"Creating custom experimental images in Docker" matching MCP servers:

Sandboxed Python execution with automatic dependency management. Executes Python scripts in isolated environments (bubblewrap or Docker) with PEP 723 inline dependencies, preventing host pollution.

MCP server for creating, monitoring, and managing Devin AI sessions.

MCP server that generates images using Gemini 3 Pro Image on Vertex AI, with support for reference images, task management, and GCS integration.

An MCP server that scaffolds full-stack projects with consistent structure, Docker setup, CI/CD pipelines, and database configuration.

Enables AI assistants to render 3D models from OpenSCAD code, generating single views or multiple perspectives with full camera control. Supports animations, custom parameters, and returns base64-encoded PNG images for seamless integration.

Enables LLM clients to inspect local development environment, including Docker container health, pnpm workspace integrity, and stuck process diagnosis.

Finds MCP servers in the MCP Rating index and connects to them on demand, proxying their tools under namespaced names and notifying the client when tools change. Each server gets a short environment allowlist plus only the variables you name for it, so other API keys in your environment aren't passed on. Files aren't isolated unless you opt into Docker containers.

Provides access to the Ghibli Image Generator API for creating Ghibli-style images using OpenAI models. It enables users to generate stylized artwork through the ghibli_generate_image tool.

This MCP server enables interaction with Atlassian products (Jira and Confluence), with additional tools for uploading attachments, embedding images, and commenting with images. It supports both Cloud and Server/Data Center deployments.

Enables searching, reading, creating, and updating AIO Tests test cases in Jira from any MCP client, supporting Jira Cloud and Server/Data Center with a read-only mode.

A personal memory engine and MCP server that stores durable facts in markdown files managed via git, enabling hybrid search (lexical + semantic) through an MCP interface for persistent context across LLM sessions.

Code-mode MCP server (docs_search + execute_code two-tool surface) backed by a unified capability manifest across three sandbox kernels (in-process node:vm, WASM via QuickJS / Pyodide / Wasmtime, and remote microVM via E2B / Cloudflare Sandbox). At N=30 tools the bootstrap-context cost drops to 13.6% of direct tool-use. Apache-2.0.

Enables management of Kylas CRM lead operations, including creating leads, searching and filtering records, and resolving user, product, or pipeline IDs. It provides specialized tools for monitoring idle leads and accessing lead schema instructions through natural language.

Enables Claude to speak in 70+ languages, including pronunciation, audio flashcards, and full language lessons with tutor personas.

MCP server for the Trading 212 public API, enabling account, portfolio, order, pie, and history access with read tools always available and trading tools opt-in.

Enables local agents to connect to and interact with Google Colab sessions running in the browser.

Enables non-multimodal models to see images by providing MCP tools for image understanding and OCR, backed by any OpenAI-compatible vision model.

Provides CodeQL language intelligence to AI agents via MCP, enabling completions, hover, definitions, references, diagnostics, formatting, and in-memory file updates for QL code.

A multi-agent RAG MCP server that answers questions from your documents with a human-in-the-loop approval step, using a coordinator, retriever, and synthesizer agents.

Bridges a local AI agent to a Colab session in the browser, enabling code execution and file operations through the Model Context Protocol.