Side-by-Side Model Context Protocol Comparison
Churnkey vs GPU MCP Server
In-depth architectural comparison of the Churnkey and GPU MCP Server MCP servers. Compare execution transports, security boundaries, tool capabilities, quality scores, and ready-to-paste client installation snippets for Claude, Cursor, Windsurf, and VS Code.
At a Glance & Executive Verdict
Churnkey
Monitoring · Local stdio
Quality: 36/100 (Fair) | Auth: No auth required
GPU MCP Server
Monitoring · Local stdio
Quality: 48/100 (Fair) | Auth: No auth required
Verdict Summary: Choose Churnkey if you need specialized Monitoring tools running via a local process. Choose GPU MCP Server if your workspace requires Monitoring integration with local subprocess execution. Both servers can be configured concurrently in your client's
mcpServers manifest.Which MCP Server Should You Choose?
C
Choose Churnkey when:
- You need dedicated capabilities in the Monitoring domain.
- You prefer local stdio subprocess transport architecture.
- Your security boundary fits: No auth required (Free / Open Source).
G
Choose GPU MCP Server when:
- You need dedicated capabilities in the Monitoring domain.
- You prefer local stdio subprocess transport architecture.
- Your security boundary fits: No auth required (Free / Open Source).
- Primary tools included: list_gpus, get_gpu_metrics, get_gpu_processes.
Feature & Specification Comparison
Tools & Capabilities Breakdown
Churnkey Tools (0)
No explicit tool names declared in metadata yet. Check project README on main listing page.
GPU MCP Server Tools (4)
list_gpus
List all GPUs with utilization and memory info
get_gpu_metrics
Detailed metrics for a GPU by index or UUID
get_gpu_processes
PID-level GPU process attribution
gpu_summary
Aggregate stats across all devices
Ready-to-Paste Client Configurations
Paste either (or both) of these JSON server blocks into your client config file (e.g. claude_desktop_config.json or ~/.cursor/mcp.json).
Churnkey Configuration
GPU MCP Server Configuration