Hello World MCP Server
Ctxnest MCP server is a locally run integration for AI assistants that speak the Model Context Protocol. Hello World MCP Server.
This is a simple "Hello World" MCP (Model Context Protocol) server created for testing purposes.
Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client.
Once Ctxnest is connected, these are the calls the assistant has available:
Input — name (string)Output — A personalized hello messagePrerequisites — The Prerequisites tool exposed by this serverInstallation — 1. Clone or navigate to the project directory. 2. Install dependencies: bash npm installPlenty of file and storage access servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. Ctxnest's toolset — Input, Output, Prerequisites and 1 more — is a fair guide to whether it matches your workflow. It is maintained by safiyu; worth a glance at recent repository activity before you build anything load-bearing on it.
We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.
| Tool | What it does |
|---|---|
| Input | name (string) |
| Output | A personalized hello message. |
| Prerequisites | The Prerequisites tool exposed by this server. |
| Installation | 1. Clone or navigate to the project directory. 2. Install dependencies: bash npm install |
Scoped local file access — read, write, search and reorganise files in directories you explicitly allow.
Search and read your Drive — Docs, Sheets and files become context your assistant can actually use.
Query, modify and analyse local SQLite databases in conversation — the fastest way to chat with a data file.
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Chat with your second brain — search, read and write vault notes through the Local REST API.
Connects AI models to an Obsidian knowledge base for direct access and manipulation of notes and folders.