"Fossil SCM" matching MCP servers:

A stdio MCP server providing AI agents with a stable tool interface to read and write TCM test cases through REST, including search, CRUD operations, and a dry-run-to-commit safety flow.

Enables building and evaluating shopping/support agents against a deterministic synthetic retail store with in-memory fixtures. Provides tools, resources, and prompts for product search, cart and order flows, inventory, and policy retrieval over stdio or Streamable HTTP.

An MCP server that composes XcodeBuildMCP and ios-simulator-mcp, adding React Native inspection tools to read the component tree, resolved styles, and perform layout audits on iOS simulators.

Enables mirroring and controlling the iOS Simulator from MCP clients, providing a live viewer, agent cursor tracking, and token-efficient UI snapshots for automation.

Lets a coding agent drive a live GTA San Andreas 1.0 US process to read and write game state, spawn vehicles and peds, set up scenarios, capture screenshots, poke memory, and invoke any SCM opcode. It also hot-reloads ASI plugins under development without restarting the game, turning minute-long test cycles into seconds.

A Model Context Protocol (MCP) server for iOS Simulator automation. Enables AI assistants to visually interact with iOS apps running in the simulator.

Enables AI agents to drive iOS Simulators on macOS by listing devices, launching apps, tapping, typing, swiping, inspecting the UI tree, and taking screenshots.

MCP server that drives the iOS Simulator via accessibility-tree snapshots with stable element refs, enabling LLMs to interactively find, tap, type, and inspect UI elements at sub-200ms latency.

Enables AI agents to manage iOS Simulator state declaratively through MCP tools for inventory, snapshot, diff, planning, and safe apply operations.

Enables AI assistants to lint, render, fix, inspect, and find free space in KiCad schematics and PCBs, providing visual feedback and safe automated text fixes.

Lets Claude design, run and compare local robotics experiments — swarm behaviours, formations, coverage, cooperative localisation and synthetic visual odometry — through tools for cataloguing worlds, launching runs and campaigns, tuning parameters, saving floor plans and diffing metrics. Everything executes on the user's machine via a stdio JSON-RPC process, so runs are reproducible and no data leaves the host.