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jasonwu001t

marketlens-mcp

by jasonwu001t

Crypto trades

crypto_trades
Read-onlyIdempotent

Fetch historical crypto trades with taker side, windowed by start/end or lookback, and get a result_id to query large stored results via SQL.

Instructions

Historical crypto trades (size in base units) with the taker side (buy/sell). Window by start/end or lookback (default PT15M). Large results are stored, not shown: you get a result_id to query with results_query.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNoWindow end (same format). Default: now (Alpaca's latest available).
sortNoTime order of the rows: asc (oldest first, default) or desc (newest first).asc
startNoWindow start: ISO date (00:00 UTC) or datetime with a zone, e.g. 2026-01-02T14:30:00Z.
tickersYesCrypto pairs as BASE/QUOTE, e.g. ["BTC/USD"] (1-200).
lookbackNoWindow length back from end as an ISO-8601 duration (P5D, P1Y, PT20M); only when start is omitted. Default PT15M.
page_tokenNoContinue a truncated fetch: the page_token from the previous response's pagination.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

With annotations already declaring read-only/idempotent/open-world, the description adds genuinely useful behavior the annotations cannot convey: trades carry base-unit size and taker side, and large results are stored rather than returned inline, yielding a result_id for results_query. This offsets the missing return-shape detail.

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?

Three tight sentences, front-loaded with the resource and its key data semantics, then windowing, then the results-storage caveat. No filler.

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?

No output schema exists, so the description carries extra burden, and it covers the most important surprises: size units, taker side, and stored-result/result_id behavior. It could still say more about pagination and the truncation case, but the essentials are present.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents every parameter including the lookback default and formats; baseline 3 applies. The description restates the windowing and default PT15M without adding format or syntax detail beyond the schema.

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

Purpose4/5

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

States a specific verb+resource: 'Historical crypto trades' with the taker side, and the parenthetical clarifies size units. The word 'Historical' implicitly separates it from the sibling crypto_latest_trades, but the description never names that sibling, so an agent must infer the distinction.

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?

Explains how to scope the window (start/end or lookback, default PT15M) and routes the agent to results_query when results are large. It gives clear context for invocation but does not explicitly state when to prefer this over crypto_latest_trades or market_trades.

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