🔬 IOWarp MCPs

Darshan MCP analyzes HPC application I/O performance through comprehensive trace file analysis, performance bottleneck identification, timeline analysis, and comparative reporting tools for optimizing scientific computing I/O patterns.

Slurm MCP enables high-performance computing workflows through comprehensive job submission, monitoring, and resource management on HPC clusters, featuring intelligent scheduling, array job support, interactive node allocation, and real-time performance analytics.

Parallel Sort MCP processes large log files with high-performance sorting, advanced multi-condition filtering, pattern detection, and statistical analysis capabilities, supporting multiple export formats for comprehensive log management workflows.

Compression MCP delivers efficient file compression operations using industry-standard gzip algorithms with detailed analytics, comprehensive error management, and storage optimization capabilities for data archival and transfer operations.

Pandas MCP transforms data analysis workflows by providing comprehensive statistical analysis, data cleaning and transformation, time series operations, multi-format I/O support, and intelligent data quality assessment for efficient data science workflows.

Jarvis MCP manages data-centric pipeline lifecycles using the Jarvis framework, featuring pipeline creation, package management, configuration updates, environment building, and execution capabilities for high-performance computing and data science.

HDF5 MCP provides comprehensive scientific data access through hierarchical data structure inspection, dataset previewing, and complete data reading with seamless integration for multi-dimensional arrays and attribute handling in scientific computing.

ADIOS MCP enables scientific simulation data access through ADIOS2 framework with read-only BP5 file support, variable inspection, attribute reading, and step-based data handling for high-performance scientific computing workflows.

Plot MCP creates data visualizations from CSV and Excel files with intelligent data processing capabilities, supporting line plots, bar charts, scatter plots, histograms, and correlation heatmaps for comprehensive data analysis.

Parquet MCP accesses columnar data files with high-performance PyArrow-based reading, automatic schema detection, column-based operations, and analytics integration supporting data science workflows and big data processing capabilities.

ArXiv MCP provides comprehensive research paper access from ArXiv preprint repository with multi-dimensional search capabilities, paper analysis tools, citation management, PDF access, and research workflow support for academic literature review.

Lmod MCP manages environment modules using the Lmod system with advanced search capabilities, atomic operations, environment collections, and HPC integration for reproducible scientific computing and development environments.

ChronoLog MCP integrates with ChronoLog distributed shared log store for capturing, managing, and retrieving conversational interactions with structured event formatting, session management, and real-time event processing capabilities.

Node Hardware MCP monitors system hardware information including CPU specifications, memory usage, disk performance, network interfaces, GPU details, and sensor data for both local and remote nodes via SSH connections.