"Files formatted in JSON" matching MCP servers:

Enables running one Codex CLI task at a time in an isolated temporary folder, returning Codex's answer and a manifest of produced files for manual review and selective copying.

Local MCP server that registers restricted Python filters and runs them against local JSON, YAML, and TXT files, enabling safe data filtering and file conversion.

A FastMCP server that turns JSON data into Plotly figures, deployable as an isolated service on Modal. Data goes in as JSON; a validated Plotly figure (JSON) or a rendered PNG comes back over the Model Context Protocol.

Runs AI-generated code in secure Firecracker microVMs with opt-in network policy enforcement, PII scanning, prompt injection defense, and audit logging. Exposes MCP tools for running commands, managing files, and the full sandbox lifecycle.

Enables AI assistants to run, list, and analyze Lupa test suites, returning structured JSON results for debugging.

Enables AI assistants to interact with running games in real time — introspecting game state, simulating keyboard and mouse input to actually play, capturing screenshots, executing Lua code, hot-reloading files, and receiving push notifications when state changes.

Enables Claude to generate executable test cases from decision tables in CSV, JSON, or Markdown formats. Provides intelligent test planning guidance and generates Playwright/API test code with TypeScript support.

Enables AI agents to spin up disposable Tenki microVM sandboxes in seconds and use them to run code, manage files, run git commands, and expose preview URLs.

A Model Context Protocol server that enables LLMs to read, search, and analyze code files with advanced caching and real-time file watching capabilities.

A dynamic MCP server that automatically discovers Python files in a directory and exposes them as tools to any MCP-compatible AI client, allowing users to easily create and deploy custom AI tools.

A Model Context Protocol server that automatically reads the Claude Desktop configuration file and presents all available MCP services in an easy-to-copy format at the top of the tools list.

Enables AI assistants to solve linear, integer, mixed-integer, and knapsack optimization problems using Google OR-Tools via a simple JSON interface.

Enables running multiple Claude prompts simultaneously in parallel with support for file contexts and output redirection to individual files.

A Node.js MCP server that wraps the Claude Code CLI to enable parallel execution of AI requests for code generation, editing, and refactoring. It features built-in retry logic, model selection, and JSON validation for structured outputs.

Enables AI agents to read and write .mph model files, control the COMSOL desktop GUI in real time, and run complete modeling, meshing, solving, and post-processing workflows.

Fetches up-to-date documentation for any npm package directly in your IDE by retrieving README files from GitHub repositories or package tarballs. Provides real-time access to current package documentation and API information.

Cuts AI token costs by running user code in a secure sandbox, so data never enters the context window, enabling efficient data processing with MCP protocol.

Enables AI agents to interact with the Roark API by writing and executing TypeScript SDK code in an isolated sandbox, with built-in documentation search to guide those tasks.

Enables agents to synthesize typed MCP tool schemas at runtime, validate Python ASTs for unsafe imports, compile sandboxed callable handlers, and hot-plug them into an active MCP runtime. It provides a zero-dependency, standard-library-only MCP server for safe just-in-time tool creation and execution.

Model Context Protocol server to run Python code in a sandbox.