SoftPerceptron MCP Server

by softperceptron Your server? Claim it

answering

SoftPerceptron is answering right now. Last checked 12 min ago. It exposes 6 tools.

AI model/agent directory with pricing and comparisons, plus GPU VRAM fit and tokens/sec estimates.

Uptime history 71 hours of history · worst hour 75%

71 hours agonow

98.9%

Uptime 24h

90 of 91 checks

Tools

read from the server

1100 ms

Response time

average over 24h

open, no key

Access

streamable-http

SoftPerceptron missed one check this week

Everything else answered, so this is steady rather than shaky. We check every 15 minutes, which is how a one-off gets told apart from the start of a pattern, and how you hear about the next one within the hour instead of from your users.

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 12 min ago.

Claude Code Claude Desktop Codex Cursor VS Code

run in your terminal

claude mcp add mcp --transport http https://softperceptron.com/mcp

Settings → Connectors → Add custom connector, then paste this address

https://softperceptron.com/mcp

~/.codex/config.toml

[mcp_servers.mcp]
url = "https://softperceptron.com/mcp"

.cursor/mcp.json

{
  "mcpServers": {
    "mcp": {
      "url": "https://softperceptron.com/mcp"
    }
  }
}

.vscode/mcp.json

{
  "servers": {
    "mcp": {
      "type": "http",
      "url": "https://softperceptron.com/mcp"
    }
  }
}

Available tools 6

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

can

can_i_run_model

Check whether a specific open-weight model fits on a specific GPU: VRAM required, whether it fits, how much headroom, which quantization to use, and an estimated decode speed in tokens/sec. Use for questions like 'can an RTX 4090 run Llama 70B'.

compare

compare_ai_models

Compare two directory entries side by side — pricing, context window, modality and what each is best for. Both must be the same kind (model vs model, agent vs agent).

gpus

list_gpus

List the GPUs supported by the VRAM calculator, with VRAM, memory bandwidth and power draw.

local

list_local_models

List the open-weight models supported by the VRAM/can-i-run calculator, with parameter counts and what each is good for.

model

get_ai_model

Get full details for one directory entry by id or common alias (e.g. 'claude', 'gpt', 'gemini'). Returns pricing, specs, provider and links.

models

search_ai_models

Search the SoftPerceptron directory of AI models, autonomous agents and token/credit products. Returns pricing, specs and provider for each match. Use this to answer questions like 'what AI models are available', 'cheapest model with a big context window', or 'which coding agents exist'.

Endpoints

URL	Transport	State	Latency	Checked
https://softperceptron.com/mcp	streamable-http	answering	1013 ms	12 min ago

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SoftPerceptron — questions

Answers built from our own checks of this server.

What can SoftPerceptron do?

It exposes 6 tools, read directly from the server on our last check. Among them: can_i_run_model, compare_ai_models, get_ai_model, list_gpus, list_local_models, search_ai_models. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →

Is SoftPerceptron working right now?

We send a real MCP handshake every 15 minutes. Over the last 24 hours 90 of 91 checks got a reply (98.9%), average response time 1100 ms. The bar chart above shows every period we have measured.

How do I connect SoftPerceptron?

Copy the ready config from this page. We generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each in the form that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.

Does SoftPerceptron need an API key?

No. SoftPerceptron completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 6 of them are readable on this page. This is what we observed, not what the docs claim.

How fast is SoftPerceptron?

It answers our handshake in 1100 ms on average, which is faster than 4% of all working MCP servers we measure. That is on the slow side — worth knowing if the tool sits inside an interactive loop. The comparison comes from our own checks across the whole registry, every 15 minutes.