"Resources for Coding in Python" matching MCP servers:

Specialized MCP server for coding workflows with web search and image analysis tools.

A transport-agnostic MCP server that integrates multiple AI coding agents (Claude Code, Gemini, and Codex) with built-in tools for command execution, calculations, and streaming capabilities. Supports both STDIO and HTTP transports for flexible deployment.

Server that enhances the capabilities of the Cline coding agent. It provides intelligent code suggestions, reduces hallucinations, and documents the knowledge base by leveraging your project's documentation and detecting the technologies used in your codebase.

Enable Claude (or any other LLM) to interactively debug your code (set breakpoints and evaluate expressions in stack frame). It's language-agnostic, assuming debugger console support and valid launch.json for debugging in VSCode.

Persistent memory and pattern learning for AI coding assistants via MCP.

An MCP server that provides tools and resources for managing a coding project's todo list, allowing users to view, add, update, and delete todo items with details like priority, status, and tags.

Enables coding agents to execute Python code, run script files, and install pip packages locally via MCP.

Simple sequential thinking MCP in python

Enables MCP clients like Claude Code and Codex to delegate coding tasks to Cursor's CLI agent, which implements changes in the workspace and returns clean, structured results for review.

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

Call OpenAI Codex from Claude Code for independent second opinions, structured code review, and delegated coding tasks through a FastMCP plugin that drives the codex CLI safely.

Production-ready MCP server starter templates in TypeScript and Python. Includes tool, resource, and prompt patterns with Claude Desktop integration configs.

MCP server for Python build123d to help AIs develop and reason about 3D models and CAD

Exposes 31 high-assurance agentic coding skills as MCP tools and resources, enabling AI agents to invoke structured workflows across DISCIPLINE, TECHNIQUE, KNOWLEDGE LAYER, and REFERENCE registers.

Universal Python code execution MCP server that lets LLMs write and run Python for any task, with auto-install packages, streaming output, and automatic file display.

Delegate coding tasks to external AI coding agents in isolated git worktrees with independent verification, enabling any MCP client to orchestrate multi-agent workflows.

Allows two AI coding agents on different machines to securely pair and share files, context, and conventions through an end-to-end encrypted peer-to-peer channel with human-in-the-loop consent.

Enables Windows users to connect Antigravity CLI as an MCP subagent for coding tasks such as file reading, code execution, edits, and terminal commands, with model selection, conversation continuity, and streaming progress.

MCP server that launches and supervises coding-CLI subagents (claude, opencode) in detached tmux windows, collapsing the ceremony of starting a TUI coding assistant into a single tool call.

Enables AI agents to execute Python, TypeScript, and JavaScript code in persistent Jupyter kernels with stateful variables and imports across interactions.