mcpappwrite

mcpappwrite

A minimal Python MCP Todo server backed by Appwrite Cloud, providing tools to add, list, get, update, complete, and delete tasks.

Category
Visit Server

README

mcpappwrite

A minimal Python MCP Todo server backed by Appwrite Cloud.

The project is intentionally small: ChatGPT/MCP clients call Todo tools, and the server stores the data in an Appwrite TablesDB table.

Architecture

MCP client / ChatGPT
        |
        v
   Python MCP server
        |
        v
   Appwrite TablesDB
        |
        v
      tasks

Requirements

  • Python 3.10+
  • An Appwrite Cloud project
  • An Appwrite server API key with row read/write access

Appwrite setup

Create a database and a table named tasks (the IDs can also be custom):

  • Database ID: todo_db
  • Table ID: tasks

Create these columns:

Column Type Required Notes
title Varchar Yes Task title
description Text No Details
dueDate Datetime No ISO-8601 datetime
priority Integer No 1 high, 2 medium, 3 low
completed Boolean No Default false
category Varchar No Example: Career
tags Varchar No Comma-separated tags

For the server API key, grant only the database/table/row scopes required for this project. Do not put the API key in source code.

Local setup

Windows PowerShell

python -m venv .venv
.\.venv\Scripts\Activate.ps1
pip install -r requirements.txt
Copy-Item .env.example .env

macOS/Linux

python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
cp .env.example .env

Edit .env with your Appwrite values.

APPWRITE_ENDPOINT=https://<REGION>.cloud.appwrite.io/v1
APPWRITE_PROJECT_ID=your_project_id
APPWRITE_API_KEY=your_server_api_key
APPWRITE_DATABASE_ID=todo_db
APPWRITE_TABLE_ID=tasks

Run

The server uses MCP Streamable HTTP so it can later be deployed as a remote MCP server.

python app.py

The MCP endpoint is normally:

http://localhost:8000/mcp

For a quick local tool test, use the MCP Inspector or another MCP client.

Available tools

  • add_task - create a task
  • list_tasks - list tasks, optionally filtering completed status/category
  • get_task - retrieve one task by row ID
  • update_task - update selected task fields
  • complete_task - mark a task complete
  • delete_task - delete a task

Security

.env is ignored by Git. Never commit an Appwrite API key. For production, put the secret in the hosting platform's secret/environment-variable system.

Future steps

  1. Test Appwrite connection locally.
  2. Test every MCP tool locally.
  3. Add authentication for a remote deployment.
  4. Deploy the MCP server on a free-tier host.
  5. Connect the remote MCP server to a compatible MCP client.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured