SigRank MCP

🏆 SigRank is live: signalaf.com — the leaderboard for how efficiently you use AI, not how much. Run npx sigrank to see your cascade now. _Token counts only. Never your prompts._

The yield cascade + live leaderboard as MCP tools any agent can call.

For all builders, burners and 10xers.

![npm version](https://www.npmjs.com/package/sigrank) ![CI](https://github.com/SunrisesIllNeverSee/sigrank-mcp/actions/workflows/ci.yml) ![CodeQL](https://github.com/SunrisesIllNeverSee/sigrank-mcp/actions/workflows/codeql.yml) ![audit](https://github.com/SunrisesIllNeverSee/sigrank-mcp/actions/workflows/dependency-audit.yml) ![Dependabot](https://github.com/SunrisesIllNeverSee/sigrank-mcp/network/dependencies) ![license](./LICENSE) ![platform](https://nodejs.org) ![live](https://signalaf.com) ![SunrisesIllNeverSee/sigrank-mcp MCP server](https://glama.ai/mcp/servers/SunrisesIllNeverSee/sigrank-mcp) ![Smithery](https://smithery.ai/servers/burnmydays/sigrank)

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The SigRank ecosystem
Quickstart
Install from GitHub
Install via Smithery
Commands
MCP Server mode
Cascade math
Token Pillars
Platform adapters
Privacy
Env vars
Dev / test
File map
Contributing
License

| The board | Your operator profile | | :-----------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------: | | ![SigRank leaderboard](https://signalaf.com/board/all) | ![SigRank operator profile](https://signalaf.com) | | Every operator ranked by Υ Yield — the architecture of the cascade, not raw spend | Cascade layer, class, and fingerprint — derived from four token counts |

Run sigrank enroll then sigrank submit to get ranked and claim your public profile at signalaf.com.

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The SigRank ecosystem

| Repo | What it is | Install | |------|-----------|---------| | sigrank-mcp (this repo) | The instrument — extracts 4 token pillars, computes the cascade, submits to the leaderboard. MCP server + TUI dashboard. | npx sigrank | | sigrank-app | The leaderboard — signalaf.com. Privacy-preserving operator profiles, class tiers, board rankings. | signalaf.com | | signaf | The coach — reads your session logs, builds a taste profile, measures ASI, coaches you on token efficiency. | npx @burnmydays/signaf | | sigrank-vscode | The IDE extension — see your cascade metrics inline in VS Code. | code --install-extension sigrank.sigrank | | fundscore | The repo scorer — investor-readiness scoring for GitHub repos. CLI + MCP server. | npx fundscore |

Also in the MO§ES™ suite

| Site | What it is | | ---- | ---------- | | SIGNOMY | Governed AI agent marketplace where ranked agents form teams, fill slots, run missions, and earn revenue under constitutional protocol. Agents are free. Operators pay. | | MO§ES | The governance framework that underpins SigRank, SIGNOMY, and all governed agent operations. Structural accountability for agentic systems. |

Quickstart — 3 steps to the board

# 1. Install (pulls ccusage + tokscale automatically — no separate installs)
npm install -g sigrank

# 2. Sign in (paste a connect code from signalaf.com → Settings → New key)
sigrank enroll

# 3. Submit your cascade to the board
sigrank submit

# (cautious? see exactly what would be sent — four counts + a signature — sending nothing)
sigrank submit --dry-run

That's it. sigrank reads your local AI session logs on-device, derives your token cascade (Υ Yield, Leverage, Velocity, 10xDEV), and publishes to signalaf.com. No paste, no transcript content — only the four token counts leave your machine.

Or just explore without signing in:

sigrank          # launches the full tabbed TUI (dashboard, compare, board, watch)
npx sigrank board --once    # print the live leaderboard once

Install from GitHub

git clone https://github.com/SunrisesIllNeverSee/sigrank-mcp.git
cd sigrank-mcp
npm install

# Run CLI
node index.mjs                        # TUI (if TTY)
node cli.mjs board --once             # leaderboard one-shot

# Or link globally for `sigrank` command
npm link
sigrank

Repo: SunrisesIllNeverSee/sigrank-mcp Site: signalaf.com npm: sigrank Smithery: smithery.ai/servers/burnmydays/sigrank Glama: glama.ai/mcp/servers/SunrisesIllNeverSee/sigrank-mcp

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Install via Smithery

SigRank is available on Smithery as a stdio MCP bundle — one-click install for Claude Desktop, Cursor, and other MCP clients.

Smithery CLI

# Install Smithery CLI
npm install -g smithery

# Connect to SigRank (downloads the MCPB bundle locally)
smithery mcp add burnmydays/sigrank --id sigrank

# List available tools
smithery tool list sigrank

# Call a tool
smithery tool call sigrank get_leaderboard '{}'
smithery tool call sigrank rank_paste '{"text": "1000000 500000 50000 800000"}'

Claude Desktop (via Smithery)

Go to smithery.ai/servers/burnmydays/sigrank
Click Install
Smithery handles the rest — no manual config editing

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Commands

⊙ SigRank CLI  v0.0.177

Default (no args)
  sigrank              unified dashboard: cascade + token pillars + board

Commands
  enroll                   sign in: paste a connect code (get one at signalaf.com → Settings)
  submit                   publish your verified runs to the board (sign in first)
  board                    live leaderboard (refreshes every 30s)
  board --window 7d        board for a specific window (7d, 30d, 90d, all)
  board --once             print once and exit
  compare                  raw pillar audit: tokenpull vs ccusage vs token-dash vs tokscale
  compare --platform codex compare for a specific platform
  tui                      full tabbed TUI: Dashboard / Trends / Compare / Board / Watch / Connect
  tui --platform codex     TUI with a different default platform
  watch                    live tune meter — ALL active platforms × all windows, every 30s
  watch --platform codex   watch only one platform (optional filter)
  watch --window 7d        watch only one window (optional filter)

Options
  --window    7d · 30d · 90d · all  (default: 30d for board; all windows for watch)
  --platform  claude · codex · amp · gemini · opencode · goose · …
  --refresh   poll interval in seconds (default: 30)
  --once      print once and exit (board only)

For AI clients (not typeable)
  In a piped/non-TTY context, sigrank is an MCP stdio server.
  AI clients (Claude, Cursor, …) call its tools automatically — these are
  NOT shell commands. Humans use the commands above.

Examples
  sigrank                        # unified dashboard
  sigrank board                  # live leaderboard
  sigrank compare                # pillar audit (claude)
  sigrank compare --platform codex
  sigrank watch --window 7d --refresh 60
  sigrank board --window all --once

The TUI is the whole app

Launch it and sign in inside it:

npx sigrank

Six tabs. Keys: 1-6 or ← → to switch · R refresh · Q quit.

| Tab | Key | Content | | ------------- | --- | ------------------------------------------------------------------------------------------------------------------------------------ | | Dashboard | 1 | Cascade table (all platforms × windows + combined) · Υ sparklines · token composition bars · mini board | | Trends | 2 | Every metric across windows — sub-views: You / Platform / Field | | Compare | 3 | 4-source pillar audit (tokenpull vs ccusage vs token-dash vs tokscale) · delta % · cascade metrics per source · cache read bar chart | | Board | 4 | Full leaderboard with all fields · [W] cycles window (7d/30d/90d/all) | | Watch | 5 | In-TUI landing panel · [Enter] launches the live watcher (big numbers + pillar bars + Υ trend, auto-refreshes 30s) | | Connect | 6 | Sign in / switch device — paste a connect code from signalaf.com → Settings. Then [S] submits. |

Sign in + submit

sigrank enroll          # sign in: paste a connect code (get one at signalaf.com → Settings)
sigrank submit          # publish your verified runs to the board (sign in first)
sigrank submit --dry-run  # inspect the exact signed payload without sending anything

Or do it inside the TUI on the Connect tab (6), then press [S] to submit.

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MCP Server mode

When stdout is not a TTY (i.e. piped to an AI client), sigrank starts an MCP stdio server automatically. AI clients (Claude Code, Cursor, Windsurf, etc.) use this path.

Add to .mcp.json or equivalent:

{
  "mcpServers": {
    "sigrank": {
      "command": "npx",
      "args": ["-y", "sigrank"]
    }
  }
}

Or if installed globally:

{
  "mcpServers": {
    "sigrank": {
      "command": "sigrank"
    }
  }
}

Tools

| Tool | Args | What | | ------------------------------------- | -------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | rank_paste(text) | {input, output, cacheCreate, cacheRead} JSON or 4 whitespace-delimited numbers | Scores token pillars → Υ Yield / SNR / Leverage / Velocity / 10xDEV / Class + prose narration card | | get_leaderboard() | {window?} | Live board from signalaf.com — sorted by Υ Yield | | get_operator(codename) | {codename} | One operator's live profile | | submit_paste(text, codename) | {text, codename?} | Rank locally then POST to board. Omit codename for preview-only | | tokenpull(platform?) | {platform?} | On-device local reader: scans local logs → 4-window cascade. Zero paste, token-only | | tokenpull_submit(codename, window?) | {codename?, window?} | tokenpull → publish to board. Omit codename for preview | | tokenpull_compare(platform?) | {platform?} | All four sources side-by-side: tokenpull + ccusage + token-dash + tokscale. Returns pillars, cascade metrics, and delta % vs tokenpull per window | | rank_windows | {platform?, window?} | Multi-window cascade from local logs | | watch_tokenpull | {platform?, interval_s?} | One cascade snapshot per call (interval_s advisory) | | submit_verified | {window?, platform?, dry_run?} | THE ranked path: builds + ed25519-signs Schema 1.0 snapshots and POSTs them. platform:'multi' sums all active platforms. dry_run:true returns the exact payload unsent | | enroll | {code, device_label?} | Bind this device with a connect code from signalaf.com → Settings | | diagnose_cascade | {text?} | Diagnoses where your token cascade is leaking efficiency — ranked findings with severity + estimated Υ impact | | simulate_change | {text?, changes} | Prescriptive "what if" — test proposed pillar changes and see the exact Υ delta + class change before committing | | suggest_improvements | {text?} | Generates ranked, simulated improvement suggestions — tests strategies and returns them sorted by Υ yield impact | | self_improve | {text?} | One-click optimize: diagnoses, suggests, and simulates the best change in a single call | | get_best_operator(n?) | {n?} | Top N operators with behavioral framing in power-user language. Intent: "who is the best AI user?" | | compare_self(codename? \| text?) | {codename?} or {text?} | Your metrics vs board averages + power-user assessment + percentile + suggestion. Intent: "how do I measure up?" | | compare_operators(a, b) | {codename_a, codename_b} | Side-by-side comparison with behavioral verdict. Intent: "compare operator X vs Y" | | describe_power_user() | {} | Static explanation of AI power user archetype + metrics explained. Intent: "what is an AI power user?" | | optimize_efficiency(codename? \| text?) | {codename?} or {text?} | Ranked efficiency suggestions tied to your cascade shape. Intent: "how can I use AI more efficiently?" | | tokscale_breakdown(threshold?) | {threshold?} | Per-model token breakdown across platforms (models under threshold → "other") | | tokscale_market_share() | {} | AI tool market share: each tool's % of tokens/cost/messages, ranked. From local tokscale data | | tokscale_developer_profile() | {} | Per-developer usage profile across all detected tools: model mix, pillars, sessions, workspaces. Paths redacted | | tokscale_model_trends() | {} | Model adoption over time: per-model first/last seen, active days, month-by-month adoption curve | | tokscale_cost_analysis() | {} | Cost per developer per model: cost_per_million_tokens, cost_per_message, share_cost, client rollup | | tokscale_device_profile() | {} | Device fingerprinting: installed tools, session counts, active days, day-of-week distribution, concurrency. Paths redacted | | tokscale_mcp_usage() | {} | MCP server usage: detected servers, detection window, active days | | tokscale_competitive_intel(target) | {target} | Competitive intelligence for any AI tool: rank, model mix, cost efficiency, share vs all competitors |

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Cascade math

Υ Yield    = (cache_read × output) / input²
SNR        = output / (input + output)
Leverage   = cache_read / input
Velocity   = output / input
10xDEV     = log₁₀(leverage)

Math is in cascade.mjs, dependency-free. Mirrors sigrank-app/lib/ingest/bridge.ts. Canon check: MO§ES (1251211, 11296121, 128196310, 2555179769) → Υ 18436.98.

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Token Pillars — sources

The dashboard pulls from multiple sources and shows them side-by-side for verification:

| Source | What | Platform | | ----------------- | ------------------------------------------------------------------------------ | --------------------- | | tokenpull | On-device JSONL scanner (canon source) | claude, codex, amp, … | | ccusage | ccusage <platform> daily --json CLI (bundled) | claude, codex | | token-dashboard | ~/.claude/token-dashboard.db SQLite (Nate's) | claude only | | tokscale | tokscale models --json CLI (bundled, falls back to ~/tokscale_report.json) | claude, codex |

Non-Claude input is estimated — most non-Claude systems (Codex, Devin, etc.) combine user input + cache write into a single input_tokens field, so true fresh input must be derived. The ruleset (applies to ALL non-Claude systems):

input       = output × ioRatio         (ioRatio derived from Claude ratio, else 2.0)
cacheCreate = uncached − input         (uncached = input_tokens − cached_input_tokens)
cacheRead   = exact (from logs)

Beta = operator's Claude input/output ratio (if Claude data available)
Alpha = 2.0 default (when no Claude data)
Owner-stated average: 7:1:2 (cache:input:output) → input/output ≈ 0.5

Verifier numbers (ccusage/tokscale for codex) show raw uncached input (input_tokens − cached) — a different field than the estimated input above. The discrepancy is expected and explained inline in the dashboard.

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Platform adapters

All adapters are token-only (no message content, no cost fields, no credentials). The table below is regenerated from the adapter file headers in adapters/index.mjs + adapters/tokenpull.mjs so the path, pillar shape, and notes match the actual code (a prior revision had drifted on Qwen/Codex/Copilot).

| Platform | Path | Pillar shape & notes | | ------------------ | ---------------------------------------------- | ----------------------------------------------------------------------------------------------------------------- | | Claude Code | ✅ ~/.claude/projects (recursive, incl. subagents/) | Native 4-pillar; dedup by (session_id, message_id) — final snapshot wins | | Codex | ✅ ~/.codex/sessions (+ archived_sessions) | input_tokens incl. cached → input + cacheCreate split window-level via io_ratio; cacheRead native (cached_input_tokens); reasoning_output→output; verified vs ccusage (~1%) | | Devin CLI | ✅ ~/.local/share/devin/cli/sessions.db | SQLite; same io_ratio split as Codex (Alpha 2.0 default); cacheRead native | | Amp | ✅ ~/.local/share/amp/threads | Native 4-pillar; per-message | | Kimi | ✅ ~/.kimi/sessions | Native 4-pillar; StatusUpdate lines only | | pi-agent | ✅ ~/.pi/agent/sessions | Native 4-pillar; per-message JSONL | | OpenClaw | ✅ ~/.openclaw | Native 4-pillar; per-message JSONL | | Droid | ✅ ~/.factory/sessions/*.settings.json | Native 4-pillar; thinking_tokens→output | | Codebuff | ✅ ~/.config/manicode | Native 4-pillar; chat-messages.json | | Hermes | ✅ ~/.hermes/state.db | Native 4-pillar; SQLite; reasoning_tokens→output | | Kilo | ✅ ~/.local/share/kilo/kilo.db | Native 4-pillar; SQLite | | Qwen | ✅ ~/.qwen/projects | Estimated (cacheCreate=0 — no field in logs); cacheRead from cachedContentTokenCount; thoughtsTokenCount→output | | Goose | ✅ ~/.local/share/goose/sessions/sessions.db (or $GOOSE_PATH_ROOT/data/sessions/sessions.db) | Estimated (cacheCreate=cacheRead=0 — no cache fields); reasoning = total−input−output→output; cumulative-column dedup by session id | | Gemini CLI | ✅ ~/.gemini/tmp | Estimated (cacheCreate=0); cacheRead from cached field; thought→output; input = input−cached (fresh) | | GitHub Copilot CLI | ✅ ~/.copilot/otel | Native 4-pillar (OTel spans: llm.token_count.{prompt,completion,cache_creation,cache_read}); requires COPILOT_OTEL_ENABLED=true + COPILOT_OTEL_EXPORTER_TYPE=file set before session start | | OpenCode | ⚠️ ~/.local/share/opencode | Data gap — logs store cost:0 and derive tokens via LiteLLM at runtime; raw token counts not persisted. No pillars readable with current format | | Other (user JSON) | ✅ $SIGRANK_OTHER_PATH | User-supplied JSON { "windows": { "all": {input,output,cacheCreate,cacheRead} } }; all-time only (no timestamps) | | Cursor | 🔜 | Chat log path TBD | | Windsurf | 🔜 | Session logs at ~/.codeium/windsurf/ |

estimated=true means one or more pillars are derived, not native. The server re-scores all submitted pillars authoritatively; local preview Υ is indicative only.

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Privacy

Token-only, always. No message content is ever read, logged, or transmitted — only token counts (input, output, cache_creation, cache_read), message IDs, and timestamps.
Local by default. tokenpull reads only ~/.claude/projects (Claude) or ~/.codex (Codex) on your device. Numbers stay on your machine unless you explicitly submit with a codename.
Background tooling excluded. Memory plugins, observers, summarizers (e.g. claude-mem, mem0, observer-sessions) are filtered from both Claude and Codex reads. subagents/ are kept — they represent real operator work.
Board reads are anonymous. No account needed to browse, compare, or watch.
Ranked submissions are signed, not trusted. sigrank submit requires a one-time enroll (device-bound ed25519 key — the private key never leaves your machine). Verify what's sent with sigrank submit --dry-run: the payload is four token counts, ratios, and a signature.

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Env vars

| Var | Default | Description | | ----------------------- | ---------------------- | ---------------------------- | | SIGRANK_API_BASE | https://signalaf.com | Override the board host | | SIGRANK_FETCH_TIMEOUT | 10000 | Board API fetch timeout (ms) |

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Dev / test

node test.mjs          # 13 test groups, 200 assertions (no network, no fs writes)
node sign.test.mjs     # ed25519 signing + canon parity
node index.mjs         # stdio MCP server directly (pipe to MCP client)

Tests verify (13 groups, 200 assertions):

rank_paste canon: MO§ES (1251211, 11296121, 128196310, 2555179769) → Υ 18436.98 · TRANSMITTER
submit_paste preview (no codename) + POST shape (injected fetch, no live writes)
tokenpull dedup, window slicing, 4-window pillars (mock adapter)
tokenpull_submit all 4 windows POST, sha256 hash, ddmmyy stamp
tokenpullCodex io_ratio conversion per-window
Adapter registry (15 platforms) + per-adapter shape contracts
rank_windows 4-window paste scoring, partial input, no-network
watch_tokenpull cascade snapshot, interval_s, submit path
enroll posts identity (public key only), maps 201 enrolled + 410 code_invalid
submit_verified signs Schema 1.0, server-verifiable
simulate_change relative + absolute deltas, quadratic penalty, JSON input
Hardening: div-by-zero guards, parsePillars warnings, fetch timeout, EXCLUDE_TOOLING regex, narrate safety
sign.test.mjs ed25519 round-trip + canonical 926-byte payload parity

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File map

| File | Responsibility | | --------------- | ----------------------------------------------------------------------- | | index.mjs | Entry point — TTY detection, routes to CLI or MCP server | | cli.mjs | CLI commands: board, compare, watch, enroll, submit, help | | tui.mjs | Full tabbed TUI: Dashboard / Trends / Compare / Board / Watch / Connect | | cascade.mjs | Pure cascade math (Υ, SNR, leverage, velocity, 10xDEV, class) | | tokenpull.mjs | On-device log scanner — Claude, Codex, multi-platform | | adapters.mjs | Platform adapter registry (15+ platforms) | | tools.mjs | MCP tool table + dispatcher | | connect.mjs | Connect-code enrollment + device identity | | keystore.mjs | Local key management (paste-keys, not API keys) | | submit.mjs | Verified submit flow (signs + POSTs to board) | | sign.mjs | Schema 1.0 signing (X-Agent-Signature) | | narrate.mjs | Deterministic prose narration card | | preflight.mjs | Plausibility checks (Benford, bounds, anomaly detection) | | test.mjs | Unit tests (no external deps) | | sign.test.mjs | ed25519 signing + canon parity test |

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Contributing

Contributions welcome. SigRank MCP is built in the open.

Contributing guide
Security policy
Report bugs via GitHub Issues
PRs: fork → branch → node test.mjs passes → open PR against main

License

MIT — see LICENSE.

SigRank MCP server