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seungdori

tickscope-mcp

by seungdori

get_aggregated_price

Aggregate a symbol's current price across multiple exchanges, computing volume-weighted average, mean, best and worst venue, and cross-exchange spread to identify arbitrage opportunities.

Instructions

Aggregate a symbol's price across multiple exchanges (arbitrage view).

Fetches the ticker on each configured (or given) exchange concurrently and returns the 24h-volume-weighted average price, the simple mean, the cheapest/most-expensive venue, and the cross-exchange spread (arb_spread / arb_spread_pct) — the foundation for spotting arbitrage. Venues that fail or lack the symbol are skipped.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYes
exchangesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses concurrent fetching, the computed metrics (volume-weighted average, simple mean, best/worst venue, spread), and a key error-handling behavior: venues that fail or lack the symbol are skipped. It does not mention rate limits or caching, but for a read-only aggregation tool this is acceptable.

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

Conciseness5/5

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

Two short paragraphs: the first is a concise one-sentence summary, the second provides necessary detail on outputs and failure handling. Every sentence adds value with no redundancy.

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?

With only 2 parameters and no annotations, the description covers purpose, computation logic, and error behavior. It does not detail return structure, but an output schema exists, so that burden is already handled. It is sufficiently complete for an agent to select and call the tool.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It hints at the `exchanges` parameter with 'configured (or given) exchange', but does not explain symbol format, how to specify venues, or what happens when `exchanges` is null. The schema is minimal and the description adds only vague semantics, leaving significant gap.

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 uses a specific verb 'Aggregate' and identifies the exact resource ('a symbol's price across multiple exchanges'), explicitly framing it as an 'arbitrage view'. This clearly distinguishes it from siblings like get_ticker, which focuses on a single exchange.

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?

It states the use case as an 'arbitrage view' and 'the foundation for spotting arbitrage', making it clear when to use this tool over single-exchange alternatives. It does not explicitly name alternatives or exclusions, but the context is strong enough.

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

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