Agent Toolkit - MCP Servers, Clients, and Tools for AI Agents
Project description
Agent Toolkit
Agent Toolkit - Part of the IoWarp platform's tooling layer for AI agents. A comprehensive collection of tools, skills, plugins, and extensions. Currently featuring 15+ Model Context Protocol (MCP) servers for scientific computing, with plans to expand to additional agent capabilities. Enables AI agents to interact with HPC resources, scientific data formats, and research datasets.
Chat with us on Zulip or join us
Developed by Gnosis Research Center
❌ Without Agent Toolkit
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 Agent Toolkit
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
One unified interface. 15 MCP servers. 150+ specialized tools. Built for research.
Agent Toolkit 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: Agent Toolkit 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, MIT licensed, and beta-tested in real HPC environments.
🚀 Quick Installation
One Command for Any Server
# List all 15 available MCP servers
uvx agent-toolkit
# Run any server instantly
uvx agent-toolkit hdf5
uvx agent-toolkit pandas
uvx agent-toolkit slurm
Install in Cursor
Add to your Cursor ~/.cursor/mcp.json:
{
"mcpServers": {
"hdf5-mcp": {
"command": "uvx",
"args": ["agent-toolkit", "hdf5"]
},
"pandas-mcp": {
"command": "uvx",
"args": ["agent-toolkit", "pandas"]
},
"slurm-mcp": {
"command": "uvx",
"args": ["agent-toolkit", "slurm"]
}
}
}
See Cursor MCP docs for more info.
Install in Claude Code
# Add HDF5 MCP
claude mcp add hdf5-mcp -- uvx agent-toolkit hdf5
# Add Pandas MCP
claude mcp add pandas-mcp -- uvx agent-toolkit pandas
# Add Slurm MCP
claude mcp add slurm-mcp -- uvx agent-toolkit slurm
See Claude Code MCP docs for more info.
Install in VS Code
Add to your VS Code MCP config:
"mcp": {
"servers": {
"hdf5-mcp": {
"type": "stdio",
"command": "uvx",
"args": ["agent-toolkit", "hdf5"]
},
"pandas-mcp": {
"type": "stdio",
"command": "uvx",
"args": ["agent-toolkit", "pandas"]
}
}
}
See VS Code MCP docs for more info.
Install in Claude Desktop
Edit claude_desktop_config.json:
{
"mcpServers": {
"hdf5-mcp": {
"command": "uvx",
"args": ["agent-toolkit", "hdf5"]
},
"arxiv-mcp": {
"command": "uvx",
"args": ["agent-toolkit", "arxiv"]
}
}
}
See Claude Desktop MCP docs for more info.
Available Packages
| 📦 Package | 📌 Ver | 🔧 System | 📋 Description | ⚡ Install Command |
|---|---|---|---|---|
adios |
1.0 | Data I/O | Read data using ADIOS2 engine | uvx agent-toolkit adios |
arxiv |
1.0 | Research | Fetch research papers from ArXiv | uvx agent-toolkit arxiv |
chronolog |
1.0 | Logging | Log and retrieve data from ChronoLog | uvx agent-toolkit chronolog |
compression |
1.0 | Utilities | File compression with gzip | uvx agent-toolkit compression |
darshan |
1.0 | Performance | I/O performance trace analysis | uvx agent-toolkit darshan |
hdf5 |
2.1 | Data I/O | HPC-optimized scientific data with 27 tools, AI insights, caching, streaming | uvx agent-toolkit hdf5 |
jarvis |
1.0 | Workflow | Data pipeline lifecycle management | uvx agent-toolkit jarvis |
lmod |
1.0 | Environment | Environment module management | uvx agent-toolkit lmod |
ndp |
1.0 | Data Protocol | Search and discover datasets across CKAN instances | uvx agent-toolkit ndp |
node-hardware |
1.0 | System | System hardware information | uvx agent-toolkit node-hardware |
pandas |
1.0 | Data Analysis | CSV data loading and filtering | uvx agent-toolkit pandas |
parallel-sort |
1.0 | Computing | Large file sorting simulation | uvx agent-toolkit parallel-sort |
parquet |
1.0 | Data I/O | Read Parquet file columns | uvx agent-toolkit parquet |
plot |
1.0 | Visualization | Generate plots from CSV data | uvx agent-toolkit plot |
slurm |
1.0 | HPC | Job submission simulation | uvx agent-toolkit slurm |
📖 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
🚨 Troubleshooting
Server Not Found Error
If uvx agent-toolkit <server-name> fails:
# Verify server name is correct
uvx agent-toolkit
# Common names: hdf5, pandas, slurm, arxiv (not hdf5-mcp, pandas-mcp)
Import Errors or Missing Dependencies
For development or local testing:
cd agent-toolkit-mcp-servers/hdf5
uv sync --all-extras --dev
uv run hdf5-mcp
uvx Command Not Found
Install uv package manager:
# Linux/macOS
curl -LsSf https://astral.sh/uv/install.sh | sh
# Windows
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
# Or via pip
pip install uv
Team
- Gnosis Research Center (GRC) - Illinois Institute of Technology | Lead
- HDF Group - Data format and library developers | Industry Partner
- University of Utah - Research collaboration | Domain Science Partner
Sponsored By
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 Agent Toolkit in your research
Full Guide: CONTRIBUTING.md
Community & Support
- Chat: Zulip Community
- Join: Invitation Link
- Issues: GitHub Issues
- Discussions: GitHub Discussions
- Website: https://iowarp.ai/agent-toolkit/
- Project: IOWarp Project
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file iowarp_agent_toolkit-1.0.3.tar.gz.
File metadata
- Download URL: iowarp_agent_toolkit-1.0.3.tar.gz
- Upload date:
- Size: 9.9 MB
- Tags: Source
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/6.1.0 CPython/3.13.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
5932cd27605780aaac1daa535d76b6fa436764ee98114662da35323fbe6721ce
|
|
| MD5 |
0e6f4b78ce22c6a1c7dd8561f1184585
|
|
| BLAKE2b-256 |
2959d24167772296f1bc0695cffc7077d607027ea764d77c22413e0582743ec1
|
Provenance
The following attestation bundles were made for iowarp_agent_toolkit-1.0.3.tar.gz:
Publisher:
publish.yml on iowarp/agent-toolkit
-
Statement:
-
Statement type:
https://in-toto.io/Statement/v1 -
Predicate type:
https://docs.pypi.org/attestations/publish/v1 -
Subject name:
iowarp_agent_toolkit-1.0.3.tar.gz -
Subject digest:
5932cd27605780aaac1daa535d76b6fa436764ee98114662da35323fbe6721ce - Sigstore transparency entry: 702293320
- Sigstore integration time:
-
Permalink:
iowarp/agent-toolkit@eae891e6e0537226aabdecca91c1ddfbbaa8f101 -
Branch / Tag:
refs/tags/v1.0.3 - Owner: https://github.com/iowarp
-
Access:
public
-
Token Issuer:
https://token.actions.githubusercontent.com -
Runner Environment:
github-hosted -
Publication workflow:
publish.yml@eae891e6e0537226aabdecca91c1ddfbbaa8f101 -
Trigger Event:
push
-
Statement type:
File details
Details for the file iowarp_agent_toolkit-1.0.3-py3-none-any.whl.
File metadata
- Download URL: iowarp_agent_toolkit-1.0.3-py3-none-any.whl
- Upload date:
- Size: 10.2 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/6.1.0 CPython/3.13.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
2bf143391f2a344aad4a023ec0a7ab2b98edafc0e8910a003d5152a75b081b8d
|
|
| MD5 |
d2a991f007d3cbd12a67bdb252dec8e1
|
|
| BLAKE2b-256 |
97a0a2a298c3c63dbea88ceeea3833d2fdb49f9c083032ec9934d9df358777cf
|
Provenance
The following attestation bundles were made for iowarp_agent_toolkit-1.0.3-py3-none-any.whl:
Publisher:
publish.yml on iowarp/agent-toolkit
-
Statement:
-
Statement type:
https://in-toto.io/Statement/v1 -
Predicate type:
https://docs.pypi.org/attestations/publish/v1 -
Subject name:
iowarp_agent_toolkit-1.0.3-py3-none-any.whl -
Subject digest:
2bf143391f2a344aad4a023ec0a7ab2b98edafc0e8910a003d5152a75b081b8d - Sigstore transparency entry: 702293325
- Sigstore integration time:
-
Permalink:
iowarp/agent-toolkit@eae891e6e0537226aabdecca91c1ddfbbaa8f101 -
Branch / Tag:
refs/tags/v1.0.3 - Owner: https://github.com/iowarp
-
Access:
public
-
Token Issuer:
https://token.actions.githubusercontent.com -
Runner Environment:
github-hosted -
Publication workflow:
publish.yml@eae891e6e0537226aabdecca91c1ddfbbaa8f101 -
Trigger Event:
push
-
Statement type: