"Devbox" matching MCP servers:

Enables MCP clients to execute shell commands, manage long-running processes, and read/write files on the host machine with the permissions of the user running the server.

Enables an LLM to run a project's real test suite and SonarQube scan against on-disk projects using throwaway, socket-proxied containers without granting raw shell access.

An MCP server that exposes Runloop Devbox operations as tools, enabling AI agents to create and manage Linux sandboxes, execute commands, edit files, snapshot disks, and drive interactive PTY sessions.

Enables agents to ask TypeSafe AI's Jev decision model typed questions — choices, scores, true/false propositions, and image bounding boxes — about a text or JSON state, returning structured answers with calibrated probabilities and confidence instead of free-form prose. Supports images, multi-question batch calls, and long-context requests over stdio.

Enables MCP clients to obtain typed, probabilistic decisions from text or structured state and up to four images—choosing among labeled options, scoring on ordered scales, and estimating whether propositions are true—for routing, triage, moderation, risk scoring, and similar agent workflows.

MCP server that integrates Blender with CSM.ai 3D assets and LLM agents, enabling AI-assisted 3D modeling and animation through natural language commands.

A Flask-based chatbot using Gemini 2.5 Flash and MCP tools to manage GitHub repositories and LinkedIn profiles via natural language.