CLIO Hdf5

io.github.iowarp由 GitHub 账号 iowarp 发布v2.2.7更新于 Oct 29, 2026

Open HDF5 files, browse groups, inspect datasets and attributes, and read or summarize data in...

已验证STDIO仅桌面文件与存储数据与分析

概览

AI 生成的概览

CLIO Kit 中的本地 MCP 服务器,让助手打开 HDF5 文件、浏览组、查看数据集与属性,并读取或汇总科学数据。

可以做什么
  • 打开 HDF5 文件并列出其中的组与结构
  • 查看数据集结构与属性
  • 读取完整或部分数据集,例如前若干个时间步
  • 汇总与分析存储在 HDF5 中的科学数据
适用场景
适合处理 HDF5 科学或 HPC 数据集的场景:希望助手在不写自定义脚本的情况下探查文件结构、检查属性并提取或汇总数据。
运行要求
作为本地进程在用户机器上运行(仅桌面端)。通过 clio-kit Python 包安装(通常使用 uv),并以 hdf5 服务器方式启动;未声明认证、环境变量或请求头。
安装前请注意
该包同时捆绑了许多其他 MCP 服务器(如 Slurm 作业提交、Spack 安装、文件压缩等),可能改动系统或提交作业,建议只启用需要的服务器。README 还提到分支启动选项属于开发路径,并非不可变的发布产物。

安装

在 SourceWeft 中

  1. 打开 控制台中的 CLIO Hdf5,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

README

CLIO Kit

[License: BSD-3-Clause] [PyPI version] [Python] [FastMCP] [CI] [Coverage]

[MCP Servers] [Ruff] [Type Checked] [Package Manager] [Security Audit]

CLIO Kit - Part of the IoWarp platform's tooling layer for AI agents. A comprehensive collection of tools, skills, plugins, and extensions. It ships 22 Model Context Protocol (MCP) servers for scientific computing and enables AI agents to interact with HPC resources, scientific data formats, and research datasets.

Website | IOWarp

Chat with us on Zulip or join us

Developed by [GRC Logo] Gnosis Research Center


❌ Without CLIO Kit

Working with scientific data and HPC resources requires manual scripting and tool-specific knowledge:

  • ❌ Write custom scripts for every HDF5/Parquet file exploration
  • ❌ Manually craft Slurm job submission scripts
  • ❌ Switch between multiple tools for data analysis
  • ❌ No AI assistance for scientific workflows
  • ❌ Repetitive coding for common research tasks

✅ With CLIO Kit

AI agents handle scientific computing tasks through natural language:

  • ✅ "Analyze the temperature dataset in this HDF5 file" - HDF5 MCP does it
  • ✅ "Submit this simulation to Slurm with 32 cores" - Slurm MCP handles it
  • ✅ "Find papers on neural networks from ArXiv" - ArXiv MCP searches
  • ✅ "Plot the results from this CSV file" - Plot MCP visualizes
  • ✅ "Optimize memory usage for this pandas DataFrame" - Pandas MCP optimizes
  • ✅ "Find all documents where pressure exceeds 200 kPa" - Agentic Search retrieves

One unified interface. 22 MCP servers. Hybrid search engine. 150+ specialized tools. Built for research.

CLIO Kit is part of the IoWarp platform's comprehensive tooling ecosystem for AI agents. It brings AI assistance to your scientific computing workflow—whether you're analyzing terabytes of HDF5 data, managing Slurm jobs across clusters, or exploring research papers. Built by researchers, for researchers, at Illinois Institute of Technology with NSF support.

Part of IoWarp Platform: CLIO Kit is the tooling layer of the IoWarp platform, providing skills, plugins, and extensions for AI agents working in scientific computing environments.

One simple command. Production-ready, fully typed, BSD-3-Clause licensed, and live-tested in real HPC environments.

🚀 Quick Installation

One Command for Any Server

bash
# Install the released CLI into its own persistent tool environmentuv tool install 'clio-kit==2.4.3'# If uv reports that its executable directory is not on PATH:uv tool update-shell
# List all 23 available MCP serversclio-kit mcp-servers
# Run any installed serverclio-kit mcp-server hdf5clio-kit mcp-server pandasclio-kit mcp-server slurm
# Agentic search — hybrid retrieval for scientific corporaclio-kit search serve               # Start search API serverclio-kit search query --namespace local_fs --q "pressure > 200 kPa"
# AI prompts also availableclio-kit prompts                    # List all promptsclio-kit prompt code-coverage-prompt # Use a prompt

uv tool install keeps CLIO Kit in a persistent, isolated tool environment. Use uvx --from 'clio-kit==2.4.3' clio-kit ... only for a temporary, one-shot invocation.

Released clio-kit wheels execute each embedded MCP server from that server's shipped uv.lock. The launcher uses a source-and-lock-addressed environment under the user cache, installs only production dependencies, and refuses to resolve an embedded server whose lock is missing. The --branch launcher option is an explicit development path and is not an immutable release-artifact path.

The root wheel also ships machine-readable user contracts for the locked JARVIS, SLURM, Spack, and Scientific Catalog servers. These artifacts are generated from real stdio tools/list exchanges and include canonical SHA-256 digests for downstream federation gates:

bash
clio-kit mcp-contractsclio-kit mcp-contract clio-kit-jarvis-user-v3.5clio-kit mcp-contract clio-kit-slurm-user-v3clio-kit mcp-contract clio-kit-spack-user-v2.1clio-kit mcp-contract clio-kit-scientific-catalog-user-v1.1
Install in Cursor

Add to your Cursor ~/.cursor/mcp.json:

json
{  "mcpServers": {    "hdf5-mcp": {      "command": "clio-kit",      "args": ["mcp-server", "hdf5"]    },    "pandas-mcp": {      "command": "clio-kit",      "args": ["mcp-server", "pandas"]    },    "slurm-mcp": {      "command": "clio-kit",      "args": ["mcp-server", "slurm"]    }  }}

See Cursor MCP docs for more info.

Install in Claude Code
bash
# Add HDF5 MCPclaude mcp add hdf5-mcp -- clio-kit mcp-server hdf5
# Add Pandas MCPclaude mcp add pandas-mcp -- clio-kit mcp-server pandas
# Add Slurm MCPclaude mcp add slurm-mcp -- clio-kit mcp-server slurm

See Claude Code MCP docs for more info.

Install in VS Code

Add to your VS Code MCP config:

json
"mcp": {  "servers": {    "hdf5-mcp": {      "type": "stdio",      "command": "clio-kit",      "args": ["mcp-server", "hdf5"]    },    "pandas-mcp": {      "type": "stdio",      "command": "clio-kit",      "args": ["mcp-server", "pandas"]    }  }}

See VS Code MCP docs for more info.

Install in Claude Desktop

Edit claude_desktop_config.json:

json
{  "mcpServers": {    "hdf5-mcp": {      "command": "clio-kit",      "args": ["mcp-server", "hdf5"]    },    "arxiv-mcp": {      "command": "clio-kit",      "args": ["mcp-server", "arxiv"]    }  }}

See Claude Desktop MCP docs for more info.

Available Packages

The version below is each MCP server's agent-facing contract version, not the containing clio-kit wheel version. JARVIS 3.4 and SLURM 3.0 have contracts redesigned for agent use. Spack is at 2.1, while the other contracts retain their existing 2.x identities until a focused upgrade.

The Spack install contract makes concretization explicit: reuse=true passes spack install --reuse, while reuse=false passes spack install --fresh. Agents should discover first, install only when needed, then pass the exact spack_locate result to JARVIS for runtime loading. A find with no installed match is normal typed data (count=0, packages=[]); locate reports the distinct not_installed semantic, while real Spack failures remain errors.

📦 Package📌 Ver🔧 System📋 Description⚡ Install Command
adios2.2.3Data I/ORead data using ADIOS2 engineclio-kit mcp-server adios
arxiv2.2.3ResearchFetch research papers from ArXivclio-kit mcp-server arxiv
chronolog2.0.1LoggingLog and retrieve data from ChronoLogclio-kit mcp-server chronolog
compression2.2.3UtilitiesFile compression with gzipclio-kit mcp-server compression
darshan2.2.3PerformanceI/O performance trace analysisclio-kit mcp-server darshan
geo2.2.3GeospatialRender GeoJSON vector layers with basemapsclio-kit mcp-server geo
geojson2.2.3GeospatialInspect, validate, and summarize GeoJSONclio-kit mcp-server geojson
hdf52.2.3Data I/OHPC-optimized scientific data with 27 tools, AI insights, caching, streamingclio-kit mcp-server hdf5
jarvis3.6.2WorkflowDurable pipeline, bounded package discovery, progress, artifact, and service-runtime managementclio-kit mcp-server jarvis
lmod2.2.3EnvironmentEnvironment module managementclio-kit mcp-server lmod
ndp2.2.3Data ProtocolSearch and discover datasets across CKAN instancesclio-kit mcp-server ndp
node-hardware2.2.3SystemSystem hardware informationclio-kit mcp-server node-hardware
pandas2.2.3Data AnalysisCSV data loading and filteringclio-kit mcp-server pandas
parallel-sort2.2.3ComputingLarge file sortingclio-kit mcp-server parallel-sort
paraview2.2.3VisualizationScientific 3D visualization and analysisclio-kit mcp-server paraview
parquet2.2.3Data I/ORead Parquet file columnsclio-kit mcp-server parquet
plot2.2.3VisualizationGenerate plots from CSV dataclio-kit mcp-server plot
sac2.2.3SeismologyAnalyze SAC waveforms and archivesclio-kit mcp-server sac
seismic2.2.3SeismologyAnalyze earthquake catalogs and sequencesclio-kit mcp-server seismic
scientific-catalog1.1.2DiscoveryOperator-owned scientific dataset discoveryclio-kit mcp-server scientific-catalog
slurm3.0.0HPCJob submission and managementclio-kit mcp-server slurm
spack2.1.0Package ManagementStructured package discovery, installation, and locationclio-kit mcp-server spack
terrain2.2.3GeospatialAnalyze DEMs and terrain point cloudsclio-kit mcp-server terrain
web1.0.0WebFetch a URL to Markdown and search the webclio-kit mcp-server web

Agentic Search

Hybrid retrieval engine for scientific corpora — combines lexical (BM25), vector, graph, and scientific search (numeric range, unit matching, formula targeting) over namespaced document collections. DuckDB storage, FastAPI, async job queue, OpenTelemetry tracing, Prometheus metrics.

bash
# Start the search API serverclio-kit search serve
# Index documents from a namespaceclio-kit search index --namespace local_fs
# Query with scientific operatorsclio-kit search query --namespace local_fs --q "pressure between 190 and 360 kPa"
# List indexed documentsclio-kit search list --namespace local_fs

API endpoints: /query, /jobs/index, /documents, /health, /metrics — full docs


📖 Usage Examples

HDF5: Scientific Data Analysis

"What datasets are in climate_simulation.h5? Show me the temperature field structure and read the first 100 timesteps."

Tools used: open_file, analyze_dataset_structure, read_partial_dataset, list_attributes

Slurm: HPC Job Management

"Submit simulation.py to Slurm with 32 cores, 64GB memory, 24-hour runtime. Monitor progress and retrieve output when complete."

Tools used: submit_slurm_job, check_job_status, get_job_output

ArXiv: Research Discovery

"Find the latest papers on diffusion models from ArXiv, get details on the top 3, and export citations to BibTeX."

Tools used: search_arxiv, get_paper_details, export_to_bibtex, download_paper_pdf

Pandas: Data Processing

"Load sales_data.csv, clean missing values, compute statistics by region, and save as Parquet with compression."

Tools used: load_data, handle_missing_data, groupby_operations, save_data

Plot: Data Visualization

"Create a line plot showing temperature trends over time from weather.csv with proper axis labels."

Tools used: line_plot, data_info

Agentic Search: Scientific Retrieval

"Find all chunks mentioning pressure above 200 kPa in the local_fs namespace."

CLI: clio-kit search query --namespace local_fs --q "pressure > 200 kPa"


🚨 Troubleshooting

Server Not Found Error

If clio-kit mcp-server <server-name> fails:

bash
# Verify server name is correctclio-kit mcp-servers
# Common names: hdf5, pandas, slurm, arxiv (not hdf5-mcp, pandas-mcp)
Import Errors or Missing Dependencies

For development or local testing:

bash
cd clio-kit-mcp-servers/hdf5uv sync --all-extras --devuv run hdf5-mcp
uv or clio-kit Command Not Found

Install uv package manager:

bash
# Linux/macOScurl -LsSf https://astral.sh/uv/install.sh | sh
# Windowspowershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
# Or via pippip install uv

Then install CLIO Kit persistently and expose uv's tool directory:

bash
uv tool install 'clio-kit==2.4.3'uv tool update-shell

Team

Sponsored By

[NSF Logo] NSF (National Science Foundation) - Supporting scientific computing research and AI integration initiatives

we welcome more sponsorships. please contact the Principal Investigator

Ways to Contribute

  • Submit Issues: Report bugs or request features via GitHub Issues
  • Develop New MCPs: Add servers for your research tools (CONTRIBUTING.md)
  • Improve Documentation: Help make guides clearer
  • Share Use Cases: Tell us how you're using CLIO Kit in your research

Full Guide: CONTRIBUTING.md

Community & Support


来源:README.md,提交 93e41d7

工具

0
SourceWeft 尚未在沙箱中启动过该软件包,因此其工具未知。

版本历史

3
  1. v2.2.7最新Oct 29, 2026
  2. v2.2.6Oct 9, 2026
  3. v2.2.3Sep 16, 2026

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