"A server for data engineering tasks, GPU clustering, nomad setup, and data pipeline management" matching MCP servers:

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.

Exposes local NVIDIA GPU (CUDA) and Rust-to-WASM toolchain as MCP tools for sovereign local compute.

Enables AI coding agents to run policy-constrained Python jobs on lab NVIDIA GPU hosts, including GPU inspection, device reservation, job launching and monitoring, and owner-scoped process stopping.

Enables MCP-compatible AI assistants to run Python code on Google Colab GPU/TPU runtimes, supporting accelerators like T4, A100, H100, with background execution and Google Drive integration.

A Model Context Protocol server that enables Claude to load CSV files and execute JavaScript data analysis scripts for advanced data exploration and insights generation.

A local STDIO MCP server that bridges MCP clients to the Codex CLI by sending instructions to a configured workspace, exposing task run, status, and result tools with a read-only sandbox and no remote transport.

MCP server that turns coding workflows into explicit execution graphs (DAG) with deterministic command execution, human-in-the-loop gates, and tamper-proof run history for Claude Code.

Enables Large Language Models to access and manipulate Autodesk Revit models through a pyRevit-based bridge and the Model Context Protocol.

An MCP server that provides data bridging from Spring Boot interfaces and a lightweight Python sandbox for script execution. It enables agents to fetch data as Markdown or Parquet files and perform automated data analysis within a controlled environment.

A production-ready foundation template for building Model Context Protocol (MCP) servers with FastAPI, featuring modular tools, comprehensive testing, and OpenShift deployment configurations. Includes automated transformation scripts to create custom domain-specific MCP servers.

Exposes the automated feature engineering LangGraph agent as MCP tools, enabling dataset profiling, feature planning, and feature code execution through MCP-compatible hosts.

Enables AI agents to safely inspect, edit, and test code within a bounded repository environment to solve software engineering tasks and verify fixes.

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

This server integrates with the fastmcp library to expose the full range of NebulaBlock API functionalities as accessible tools, enabling seamless and efficient interaction within any MCP-compatible environment.

A language-neutral runtime for the SEP-2663 task lifecycle and io.sdar/taskExecution Provider Profile, delegating resource facts and side effects to versioned gRPC/Protobuf adapters. Implemented in strict TypeScript, it provides durable scheduling, recovery, and a full test suite for conformance.

Enables AI assistants to automatically analyze GitHub repositories and set up development environments by detecting tech stacks, installing dependencies, and verifying project builds. Provides safe tools for repository cloning, file system operations, package installation, and build verification through an allowlisted command system.

A minimal MCP server for running Python scripts on a remote machine over HTTP, exposing tools to Claude for script discovery, execution, and job status tracking.

A FastMCP server implementation that provides a standardized interface for accessing AI models hosted on Replicate's API, currently supporting image generation with customizable parameters.

Enables LLMs to safely execute pandas code for data analysis and generate interactive visualizations through MCP protocol.

Enable Claude (or any other LLM) to interactively debug your code (set breakpoints and evaluate expressions in stack frame). It's language-agnostic, assuming debugger console support and valid launch.json for debugging in VSCode.