INDIVIDUAL MCP TOOL
procurement_channels
List buy-side procurement entities (OEMs, distributors, VARs, brokers, colo, etc.) with how_to_buy and buy_url.
LIVE ENDPOINT
https://mcp.rauta.ai/mcp
Connect to this endpoint to inspect the live schema for procurement_channels and invoke it with your own arguments.
Indexed input schema
{}Risk classification
Inferred read-only · medium confidence · heuristic, not a guarantee.
- No write-capable action terms were found; this is not proof that invocation has no side effects.
Parent server
CONNECT WITH APPROVAL
Client installation
Review this server and its permissions before adding it. Secret placeholders must be set locally.
Codex
~/.codex/config.toml
[mcp_servers.rauta-market]
url = "https://mcp.rauta.ai/mcp"
enabled = true
Claude Code
.mcp.json
{
"mcpServers": {
"rauta-market": {
"type": "http",
"url": "https://mcp.rauta.ai/mcp"
}
}
}
Claude Desktop
Settings → Connectors → Add custom connector
Name: rauta-market
Remote MCP URL: https://mcp.rauta.ai/mcp
Add this remote URL as a custom connector in Claude Desktop. Availability depends on the user plan and workspace policy.
Cursor
.cursor/mcp.json
{
"mcpServers": {
"rauta-market": {
"url": "https://mcp.rauta.ai/mcp"
}
}
}
Visual Studio Code
.vscode/mcp.json
Add to Visual Studio Code{
"servers": {
"rauta-market": {
"type": "http",
"url": "https://mcp.rauta.ai/mcp"
}
}
}
Generic MCP
Client-specific MCP configuration
{
"name": "rauta-market",
"transport": "streamable-http",
"url": "https://mcp.rauta.ai/mcp"
}
MCP Inspector
Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.
Related tools
list_gpus— List GPU types currently available across providers, with per-provider price, region, and availability.lookup_model— Look up a Hugging Face model: parameter count, context window, VRAM needed at fp16/int8/int4, and which market GPUs can fit it.recommend_workload— Recommend the best provider+GPU for a workload.leaderboard— Inference leaderboard for one category: 'cloud' (GPU rental providers), 'hardware' (raw GPU types), or 'inference' (serverless inference APIs).cold_start_stats— Real provisioning (cold-start) latency AND supply health per provider+GPU: p50/p95/min provision time, success/error counts, failure rate, and — for every failing bucket — the actionable cause.compare_providers— Cross-provider time series of TTFT p50/p95, latency, tokens/sec and availability.ask_advisor— Ask the Rauta Advisor for a single opinionated, prose recommendation grounded in the same live data.hardware_catalog— Look up purchase / ownership prices for AI accelerators (H100, B200, GB200 NVL72, MI300X, etc.).