INDIVIDUAL MCP TOOL

suggest_improvements

Generates ranked, simulated improvement suggestions for your token cascade.

signalaf.comnone authenticationAvailability not checked

LIVE ENDPOINT

https://signalaf.com/api/mcp

No auth detected

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

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

CONNECT WITH APPROVAL

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

Codex

~/.codex/config.toml

[mcp_servers.sigrank]
url = "https://signalaf.com/api/mcp"
enabled = true

Claude Code

.mcp.json

{
  "mcpServers": {
    "sigrank": {
      "type": "http",
      "url": "https://signalaf.com/api/mcp"
    }
  }
}

Claude Desktop

Settings → Connectors → Add custom connector

Name: sigrank
Remote MCP URL: https://signalaf.com/api/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": {
    "sigrank": {
      "url": "https://signalaf.com/api/mcp"
    }
  }
}

Visual Studio Code

.vscode/mcp.json

Add to Visual Studio Code

{
  "servers": {
    "sigrank": {
      "type": "http",
      "url": "https://signalaf.com/api/mcp"
    }
  }
}

Generic MCP

Client-specific MCP configuration

{
  "name": "sigrank",
  "transport": "streamable-http",
  "url": "https://signalaf.com/api/mcp"
}

MCP Inspector

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

rank_paste — Calculate SigRank cascade metrics from four non-negative token counts without submitting data.
get_leaderboard — Read the current public SigRank operator leaderboard.
get_operator — Read one public operator profile by codename.
simulate_change — Prescriptive 'what if' tool — takes your current 4 token pillars and proposed changes, runs the cascade on both, returns the exact Υ Yield delta, class change, and per-metric diffs.
diagnose_cascade — Analyzes your token cascade and diagnoses where you're leaking efficiency.
self_improve — Runs the full self-improvement cycle in one call: (1) computes your current cascade from 4 token pillars, (2) diagnoses efficiency leaks, (3) generates ranked improvement suggestions, (4) simulates the top suggestion, and (5) returns the complete cycle: diagnosis + suggestions + simulated impact of the best change.
rank_windows — Score up to 4 time windows (7d, 30d, 90d, all-time) in one call.
benchmark_me — Answers 'How good am I?