Skip to main content
Glama

Backtesting Arena

by io.github.Schoasch

Get Indicator Snapshot with Historical Percentile Ranks

arena_get_indicator_snapshot

What do the classic indicators read right now? Current RSI(14), MACD(12/26/9), Bollinger(20,2), ATR(14) and OBV for a pair — each with a PERCENTILE RANK against that indicator's own history on that pair, plus the observation count — the rank turns a raw reading into a placement. ATR comes as a percentage of price so it is comparable across time, and OBV as a 30-bar slope normalised by that window's volume (raw cumulative OBV would mostly rank how long the series has existed). Where the reading sits in an extreme AND a study on this platform has tested that exact state, the payload carries the study verdict — including a null result: a Bollinger squeeze returns the quiet_volatility finding that tight bands did NOT carry an edge. Below 500 bars (1d) / 150 (1w) the raw values still come but percentile is null with a reason, rather than a rounded number from too small a sample. Set interval to '1w' for the weekly view. On the 1d view the payload also carries rsi_14_weekly (weekly RSI with its own rank) — for BTCUSDT this is the SAME series as arena_get_cycle rsi_weekly, measured character-identical (its source_note carries the measurement). state (oversold/neutral/overbought) names where a reading sits on its own scale. Related: arena_get_trend_channels (structure), arena_get_historical_analog (did a condition like this one ever pay?), arena_get_volatility_history (the volatility series behind ATR). [Free tier]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pairNoPair, e.g. "BTCUSDT" (default), "ETHUSDT", "PAXGUSDT".
intervalNoDefault '1d'. '1w' computes every indicator on weekly bars.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed3 schema fields changed
    • addedInput schema / additionalProperties
      Added value: +false
    • removedInput schema / properties / context
      Removed value: -{
-  "description": "Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): \"Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization.\"",
-  "type": "string"
-}
    • removedInput schema / required
      Removed value: -[
-  "context"
-]
  2. Added

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries full burden, and it does so thoroughly. It discloses normalization choices (ATR as % of price, OBV as 30-bar slope), behavior on small samples (percentile null with reason), study verdict inclusion conditions, and even a data provenance note (rsi_14_weekly identical to arena_get_cycle for BTCUSDT). It does not cover rate limits or explicit read-only status, but the behavioral details are extensive for a snapshot tool.

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

Conciseness3/5

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

The description is a single, lengthy paragraph with several complex clauses (e.g., the Bollinger squeeze explanation). While information-dense, it is not tightly structured; it could be split into shorter sentences or bullets for better readability. It front-loads the core purpose well, but the verbosity around edge cases and related tools makes it less concise than ideal.

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

Completeness4/5

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

Given only 2 optional parameters and no output schema, the description covers the essential call context thoroughly: indicator set, percentile rank approach, edge-case handling, extra field on 1d, state field, and related tools. It does not describe the exact response structure, but that is not required without an output schema. It is sufficiently complete for an agent to call it correctly and interpret results.

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?

Schema coverage is 100%, so parameters are documented, but the description adds meaningful nuance beyond the schema. For 'interval', it explains the effect on output (e.g., weekly RSI extra field only on 1d) and clarifies the choice. For 'pair', it provides examples and context but no additional semantics. The description adds interpretive value for the interval parameter, earning a 4 rather than a baseline 3.

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 opens with a clear, specific question: 'What do the classic indicators read right now?' and enumerates exact indicators (RSI(14), MACD(12/26/9), Bollinger(20,2), ATR(14), OBV) with percentile ranks. It explicitly distinguishes itself from siblings by naming related tools and their purposes (trend channels, historical analog, volatility history), making it unambiguous what this tool does and how it differs.

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 provides clear context for when to use the tool and explicitly lists alternative tools with their purposes in the 'Related:' clause. It gives direct usage instructions like 'Set interval to '1w' for the weekly view' and explains when percentile is null due to insufficient data. It does not explicitly state when not to use it, but the related tool explanations largely cover that.

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

All Backtesting Arena 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

A3.6/5.0
Disambiguation2/5

Many tools cover overlapping market indicators (e.g., cycle state, pulse, bullmarket ampel, volatility phases) and several share similar get_*_history patterns, which could cause an agent to select the wrong one. However, each tool has detailed descriptions with explicit references to related tools to reduce ambiguity.

Naming Consistency3/5

Tool names generally follow a verb_noun pattern (arena_get_*, arena_list_*, arena_run_*, arena_subscribe_*), but there are inconsistencies such as 'validate_strategy' (no arena_ prefix), 'arena_status' (not a clear verb_noun), and variations like 'arena_run_grid_backtest' vs 'arena_run_backtest'.

Tool Count2/5

With 84 tools, the server is heavily over-scoped for a typical MCP server, likely causing navigation and selection overhead. While the domain (crypto backtesting and analytics) is broad, 84 tools exceed reasonable coherence and impose a high cognitive load.

Completeness4/5

The tool surface covers a wide range of analytics (market indicators, backtesting, validation, alerts, subscriptions, reports) with few obvious dead ends. Minor gaps exist like lack of direct portfolio management or strategy editing, but core workflows are well covered.

Resources