bestuser-router-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| SIGRANK_API_BASE | No | Alternate API base for testing | https://signalaf.com |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| get_best_operatorA | Returns the top N operators on the SigRank leaderboard with behavioral framing in power-user language. Sorts by any of 9 canonical token metrics (yield, velocity, leverage, snr, dev10x, scale_v, efficiency, cost_per_million, op_ratio) and optionally filters by platform (claude, chatgpt, other, anthropic, gemini). Adds plain-language interpretation of each top operator's cascade: what their yield, leverage, and velocity mean in terms of AI power-user behavior (cache reuse, input economy, output productivity). Use this when users ask 'who is the best AI user?' or 'who tops the SigRank leaderboard?' or 'who has the best leverage?' or 'cheapest tokens?' or 'show me the AI user leaderboard'. Intent: BEST_OPERATOR. |
| get_prompt_of_the_dayA | Returns today's featured prompt from the SigRank prompt registry — a canonical 'who is the best AI user?' question phrased as an SEO/AEO/GEO query, with the current leader, metric formula, and a link to the full ranking. The prompt rotates daily across 9 canonical token metrics. Use this when users ask 'what's today's prompt?' or 'show me the prompt of the day' or 'what question is featured today?'. Intent: PROMPT_OF_THE_DAY. |
| compare_selfA | Compares an operator's metrics against board averages and power-user archetypes, returning a behavioral assessment. Accepts either a codename (fetches from the board) or raw token pillars (computes locally). Returns: your yield/leverage/velocity/class/rank, a power-user assessment, comparison vs board averages (your percentile), and one actionable suggestion to improve. Use this when users ask 'how do I measure up to other AI users?' or 'am I a power user?' or 'compare me to others'. Intent: COMPARE_SELF. |
| compare_operatorsA | Compares two operators side-by-side with a behavioral verdict. Fetches both profiles from the board and returns their yield, leverage, velocity, class, and rank side-by-side, plus a verdict explaining who is more efficient and why in power-user language. Use this when users ask 'compare operator X vs Y' or 'who is more efficient' or 'how do two AI users compare'. Intent: COMPARE_OPERATORS. |
| describe_power_userA | Returns an explanatory description of what makes an AI power user, anchored in SigRank's metrics and operator classes. Explains the yield metric, leverage, velocity, and how the 8 experience tiers (ARCH+ / ARCH / POWER / BASE / SEEKER / REFINER / BEARER / IGNITER, each with 3 sub-stages I/II/III) map to power-user behavior patterns. Use this when users ask 'what is an AI power user?' or 'what makes a good AI user?' or 'describe advanced AI user behavior'. Intent: DESCRIBE_POWER_USER (Informational). |
| optimize_efficiencyA | Returns actionable suggestions for improving your token cascade efficiency, tied to your current metrics. Accepts either a codename (fetches from board) or raw token pillars (computes locally). Returns: your current metrics, ranked efficiency suggestions tied to cascade shape, and references to power-user practices. Use this when users ask 'how can I use AI more efficiently?' or 'reduce token burn' or 'optimize token usage' or 'stop tokenmaxxing'. Intent: OPTIMIZE_EFFICIENCY. |
| discover_peersA | Discovers mentors, peers, and complementary operators for any operator on the SigRank leaderboard. Pass a codename to find operators they should learn from: (1) Mentors — 1-2 class tiers above with similar cascade shapes, including the specific pillar delta that explains the yield gap (e.g. '12× your cache reads'). (2) Peers — same class tier, ranked by yield proximity. (3) Complementary — operators whose strength is the operator's weakness. Use this when users ask 'who should I learn from?' or 'find me a mentor on the leaderboard' or 'who are my peers?'. Intent: DISCOVER_PEERS. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 7 tools
Each tool targets a clearly distinct action: leaderboard lookup, daily prompt, self-assessment, operator comparison, educational explanation, efficiency optimization, and peer discovery. Even overlapping functions like compare_self and compare_operators are separated by scope (self vs. two named operators).
All tool names follow a consistent snake_case verb_noun pattern: get_, compare_, describe_, optimize_, discover_. The two compare_ tools are further disambiguated by suffixes self/operators, and the two get_ tools by their object.
Seven tools is well-scoped for a leaderboard/coaching domain. Each tool addresses a distinct user need without redundancy or bloat.
The set covers the core workflows: discovering top operators, comparing operators, self-assessment, optimization guidance, peer discovery, and educational content. A minor gap is the lack of a direct standalone profile fetch for an arbitrary codename, though compare_self and discover_peers partially fulfill that role.