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Glama

Metals Api

by io.github.pipeworx-io

Get Historical

get_historical
Read-onlyIdempotent

Get metal prices for a specific historical date. Returns spot prices per troy ounce for that day. Useful for tracking price changes or computing returns.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
baseNoBase currency (default "USD")
dateYesDate in YYYY-MM-DD format (e.g., "2024-01-15")
_apiKeyYesMetals-API key
symbolsNoComma-separated metal symbols (e.g., "XAU,XAG")

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
baseYesBase currency code (e.g., USD, EUR)
dateYesHistorical date in YYYY-MM-DD format
ratesYesMetal spot prices per troy ounce, keyed by symbol (e.g., XAU, XAG)
timestampYesUnix timestamp of when prices were captured

Schema Changelog

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

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, and openWorld hints. The description adds value by specifying the return format ('spot prices per troy ounce for that day'), which is not in the annotations or schema. No contradictions with annotations.

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?

The description is two sentences, front-loaded with the primary purpose, and every sentence adds information. There is no redundant or filler text.

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?

The tool is simple, has a rich output schema, and clear annotations. The description sufficiently covers what the tool does, what it returns, and why it might be used. Nothing critical is missing for an agent to select and invoke it correctly.

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 coverage is 100%, so all parameters are already documented with types and descriptions. The tool description adds no additional parameter-level meaning beyond the schema, making the baseline score of 3 appropriate.

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 states a specific verb and resource: 'Get metal prices for a specific historical date.' It distinguishes from siblings like get_latest by emphasizing the historical date scope. The output is clearly defined as spot prices per troy ounce.

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 usage context: 'Useful for tracking price changes or computing returns.' It implies when to use historical data vs. other tools, but does not explicitly name alternatives or exclusions. Still clear enough for an agent to decide when this tool fits.

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

All Metals Api toolsInspect
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TDQS

A3.8/5.0
Disambiguation2/5

Multiple tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are variants of the same router, and the six polymarket_* tools cover overlapping arbitrage/edge analysis territory. ai_visibility_check vs scan_competitor_ai_presence and discover_tools vs suggest_questions add further boundary ambiguity. While descriptions try to differentiate, an agent could easily misselect among these clusters.

Naming Consistency3/5

Most names are readable snake_case, but there is no consistent verb_noun pattern: verbs vary (ask, get, list, scan, search, suggest, validate, generate, compare) and several tools are named by product prefix (pipeworx_*, polymarket_*) rather than by action. The pattern is predictable within clusters but inconsistent across the set.

Tool Count2/5

33 tools is heavy for the server's stated name, 'Metals Api', which only has two metals-related tools (get_historical, get_latest). Even as a general data-research server, the surface is bloated with memory utilities, subscription management, feedback, trending, and unrelated AI-visibility scanning. The scope mismatch makes the count feel unjustified.

Completeness3/5

The core metals domain is thin: latest and single-date historical prices exist, but there is no time-series range query, no list of supported metals, and no explicit currency conversion endpoint. The broader data-research/subscription/memory surface is relatively complete, but it is disconnected from the server's apparent purpose, leaving notable gaps for a metals-focused agent.

Resources