MCP Template Server
A Python starter template for building MCP servers with client connection management and Jupyter notebook integration. Provides a structured foundation for adding custom tools, prompts, and workflows to create AI-powered applications.
README
MCP-Template
A Python starter project for building an MCP (Model Context Protocol) server. It includes a server, a client pool to manage multiple connections safely, and a Jupyter notebook demonstrating how to use the tools and communicate with the AI. The project is structured to make it easy to add your own tools, prompts, and workflows. To get started, clone the repository, install dependencies, run the server, and use the notebook to test and interact with your MCP setup.
Prerequisites:
-
Create a virtual environment (conda or python) and activate it
# Python Virtual Environment (Create) python -m venv .venv # Activating (Windows) .\.venv\Scripts\activate # Activating (Linux/MacOS) source .venv/bin/activate# Conda Virtual Environment (Create) conda create -n myenv python=3.11 # Activating conda activate myenv -
pip install the requirements (in the environment)
pip install -r requirements.txt -
Make sure you have an Azure client (or OpenAI; you may need to update the code if new fields are required). Create a
.envfile in the project root directory with the following fields:AZURE_API_KEY="Your API Key" ENDPOINT="Your Endpoint" VERSION="Your OpenAI Version" MODEL="Your Azure OpenAI Model"
Sources
- Official MCP Documentation: https://modelcontextprotocol.io/docs/getting-started/intro
- Official MCP Python-SDK: https://github.com/modelcontextprotocol/python-sdk
- Official & Unofficial Servers: https://github.com/modelcontextprotocol/servers
- Tool Management: https://arxiv.org/pdf/2410.14594
Recommended Servers
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.
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.
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.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
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.
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.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
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.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.