Skip to main content
Glama

Central Command

by co.supabase.rtcelwjnrbmfmrywacky

Multi-Asset Technical Scanner

cc.asset_scanner
Read-onlyIdempotent

Call cc.asset_scanner — Scans 36 major crypto assets across BTC, ETH, SOL, alts, and memes for multi-timeframe technical signals including RSI, MACD, Bollinger Bands, ATR, and composite scores. Purpose: Scans 36 major crypto assets across BTC, ETH, SOL, alts, and memes for multi-timeframe technical signals including RSI, MACD, Bollinger Bands, ATR, and composite scores. Behavior: READ-ONLY. Does not place orders, move funds, or mutate your exchange account. Responses may be cached (~1800s). Auth: X-Api-Key or x402 payment proof (X-PAYMENT / __x_payment). Anonymous unauthenticated calls receive HTTP 402 with payment accepts. Cost: $0.002 USDC per successful call (x402 Base USDC pay-per-use or prepaid X-Api-Key balance). Linked Connect keys are free. This is billing, not a side effect. Rate limit: 60/min (per API key). Tier: standard. Returns: Array of per-symbol objects with indicator values, directional scores, and signal strength ratings. Cached 30 minutes. Guidelines: Use for research / signal context. Pair with cc.agent_strategy (paper) before any live order. Do not invent fills from this data alone. Tags: crypto, technical-analysis, scanner, multi-asset, signals.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
__x_paymentNoOptional x402 payment proof (same value as X-PAYMENT header). Use when retrying after HTTP 402 if your MCP client cannot set custom headers. Not a business parameter. Optional.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYesTrue when the gateway HTTP status is 2xx.
dataNoParsed JSON body from the endpoint (shape varies by slug).
errorNoError message when ok is false.
statusYesUpstream HTTP status from x402-gateway.
billingNoOptional payment / cost metadata when present.
endpointYesCatalog slug that was invoked (e.g. funding-rates).

TDQS

A4.6/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description comprehensively discloses behavioral traits: read-only (consistent with annotations), caching (~1800s), authentication methods, cost ($0.002), rate limit (60/min), and return format. This adds significant context beyond the annotations, which already indicate read-only, idempotent, and non-destructive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with key sections (purpose, behavior, auth, cost, return, guidelines) but contains slight redundancy (e.g., the first sentence repeats the purpose). Each sentence adds value, and it is front-loaded with the core action.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the output schema exists, the description sufficiently explains the return format and key details (indicators, scores). It also covers caching, auth, cost, and rate limits. For a read-only, zero-required-parameter tool, the description is complete and leaves no critical gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There is only one optional parameter (__x_payment) with schema coverage of 100%. The description adds context explaining its purpose (payment proof for x402 retries) and when to use it, which goes beyond the schema description. Baseline 3, plus extra context, justifies a 4.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool scans 36 major crypto assets across multiple categories (BTC, ETH, SOL, alts, memes) for multi-timeframe technical signals including specific indicators (RSI, MACD, etc.). The verb 'scans' and resource 'crypto assets' are specific, and the scope is well-defined.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states 'Use for research / signal context' and advises pairing with cc.agent_strategy for paper trading before live orders, providing positive usage guidance and a related sibling tool. However, it does not explicitly state when not to use this tool versus other similar scanners like cc.central_signal or cc.coinglass_data.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Central Command toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.1/5.0
Disambiguation2/5

Many tools serve overlapping purposes, such as multiple Coinglass data tools (cc.coinglass_data, cc.funding_rates, cc.open_interest, etc.) and multiple AI chat assistants (cc.squirrel_chat, cc.squirrel_chat_v2, cc.openclaw_chat). The distinctions are subtle, likely causing agent misselection.

Naming Consistency5/5

All tool names follow a consistent `cc.<snake_case>` pattern, with verbs like `list_catalog`, `cc.ma_fetch`, and `cc.trade_builder`. No mixing of conventions.

Tool Count3/5

33 tools is on the high side but reasonable for a comprehensive crypto trading platform. However, significant redundancy (e.g., multiple data sources for similar indicators) suggests some could be consolidated, making the surface feel heavier than necessary.

Completeness4/5

The tool set covers most aspects of crypto trading: market data, technical indicators, signals, execution, backtesting, AI analysis, and blockchain RPC. Minor gaps exist (e.g., portfolio management), but the surface is largely complete for the intended domain.

Resources