"How to Retrieve Console Logs" matching MCP servers:

Enables AI assistants to execute Ruby console commands (Rails console, IRB, etc.) with persistent session support for interacting with Ruby/Rails applications through natural language.

Enables an LLM or agent to drive a VUnit HDL unit-testing project end to end: list tests, compile, run, and inspect reports and per-test logs.

Control the Unity Editor from any MCP host. One package install, one click, and your AI assistant can see your scene, create objects, and talk to the console. Patina is a Rust MCP server paired with a C# Unity bridge. It connects your favorite AI coding tool directly to the Unity Editor over a local TCP channel, with zero manual config.

An MCP server for LaTeX that enables AI assistants to check documents for errors, parse compiler logs, and compile LaTeX files, helping them fix documents instead of guessing.

Enables AI coding agents to compile Delphi projects programmatically by parsing .dproj files, executing the Delphi compiler, and returning structured error results with multi-language support and automatic configuration generation from IDE build logs.

Enables interactive Python execution with a persistent IPython kernel through MCP, retaining namespace state and providing structured output logs for agent and tool integrations.

Jungle Grid MCP Server lets AI agents submit, estimate, monitor, and retrieve logs for GPU workloads through Jungle Grid. It enables agentic execution for inference, training, fine-tuning, and batch jobs without manually choosing GPU providers or infrastructure.

A demonstration server that reveals security risks by accessing sensitive environment variables, illustrating how MCP tools can potentially leak user data without explicit consent.

Enables execution of SAS code on SAS Viya compute environments with OAuth2 authentication. Allows users to run SAS programs and retrieve execution results including logs and output through the Model Context Protocol.

MCP Server for the Peacock extension for VS Code (https://peacockcode.dev), coloring your world, one Code editor at a time. The main goal of the project is to show how an MCP server can be used to interact with APIs.

Provides sandboxed code execution and data processing for CSVs and logs to achieve over 95% token savings. It enables secure multi-language execution and progressive tool disclosure to optimize LLM context usage.

A secure Node.js execution environment that allows coding agents and LLMs to run JavaScript dynamically, install NPM packages, and retrieve results while adhering to the Model Control Protocol.

An educational implementation of a Model Context Protocol server that demonstrates how to build a functional MCP server for integrating with various LLM clients like Claude Desktop.

Enables AI assistants to interact with Interactive Brokers trading accounts to retrieve market data, check positions, and place trades. Includes pre-configured IB Gateway and handles OAuth authentication automatically.

A Model Context Protocol server that enables AI assistants to build and test Xcode projects directly through a standardized interface, with capabilities for running tests, monitoring progress, and accessing logs in real-time.

An educational implementation of a Model Context Protocol server that demonstrates how to build a functional MCP server integrating with various LLM clients.

Enables execution of Go code in the Go Playground sandbox and generation of shareable URLs for code snippets. Provides tools to run Go code, share code via URLs, or perform both operations simultaneously.

A Model Context Protocol server that enables AI agents to retrieve and understand entire codebases at once, providing tools to analyze local workspaces or remote GitHub repositories.

An MCP server that executes tox commands to run Python tests within a project using pytest, allowing users to run all tests or specific test groups, files, cases, or directories.

Converts Figma designs to React Native components, allowing users to extract components from Figma designs and generate corresponding React Native components with proper typing and styling.