Back to MCP Servers
MCP Server

MCP Server

Public
zchaffee1/mcp-server

Implements Model Context Protocol for efficient HDF5 file operations, Slurm job management, node hardware info retrieval, and data compression with gzip and zlib support.

python
0 tools
May 30, 2025
Updated Jun 4, 2025

Supercharge Your AI with MCP Server

MCP Server

Unlock the full potential of MCP Server through LangDB's AI Gateway. Get enterprise-grade security, analytics, and seamless integration with zero configuration.

Unified API Access
Complete Tracing
Instant Setup
Get Started Now

Free tier available • No credit card required

Instant Setup
99.9% Uptime
10,000+Monthly Requests

mcp-server

By: Zack Chaffee A20478873

A server implementing Model Coupling Protocol (MCP) capabilities for HDF5 file operations and Slurm job management.

Features

HDF5 file operations:

  • Read datasets
  • List file contents

Slurm job management:

  • Submit jobs
  • Check job status

Node Hardware Operations

  • Get CPU information
  • Get memory information
  • Get disk information
  • Get comprehensive system information

Compression Operations

  • Compress string data with gzip or zlib
  • Compress files with gzip or zlib
  • Decompress data

Initialization

Once you clone this reponsitory cd into it

After this hwe will create a virtual enviornment and install all dependincies:

uv venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
uv pip install -e .
uv pip install -e ".[test]"

Running

To startup the server run:

python -m src.server

This will autoclocate the server at http://localhost:8000.

Endpoints

  • POST /mcp: Main endpoint for MCP requests
  • GET /health: Health check endpoint

Examples:

import httpx async with httpx.AsyncClient() as client: # Read a dataset response = await client.post("http://localhost:8000/mcp", json={ "capability": "hdf5", "action": "read_dataset", "parameters": { "file_path": "/path/to/data.h5", "dataset_path": "/path/to/dataset" } }) # List contents response = await client.post("http://localhost:8000/mcp", json={ "capability": "hdf5", "action": "list_contents", "parameters": { "file_path": "/path/to/data.h5", "group_path": "/" } })
curl -X POST http://localhost:8000/mcp \ -H "Content-Type: application/json" \ -d '{ "jsonrpc": "2.0", "method": "mcp/listTools", "params": {}, "id": "1" }'

Testing

For testing rung:

pytest

For tests with coverage:

pytest --cov=src
Publicly Shared Threads0

Discover shared experiences

Shared threads will appear here, showcasing real-world applications and insights from the community. Check back soon for updates!

Share your threads to help others
Related MCPs5
  • mcp-server-asana

    Enables seamless interaction with Asana API via Model Context Protocol, providing advanced task, pro...

    22 tools
    Added May 30, 2025
  • MCP SSH Server

    Secure Model Context Protocol (MCP) SSH server enabling remote command execution, file and directory...

    Added May 30, 2025
  • Ramp MCP Server

    Model Context Protocol server enabling efficient retrieval, analysis, and task execution on Ramp dat...

    Added May 30, 2025
  • MCP Filesystem Server

    Model Context Protocol server enabling secure, efficient filesystem operations with smart context ma...

    Added May 30, 2025
  • Kintone MCP Server

    Enables seamless integration with kintone via Model Context Protocol, offering comprehensive capabil...

    25 tools
    Added May 30, 2025