What components does the Quick Example server include?
The server includes tools (functions the LLM can invoke, like querying a vector database), resources (data sources identified by URIs), and prompts (reusable templates for common tasks).
Q
Quick Example MCP Server
@justmywyw
Basic information
About Quick Example MCP Server
No overview available yet
Quick Example MCP Server config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"quick-example": {
"command": "npx",
"args": [
"-y",
"mcprouter"
]
}
}
}Quick Example MCP Server tools
Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
Fetch the live tool list by running this server in a temporary sandbox using the button above.
Overview
What is Quick Example?
Quick Example is a sample MCP (Model Context Protocol) server that demonstrates the core MCP capabilities—tools, resources, and prompts—by building a simple knowledgebase chatbot flow. It is intended for developers learning how to create and integrate MCP servers with LLM applications.
How to use Quick Example?
Clone the repository, create a ChromaDB vector database as described in the provided Jupyter notebook, set up a virtual environment (recommended with uv), install dependencies via uv sync, then run python client.py mcp_server.py to start both the client and server.
Key features of Quick Example
- Demonstrates tools, resources, and prompts in a single server
- Integrates a vector database for RAG-style queries
- Allows users to choose existing resources for context
- Provides reusable prompt templates for analytical workflows
- Includes a simple CLI client for testing interaction patterns
Use cases of Quick Example
- Learning how to implement MCP server components (tools, resources, prompts)
- Prototyping a knowledgebase chatbot with retrieval augmented generation
- Testing MCP client-server communication patterns
Frequently asked questions
What are the runtime dependencies?
The server requires a Python virtual environment, dependencies installed via `uv sync`, and a pre-built ChromaDB vector database (created from the provided notebook).
Where does the vector database data live?
The ChromaDB database is created locally by following the instructions in `MCP_setup.ipynb`—no external data storage is used by default.
What transport or authentication does the server use?
The server uses standard MCP protocol communication; the example client in `client.py` connects via a subprocess (stdio transport). No authentication is described.
How does this example differ from production MCP servers?
This is a learning example, not a production-ready server. It focuses on illustrating the three core MCP components (tools, resources, prompts) in a simple knowledgebase scenario.
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