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MCP in 10 Minutes

MCP in 10 Minutes

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github.com/nicknochnackDeveloper Tools53Updated 80w ago
Repository

About MCP in 10 Minutes

MCP in 10 Minutes is a tutorial project showing how to build an MCP server for Yahoo Finance in about ten minutes. It suits developers who are new to writing MCP servers.

Key features

  1. 01Example MCP server for Yahoo Finance
  2. 02Debugging with the MCP Inspector
  3. 03Running an agent script against the server
  4. 04Langflow integration instructions

Use cases

  1. 01Learning the basic MCP server workflow
  2. 02Adapting the example to other data sources

MCP support

The project demonstrates how to write an MCP server and test it with the MCP Inspector, with the server defined in server.py for MCP clients to call.

#mcp#mcp-server#yahoo-finance

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

MCP in 10 Minutes

Learn how to build a MCP Server for Yahoo Finance (and just about anything else) in 10 minutes.

See it live and in action 📺

README image

Startup 🚀

  1. Clone this repository git clone https://github.com/nicknochnack/MCPin10 and go into it cd MCPin10
  2. Create a virtual environment uv venv and activate it source .venv/bin/activate
  3. Install the dependencies uv sync
  4. Run the inspector uv run mcp dev server.py
  5. Run the agent uv run agent.py
  6. Install langflow and run it: uv pip install langflow and uv run langflow run

N.b. Make sure you have ollama running.

Other stuff

Who, When, Why?

👨🏾‍💻 Author: Nick Renotte
📅 Version: 1.x
📜 License: This project is licensed under the MIT License

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.