A-Team MCP Server — build, validate, and deploy multi-agent solutions from any AI environment

VCP visual-synesthesia protocol plugin for DeepSeek Harness: render agent HTML output as real UI (cards / KaTeX math / Mermaid diagrams / built-in calligraphy fonts / zero-JS interactions), plug-and-play on any DSH environment

AI-native engineering environment management that makes your codebase agent-ready.

Build an iOS / Apple app on remote Xcode with `lim xcode build` instead of local xcodebuild, run project commands with `lim xcode run`, or run its XCTest suites with `lim xcode test`, from any environment (Linux, Windows, macOS, VM, container). Use for non-Bazel projects (an `.xcodeproj` / `.xcworks

Run Maestro YAML flows against a Limrun cloud iOS simulator with `lim ios maestro`, from any environment (Linux, Windows, macOS, VM, container). Use when the user wants to run, write, or debug Maestro flows or `maestro test` on iOS, migrate an existing Maestro suite to remote simulators, or asks for

Build an Android app on a remote Gradle sandbox with `lim gradle build` instead of local Gradle or Android Studio, from any environment (Linux, Windows, macOS, VM, container). Use when the user wants to build an APK or AAB, sign a release with an upload key, prepare a Play Store publish, inspect bui

CLI for setting up and managing safeword development environments

A free local cloud environment for AI agents to build, test, and debug Google Cloud applications.

Accounts-payable exception environment with a pass/fail verifier and proof packet: AI agents work AP

Execute Python code in a safe sandboxed environment via [inference.sh](https://inference.sh). Pre-installed: NumPy, Pandas, Matplotlib, requests, BeautifulSoup, Selenium, Playwright, MoviePy, Pillow, OpenCV, trimesh, and 100+ more libraries. Use for: data processing, web scraping, image manipulation

DeepSeek Harness Codex Desktop — 无需预装环境、开箱即用的跨平台桌面客户端 · A ready-to-use cross-platform DeepSeek Harness desktop client with no environment setup

Unified execution environment for Python code, shell commands, and programmatic MCP tool calls.

Video outpainting on RunComfy via the `runcomfy` CLI — extend the spatial canvas of a video, change aspect ratio (9:16 vertical to 16:9 horizontal or vice versa), add environment beyond the original frame while preserving the central action. Routes prompt-shaped spatial extension through Wan 2-7 edi

Enables AI clients to search laws and cases and retrieve legal materials through a stdio bridge, with Token configured in the environment and dynamic discovery of account-available tools.

Execute Python code in a safe sandboxed environment via [inference.sh](https://inference.sh). Pre-installed: NumPy, Pandas, Matplotlib, requests, BeautifulSoup, Selenium, Playwright, MoviePy, Pillow, OpenCV, trimesh, and 100+ more libraries. Use for: data processing, web scraping, image manipulation

Inventory local Codex plugins and Skills, inspect recorded usage, and identify potential redundancy to support user-directed cleanup. Includes a local MCP service, dashboard, and companion Skills; requires Windows and a local Codex environment.

Enables AI assistants to scan-code log into Yuketang and read-only browse courses, slides, classroom replays with page-flip timelines, AI mind maps, notes, and assignment progress. Sessions can be supplied via QR login or environment variables, with separate handling for the four Yuketang regional deployments.

Enables MCP clients to query a sensitive local workspace through a read-only status bridge that returns only pre-defined numeric file counts, status enums, and static policy—never source, paths, diffs, logs, environment variables, or command execution.

Enables vendors to run a declared check battery against their own MCP server, emit sealed Assay-format scorecards with evidence hashes and environment fingerprints, and have a local verifier re-run a random sample to issue counter-signed verification receipts.

Enables LLM-powered developer environments to discover and evaluate potentially beginner-friendly GitHub issues using explainable heuristics, clear rationale, and direct evidence links over stdio.

Execute Python code in a safe sandboxed environment via [inference.sh](https://inference.sh). Pre-installed: NumPy, Pandas, Matplotlib, requests, BeautifulSoup, Selenium, Playwright, MoviePy, Pillow, OpenCV, trimesh, and 100+ more libraries. Use for: data processing, web scraping, image manipulation

Execute Python code in a safe sandboxed environment via [inference.sh](https://inference.sh). Pre-installed: NumPy, Pandas, Matplotlib, requests, BeautifulSoup, Selenium, Playwright, MoviePy, Pillow, OpenCV, trimesh, and 100+ more libraries. Use for: data processing, web scraping, image manipulation

Execute Python code in a safe sandboxed environment via [inference.sh](https://inference.sh). Pre-installed: NumPy, Pandas, Matplotlib, requests, BeautifulSoup, Selenium, Playwright, MoviePy, Pillow, OpenCV, trimesh, and 100+ more libraries. Use for: data processing, web scraping, image manipulation

Execute Python code in a safe sandboxed environment via [inference.sh](https://inference.sh). Pre-installed: NumPy, Pandas, Matplotlib, requests, BeautifulSoup, Selenium, Playwright, MoviePy, Pillow, OpenCV, trimesh, and 100+ more libraries. Use for: data processing, web scraping, image manipulation