
"mcp": {
"servers": {
"context-engine": {
"type": "stdio",
"command": "npx",
"args": ["-y", "context-engine", "--api-key", "YOUR_API_KEY"]
}
}
}
How to run and initialize local documentation
After you have the MCP connection configured, you can start ContextEngine locally to auto-create a structured documentation workspace and begin managing requirements and workflows. Use the connected MCP client to trigger the start process, which will both initialize the remote system and scaffold your local folders.
Available tools
start_context_engine
Starts the ContextEngine system and automatically sets up the local documentation structure, initializes the remote system, creates a organized folder layout, and configures default settings and workflows. Returns combined status on API and local setup with clear indicators.