← softperceptron.com

INDIVIDUAL MCP TOOL

search_ai_models

Search the SoftPerceptron directory of AI models, autonomous agents and token/credit products.

softperceptron.comnone authenticationAvailability not checked

LIVE ENDPOINT

https://softperceptron.com/mcp

No auth detected

Connect to this endpoint to inspect the live schema for search_ai_models and invoke it with your own arguments.

Indexed input schema

{}

Risk classification

Inferred read-only · medium confidence · heuristic, not a guarantee.

  • A tool name, description or schema mentions credentials.

Parent server

softperceptron.com

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.softperceptron]
url = "https://softperceptron.com/mcp"
enabled = true
Claude Code

.mcp.json

{
  "mcpServers": {
    "softperceptron": {
      "type": "http",
      "url": "https://softperceptron.com/mcp"
    }
  }
}
Claude Desktop

Settings → Connectors → Add custom connector

Name: softperceptron
Remote MCP URL: https://softperceptron.com/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": {
    "softperceptron": {
      "url": "https://softperceptron.com/mcp"
    }
  }
}
Visual Studio Code

.vscode/mcp.json

Add to Visual Studio Code
{
  "servers": {
    "softperceptron": {
      "type": "http",
      "url": "https://softperceptron.com/mcp"
    }
  }
}
Generic MCP

Client-specific MCP configuration

{
  "name": "softperceptron",
  "transport": "streamable-http",
  "url": "https://softperceptron.com/mcp"
}
MCP Inspector

Run the official MCP Inspector locally and enter the indexed Streamable HTTP endpoint.

Related tools

  • get_ai_model — Get full details for one directory entry by id or common alias (e.g.
  • compare_ai_models — Compare two directory entries side by side — pricing, context window, modality and what each is best for.
  • 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.
  • 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.
  • list_gpus — List the GPUs supported by the VRAM calculator, with VRAM, memory bandwidth and power draw.