LIVE ENDPOINT
https://signalaf.com/api/mcp
Connect to this endpoint to inspect the live schema for get_operator 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.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.
Related tools
rank_paste— Calculate SigRank cascade metrics from four non-negative token counts without submitting data.get_leaderboard— Read the current public SigRank operator leaderboard.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.suggest_improvements— Generates ranked, simulated improvement suggestions for your token cascade.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?