"Finding a program written in Java" matching MCP servers:

Persistent memory and pattern learning for AI coding assistants via MCP.

Provides agents with real Linux VMs to run commands, manage files, expose ports, and track costs, all through an ephemeral sandbox service.

All In One Model Context Protocol: qdrant, google suite (gmail, calendar, ...), jira, gitlab, CLI, ...

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.

Enables agents to dynamically generate typed MCP tool schemas, validate Python execution ASTs against unsafe imports, and hot-plug sandboxed callable handlers into an active runtime. This allows new tools to be synthesized and safely executed on demand.

A simple MCP server implementation in TypeScript that communicates over stdio, allowing users to ask questions that end with 'yes or no' to trigger the MCP tool in Cursor.

Wraps Claude Code as a server using the Model Context Protocol (MCP), allowing teams to interact with Claude Code through a Slack bot interface.

A self-hosted MCP server that enables AI coding agents to read, edit, search, and run code in local projects with human review loops and policy controls.

Provides a secure workspace for AI-driven file management and Python script execution designed to run on Vercel. It enables tools for full file operations and code execution within a sandboxed environment.

Allows LLMs to execute Wolfram Language code in a secure, session-based environment by providing an interface to interact with a Wolfram Mathematica kernel.

Enables MCP clients to execute Python code directly via stdin, preserving quotes, f-strings, and backslashes exactly as written, and returns stdout, stderr, and exit codes.

Local CI/CD engine for AI agents. ActionD listens to LGH git events and runs plugin jobs (Go/Python/Java/web toolchains) in isolated checkouts, with structured results, root-cause failure diagnosis, approval gates, and auto-rollback. The MCP server exposes 23 tools, including dev_cycle_run (commit → CI → structured verdict in one call) and actiond_diagnose for failed-job analysis.

A FastMCP server that enables AI agents to safely execute shell commands, run code in Python/Node.js/Go, and install packages, all packaged in Docker for secure deployment.

Enables executing submitted code snippets in a fresh isolated V8 isolate, capturing stdout, stderr, return values, and failures under enforced resource limits.

Enables AI coding agents to compile, test, run, hot-swap, and debug Java applications incrementally through MCP, providing runtime feedback for verifying code changes.

A Model Context Protocol server that allows Claude Desktop to manage and execute tasks in a queue-based system, supporting planning, execution, and completion phases.

Allows LLMs to execute Python code in a specified Conda environment, enabling access to necessary libraries and dependencies for efficient code execution.

Enables an AI agent to run Wolfram Language in a persistent Mathematica kernel, interrupt running computations while preserving state, and replay notebooks in a headless environment.

Enables AI agents to program MicroPython boards such as Raspberry Pi Pico and ESP32 through Thonny, with visible shell commands and optional human approval.

A secure JavaScript REPL server that enables executing code snippets in a sandboxed environment with memory protection, timeout handling, and comprehensive error reporting.