"Common Lisp" matching MCP servers:

A simple, beginner-friendly Model Context Protocol (MCP) server written in Python. It lets any MCP-compatible AI client (like Claude Desktop) manage a to-do list on your computer through five tools: add, view, get by ID, complete, and delete.

Manages a persistent todo list with SQLite storage, reminder notifications, and cross-platform sound alerts.

Enables humanitarian negotiators to analyze complex situations using proven methodologies like Island of Agreement, Iceberg analysis, and stakeholder mapping. Provides structured frameworks for establishing common ground, understanding deeper motivations, and developing strategic engagement plans in high-stakes humanitarian contexts.

Enables AI agents to create password-protected, link-shareable lists and then read, edit, and restyle them — managing typed columns, rows, and per-list CSS, and looking up product pages to fill in prices, photos, and names. It exposes eighteen tools over Streamable HTTP with per-agent bearer tokens, so agents can build and maintain a shared list end to end.

MCP server that exposes a TODO list API to AI assistants, enabling natural language management of tasks with create, read, update, and delete operations.

Enables read-only keyword search across configured SharePoint Online sites via Microsoft Graph, plus document metadata retrieval and text extraction from common file formats. Supports STDIO and Streamable HTTP transports without write permissions.

Enables AI assistants to manage a shared shopping list by adding, viewing, updating, and deleting products for different people via MCP tools.

Enables users to manage a personal to-do list backed by SQLite, adding single or multiple tasks, listing incomplete tasks, renaming or updating task status, and marking tasks complete. All state persists in a local database created automatically on first run.