Allows users to clone and use the repository for learning MCP server development.
Provides integration for account setup and repository management required for the MCP learning process.
Enables users to build MCP servers for data analysis tasks using Python as the implementation language.
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
The purpose of the repo is to teach you how to make MCP servers. The target audience are non-technical with no real coding experience.
You must be able to:
Download and install:
Python and the dependencies in requirements.txt.
An MCP host application like VS Code or Claude Desktop. Licenses/subscriptions may apply.
Git, to be able to clone and use this repo.
You will need a GitHub account.
You should set up Git for use with VS Code.
Be able to read and understand the basic technical concepts as I explain them. You might need to consult with other resources.
GitHub tutorial for beginners.
Anthropic MCP docs.
VS Code docs.
Python docs.
Be patient with me. This is the first time I'm teaching something based in Python. I'm putting this out there for free.
This repo uses a custom non-commercial license.
You are permitted to use the contents of this repo and derivatives thereof for non-commercial, personal use only. Please enjoy the materials, but also please respect my intellectual property rights.
The code and samples in this repo was created with assistance from Claude Opus 4.0 and Claude Sonnet 4.0.
The docs in this repo were created with assistance from Gemini 2.5 Pro.
No AI was used in the creation of creative materials or content.
I do not consider myself an "AI Expert". I am trying to just share what I learned because I find it useful and interesting. The code, information, and examples in this repo are provided as-is without any warranties or guarantees. You are responsible for your own due-diligence and the code you execute or the information that you consume. Nothing I provide should be taken as advice in an official capacity.
Be critical. Be skeptical. Be humble.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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This server cannot be deployed
Create guides as MCP servers to instruct coding agents to use your software (library, API, etc).
The Mercado Pago MCP Server implements the Model Context Protocol to provide AI agents and LLMs with access to Mercado Pago's APIs and tools within compatible development environments. It acts as an intermediary that translates Mercado Pago resources into executable functions (tools) that AI applications can invoke to perform actions and automate flows. The server simplifies integration, enables using documentation to implement or improve code, and optimizes operations through natural language interactions without manual implementations.
A full backend your AI coding agent can set up over MCP
MCP server for building and testing AI agents with multi-model experimentation and insights.
