Learning Resources

inference-cost-optimizer.com

An MCP server that lists available documentation pages and retrieves the full content of specific pages.

1 endpoint2 known toolsFirst detected October 21, 2026Last detected October 21, 2026

ENDPOINT 1

https://inference-cost-optimizer.com/mcp

No auth detected

Capabilities

loggingtools.listChangedresources.listChangedprompts.listChanged

Retrieves the full content and details of a specific documentation page.

Inferred read-only

Lists all available documentation pages with their categories and basic information.

Inferred read-only

CONNECT WITH APPROVAL

Review this server and its permissions before adding it. Secret placeholders must be set locally.

Codex

~/.codex/config.toml

[mcp_servers.ico-docs]
url = "https://inference-cost-optimizer.com/mcp"
enabled = true

Claude Code

.mcp.json

{
  "mcpServers": {
    "ico-docs": {
      "type": "http",
      "url": "https://inference-cost-optimizer.com/mcp"
    }
  }
}

Claude Desktop

Settings → Connectors → Add custom connector

Name: ico-docs
Remote MCP URL: https://inference-cost-optimizer.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": {
    "ico-docs": {
      "url": "https://inference-cost-optimizer.com/mcp"
    }
  }
}

Visual Studio Code

.vscode/mcp.json

Add to Visual Studio Code

{
  "servers": {
    "ico-docs": {
      "type": "http",
      "url": "https://inference-cost-optimizer.com/mcp"
    }
  }
}

Generic MCP

Client-specific MCP configuration

{
  "name": "ico-docs",
  "transport": "streamable-http",
  "url": "https://inference-cost-optimizer.com/mcp"
}

MCP Inspector

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

TRUST AND VERIFICATION EVIDENCE

Checking the associated registrable domain. The BuiltWith key remains server-side.

Indexed

Evidence is source-attributed and does not guarantee that a third-party server is safe. Risk labels are conservative metadata heuristics.