"A sandbox environment to run Python code and install dependencies" matching MCP servers:

Gemini-powered MCP server for automated code review, analysis, and documentation.

A production-grade MCP server for the Code-Fundi API, enabling AI agents to map codebases, search semantically, and analyze blast radius. It provides tools for repository management, AI-powered research, and impact analysis before shipping changes.

An MCP server that integrates AI agents with Figma, enabling reading and programmatic modification of designs.

Enables AI agents to directly control Figma Desktop via MCP, supporting UI creation, editing, prototyping, and variable management with over 60 tools.

This MCP server enables remote control and management of Claude Code agents, allowing you to execute missions, configure agent personalities, and integrate with other MCP tools.

An MCP server that lets LLM agents operate the IDnow Trust Platform sandbox to list verification flows, create sessions, check sessions, and get session details.

Provides AI coding assistants with access to AccelByte Gaming Services (AGS) Extend SDK functions and models through searchable symbols and detailed documentation. Helps generate SDK code by exposing context about available functions, models, and templates for creating Extend app projects across multiple languages (Go, C#, Java, Python).

Inspect a cronstable job scheduler's jobs, logs, run history, DAG workflows, and cluster health, and ask why a job did or didn't run. Read-only by default; tools that run, pause, or approve jobs and workflow runs need opt-in.

DevEyes is a Model Context Protocol (MCP) server that captures screenshots from your local development environment and automatically optimizes them for LLM consumption.

Search, inspect and install Ballmac UI React + Tailwind components, blocks and templates, with props, keyboard notes and the exact shadcn install command, and plan whole pages from blocks.

A production-grade, extensible Python template for building Model Context Protocol servers with support for Streamable HTTP and stdio transports. It provides a structured framework for implementing tools, resources, and prompts with built-in authentication, observability, and background task management.

Enables AI agents to install, remove, update, and query apt packages on Linux via MCP tools.

A task management MCP server for AI-driven development, enabling creation, tracking, and organization of tasks with subtasks, priorities, and dependencies via natural language commands.

Exposes an Oracle database to MCP clients over stdio, offering 75 tools to query, modify, inspect, and triage the database with zero-install thin mode requiring no Oracle Client. Every statement is recorded in a Markdown audit log.

Enables writing to Figma from MCP clients like Claude Code without a Figma Dev seat, using a local WebSocket relay and a Figma dev plugin.

Enables AI assistants to read and modify Figma designs programmatically through the Model Context Protocol.

A lightweight MCP server that enables AI assistants to execute local development tools and retrieve system status with low latency over stdio or HTTP.

An MCP server that provides AI clients with access to developer documentation via llms.txt files. Exposes tools, resources, and prompts.

Deterministic encode, decode, hash and convert for agents, on the same pipeline engine as the String Utility Belt web app, CLI and editor extensions: a pipeline built and checked in the browser runs unchanged from its share link. Base64/hex/URL, JWT, hashes, JSON/YAML/CSV/XML, dates and regex; tools to search, describe and run utilities or whole pipelines, and to detect input formats. Runs locally

Enables AI assistants to perform Google searches with real, resolvable sources and transparent search terms.