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6 months ago
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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": {
"ishuru-open-mcp": {
"command": "node",
"args": [
"/Users/sdluffy/conductor/workspaces/playground/san-jose/open-mcp/dist/index.js"
],
"env": {
"GOOGLE_GENERATIVE_AI_API_KEY": "YOUR_API_KEY"
}
}
}
}You can run a modular MCP server that orchestrates Prompts, Skills, and Workflows to automate personal productivity. It exposes a programmable interface you can connect to from MCP clients, enabling multi-step automation with built-in templates, task sequences, and pipelines.
How to use
Connect to your MCP client and start issuing requests to manage prompts, skills, and workflows. You can run standard actions like starting the local server, executing predefined workflows, or rendering prompts with your chosen variables. The server is designed to work in conjunction with a client that can issue tool calls, pass parameters, and handle results from AI summarization and other AI-enhanced features.
How to install
Prerequisites you need on your machine: Node.js and npm installed. You may also need an API key for AI summarization if you plan to use that feature.
Install dependencies and build the project, then start the server.
Configuration and usage notes
Set the API key for AI summarization features if you plan to use those capabilities. The key is provided as an environment variable named GOOGLE_GENERATIVE_AI_API_KEY.
Run the server using the provided startup command in your environment. The recommended local runtime is to execute the Node.js entry point with your workspace path, which points to the compiled server script.
Project configuration example
{
"mcpServers": {
"open_mcp": {
"type": "stdio",
"name": "open_mcp",
"command": "node",
"args": ["/Users/sdluffy/conductor/workspaces/playground/san-jose/open-mcp/dist/index.js"]
}
}
}
Security considerations
The server validates requested paths against an allowed directory whitelist, prevents command injection, and enforces timeout protections on HTTP requests and directory traversal safeguards.
Notes on project structure and tools
The MCP server provides a range of tools to manage prompts, skills, and workflows, including listing, searching, rendering, validating, and executing. It also exposes a set of core utilities for file access, web interactions, version control, system information, and AI summarization.
Troubleshooting
If you encounter issues starting the server, verify that Node.js and npm are installed, ensure the environment variable for the API key is set if you use AI features, and confirm the path to the compiled index script is correct in the startup command.
Examples and common workflows
- Start a daily briefing workflow to generate a productivity summary
- Execute a project status workflow to gather updates from connected tools
- Render a productivity prompt with your current tasks and priorities
Project structure overview
The server is organized into core engines for prompts, skills, and workflows, plus a registry of tools that handle file operations, web scraping, git operations, and AI summarization.
Available tools
list_prompts
List all prompts with optional category filtering.
search_prompts
Search prompts by a query string.
get_prompt
Retrieve a prompt template by id.
render_prompt
Render a prompt with given parameters.
validate_prompt
Validate prompt parameters before rendering.
get_prompt_categories
List all prompt categories.
summarize_document
Read and summarize a document.
analyze_text
Read and analyze text.
setup_project
Initialize a new project.
daily_briefing
Get a daily productivity briefing.
project_status
Get a project status report.
read_file
Read a file from the filesystem.
write_file
Write content to a file.
list_directory
List files in a directory.
search_files
Search files by content or name.
fetch_url
Fetch content from a URL.
scrape_html
Scrape HTML content from a webpage.
git_status
Show git repository status.
git_log
Show git commit history.
git_diff
Show git diffs.
system_info
Provide system information.
get_time
Get the current time.
summarize
General AI summarize function.