Model Context Protocol server for Emacs task management with org-autotask
An MCP server implementation designed for Emacs, enabling integration with Org mode to manage tasks through standard interfaces. Facilitates AI assistants access to Org-mode task data, allowing manipulation, retrieval, and updates within the Emacs environment.
Added on:
Created by:
Apr 28 2025
An MCP server implementation designed for Emacs, enabling integration with Org mode to manage tasks through standard interfaces. Facilitates AI assistants access to Org-mode task data, allowing manipulation, retrieval, and updates within the Emacs environment.
Added on:
Created by:
Apr 28 2025
Laurynas Biveinis
Featured
What is Model Context Protocol server for Emacs task management with org-autotask?
This package offers a Model Context Protocol (MCP) server tailored for Emacs, specifically targeting task management through Org mode. It allows AI tools and assistants to seamlessly connect and interact with Org-based tasks, enabling operations such as task creation, updates, retrieval, and organization. The system is designed to enhance productivity by integrating automated task management features into the Emacs workflow, supporting developers and power users who rely on Org mode for organizing their tasks and projects. The server is implemented in Emacs Lisp and can be configured to work with external AI services, making task handling more efficient and accessible within the developer's environment.
Who will use Model Context Protocol server for Emacs task management with org-autotask?
- Emacs users
- Developers using Org mode
- AI assistant developers
- Productivity enthusiasts
How to use the Model Context Protocol server for Emacs task management with org-autotask?
- Step 1: Install the MCP server package
- Step 2: Configure the server according to your environment
- Step 3: Connect your AI assistant to the MCP server using the provided scripts
- Step 4: Use the commands to manipulate Org mode tasks via your AI assistant
- Step 5: Monitor and adjust configurations for optimal performance
Model Context Protocol server for Emacs task management with org-autotask's Core Features & Benefits
The Core Features
- Integrates with Emacs Org mode
- Allows task CRUD operations
- Provides a standard interface for AI assistants
- Supports configuration for different environments
The Benefits
- Streamlines task management with automation
- Enhances productivity within Emacs
- Enables AI-assisted task organization
- Provides a flexible and extendable system
Model Context Protocol server for Emacs task management with org-autotask's Main Use Cases & Applications
- Automated task updates via AI
- Embedding AI in project management workflows
- Enhancing Emacs productivity with automated task handling
- enabling remote AI access to Org tasks
FAQs of Model Context Protocol server for Emacs task management with org-autotask
Developer
- laurynas-biveinis
You may also like:
Developer Tools
A desktop application for managing server and client interactions with comprehensive functionalities.
A Model Context Protocol server for Eagle that manages data exchange between Eagle app and data sources.
A chat-based client that integrates and uses various MCP tools directly within a chat environment for enhanced productivity.
A Docker image hosting multiple MCP servers accessible through a unified entry point with supergateway integration.
Provides access to YNAB account balances, transactions, and transaction creation through MCP protocol.
A fast, scalable MCP server for managing real-time multi-client Zerodha trading operations.
A remote SSH client facilitating secure, proxy-based access to MCP servers for remote tool utilization.
A Spring-based MCP server integrating AI capabilities for managing and processing Minecraft mod communication protocols.
A minimalistic MCP client with essential chat features, supporting multiple models and contextual interactions.
A secure MCP server enabling AI agents to interact with Authenticator App for 2FA codes and passwords.
Research And Data
A server implementation supporting Model Context Protocol, integrating CRIC's industrial AI capabilities.
Provides real-time traffic, air quality, weather, and bike-sharing data for Valencia city in a unified platform.
A React application demonstrating integration with Supabase via MCP tools and Tambo for UI component registration.
A MCP client integrating Brave Search API for web searches, utilizing MCP protocol for efficient communication.
A protocol server enabling seamless communication between Umbraco CMS and external applications.
NOL integrates LangChain and Open Router to create a multi-client MCP server using Next.js
Connects LLMs to Firebolt Data Warehouse for autonomous querying, data access, and insight generation.
A client framework for connecting AI agents to MCP servers, enabling tool discovery and integration.
Spring Link facilitates linking and managing multiple Spring Boot applications efficiently within a unified environment.
An open-source client to interact with multiple MCP servers, enabling seamless tool access for Claude.
Os Automation
A server that executes AppleScript commands, providing full control over macOS automations remotely.
A Python-based MCP server enabling secure management and automation of OPNsense firewalls via API.
Securely run MCP servers without modifying configs by managing secrets safely through the launcher.
Automates MCP server creation for AWS services using boto3, simplifying server setup for development.
A GUI tool for managing MCP servers across clients with seamless toggling and real-time monitoring features.
A cross-platform desktop app providing offline access, performance, and detailed metrics for MCP system interaction.
An AI agent controlling macOS using OS-level tools, compatible with MCP, facilitating system management via AI.
A game client cheat with features like bypassing protections and modifying game behavior for Minecraft 1.16.5
A cross-platform package manager designed to manage all MCP servers efficiently and seamlessly.
A filesystem MCP server enabling an LLM to read and list local directory files for AI integration.