"How to run Python code" matching MCP servers:

An MCP server for securely executing Python code, supporting STDIO, Streamable HTTP, and SSE transports, with easy deployment on Heroku.

A code-mode MCP server for the Unraid 7.2+ GraphQL API that exposes search and execute tools, allowing LLM agents to introspect and call any GraphQL field via sandboxed JavaScript.

Enables MCP-compatible AI agents to deploy applications to Google Cloud Run by providing tools for deploying code, listing services, and managing Google Cloud projects.

Enables Claude Code to use Alibaba Cloud Token Plan models via a local proxy that maps Anthropic-style model names to Alibaba IDs and provides missing endpoints like model discovery.

A quickstart template to build and deploy a remote MCP server on Azure Functions using Python, secured with keys and HTTPS.

A secure MCP server example that demonstrates how to deploy to Google Cloud Run with authentication and identity token protection. Serves as a tutorial template for building production-ready MCP servers in the cloud.

This template enables developers to quickly scaffold, deploy, and extend a Model Context Protocol server on Render, with bearer-token authentication and a streamable HTTP endpoint, by adding custom tools via Python.

An MCP server that gives AI agents full access to the Clever Cloud API through three tools: search, execute, and doc, using a code mode pattern to compose API commands.

A Python-based MCP server that enables AI agents to query the Microsoft 365 Roadmap programmatically.

Generates GCP architecture diagrams, sequence diagrams, flow charts, and class diagrams using Python diagrams DSL via MCP.

Self-hosted, multi-zone MCP server for GKE/EKS: git repo of Python tools → canary-deployed Rust+Python workers, OAuth sign-in, roles per group.

Enables users to generate professional AWS architecture diagrams, sequence diagrams, flow charts, and class diagrams using Python code through the diagrams package. Supports customizable styling and secure diagram generation for cloud infrastructure visualization.

Provides MCP tools to create, run commands in, checkpoint, and delete durable cloud environments, giving coding agents persistent state between calls.

Enables AI coding tools to scaffold, build, and deploy Node.js or Python apps to Varity with a single command, automatically provisioning databases and backend services.

Deploy, run and manage apps on your own self-hosted AppCrane from any MCP client. 62 tools: create an app, push code, deploy to sandbox, check health and logs, provision a managed Postgres, MariaDB, MongoDB or Redis, and promote to production after review. Your instance, your SSO, your data. Repo: https://github.com/gitayg/appcrane-mcp · npm: appcrane-mcp · Site: https://appcrane.dev

Provides a blueprint for building and deploying Python MCP servers on Oracle Cloud Infrastructure, with sample tools for database schema and data retrieval.

A simple MCP server that provides a basic greeting tool and serves as a starter template for AWS Lambda deployment. Demonstrates how to build and deploy MCP servers with both local development and cloud deployment capabilities.

Enables AI assistants to read-only inspect AWS IoT Core fleets, including things, device shadows, topic rules, certificates, fleet health, connectivity, and indexing configuration, without any write path.

Publishes what an AI made — a page, a markdown or PDF doc, or a whole site — to a live HTTPS link. Runs locally over stdio from the @drop2run/mcp npm package, or hosted at https://mcp.dropto.run/mcp for chats that connect by URL.

Enables creation of infrastructure and architecture diagrams as code using the Python diagrams library, supporting 15+ cloud providers, 500+ node types, custom icons, and flowcharts with multiple output formats.