"Information about Python (programming language or general information)" matching MCP servers:

TypeScript-based MCP server designed to enhance code editing experiences by providing features such as hover information, code completion, and diagnostics.

Lightweight Python Notebook MCP - Enable AI assistants to create, edit, and view Jupyter notebooks via Model Context Protocol

Enables MCP clients to list and run tools tagged by agent task—context, completion, evaluation, post, skill, or none—through a single FastMCP-based server.

A Machine Comprehension Protocol server that enables AI assistants to interact with Kestra workflows through natural language, supporting operations like flow management, executions, backfills, and other Kestra features.

Enables secure execution of Python code in a sandboxed WebAssembly environment using Pyodide and Deno. Automatically handles package management and captures complete execution results including stdout, stderr, and return values.

Enables local, Docker-isolated code execution across six programming languages including Python, Rust, and TypeScript. It features pre-warmed container pooling, persistent sessions, and built-in support for machine learning libraries.

A sophisticated AI-powered server providing intelligent, context-aware conversational capabilities with role-based advisors, semantic memory, multi-LLM support, and web browsing.

Enables probabilistic judgment on typed questions using ten tools, converting validated answers into policy decisions (auto, review, or escalate).

Stdio MCP Server wrapping custom Python runtime (LocalPythonExecutor) from Hugging Faces' smolagents framework. The runtime combines the ease of setup (compared to docker, VM, cloud runtimes) while providing safeguards and limiting operations/imports that are allowed inside the runtime.

Enables users to query ClinicalTrials.gov using natural language instead of complex API parameters, translating plain English requests into structured API calls and returning organized clinical trial data.

A comprehensive framework for building reliable Python MCP servers that enforces incremental development practices through Cursor Rules, featuring built-in security measures and a smart rule system.

A Model Context Protocol server that allows execution of Python code within Daytona workspaces, providing a secure and isolated environment for executing and managing Python scripts.

Enables LLMs to execute Python code in isolated sandboxes with file operations and MCP integration, supporting multi-round execution and plot capture.

Enables agentic coordination by connecting humans and AI agents through group messaging, project tracking, and milestone management. It provides tools for consensus voting, progress checkpoints, and multi-session collaboration across various agentic platforms.

Pre-trade risk validation and position sizing for AI trading agents via G-formula and Iron Fist.

Provides a runnable local stdio Python server scaffold that coding agents extend into custom tool integrations by describing an idea and letting the agent investigate, build, test, and install it. Ships with no prebuilt tools, so it enables guided, agent-assisted creation of MCP tools connected to external APIs, databases, or websites while writes stay disabled until explicitly agreed.

Enables task state management for AI agents with secure credential handling and optional client-side encryption via a local stdio proxy.

Enables analysis of AI agent traces to detect and fix failures using heuristic detectors, with no LLM calls required.

A simple Machine Conversational Protocol server for Warp Terminal that provides a basic greeting tool and personalized greeting resource.

Project Point One Percent - Agent Pay \[pop-pay] is a payment guardrail and one-time flow protocol specifically designed for Agentic AI (e.g., Claude Code, OpenClaw). It enables agents to handle financial transactions safely without risking unlimited exposure of human-controlled credit cards.