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market

by xyz.sputnikx

mt_newswires_query

MT Newswires commodity headlines (read-only). Pulls the configured RSS or JSON feed (MT_NEWSWIRES_RSS_URL / MT_NEWSWIRES_API_URL), parses up to limit items, and returns {title, pubDate, link, summary, source}. Use as a low-latency news ticker for commodity-trader agents. Pass test_mode=true for deterministic mock fixtures; the tool auto-falls back to mocks if the feed is unreachable.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax headlines to return (default 10, max 50).
sinceNoOptional ISO 8601 cutoff (e.g. "2026-05-16T00:00:00Z"). Only items with pubDate >= since are returned.
topicNoOptional case-insensitive keyword filter applied to title+summary (e.g. "oil", "copper", "wheat"). Omit for unfiltered feed.
test_modeNoWhen true, return deterministic mock fixtures and skip the external feed entirely.

Schema Changelog

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

  1. Added

TDQS

A4.3/5.0
Behavior5/5

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

With no annotations, the description carries the full burden, and it delivers: it discloses read-only behavior, feed configuration, item limit handling, return fields, test_mode mocking, and automatic fallback to mocks when the feed is unreachable. This is strong behavioral coverage for a simple query tool.

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 compact and front-loaded: it states what the resource is, what the tool does, what it returns, and when to use it. No sentence is wasted.

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 description covers purpose, behavior, return shape, use case, and failure/mock behavior. With 100% schema description coverage for parameters, the absence of extra parameter detail is not a gap, and there is no output schema to compensate for, yet the return fields are explicitly listed.

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% and each parameter already has a useful description, so the baseline is 3. The tool description adds no meaningful extra semantics for since or topic, and only restates limit and test_mode behavior already present in 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?

The description clearly identifies the tool as an MT Newswires commodity headline reader, with a specific verb (pulls/parses/returns) and a concrete output shape. It does not explicitly contrast with sibling tools, but the resource and scope are unambiguous.

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 gives a clear usage context: 'Use as a low-latency news ticker for commodity-trader agents.' It does not mention exclusions or alternatives, so it falls just short of fully explicit routing guidance.

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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TDQS

B3.4/5.0
Disambiguation3/5

Multiple signal tools (front_run_watch, prediction_signals, wave_signal) serve similar purposes and could be confused, though each has a distinct data source. Similarly, soul_insights and soul_stack_feed both present agent-generated content, creating some ambiguity.

Naming Consistency3/5

All names use snake_case, but there's no consistent pattern: some are verb-first (get_prices, search_products), some are brand-prefixed nouns (soul_bounties, wave_portfolio), and mixed usage like daloopa_query and soul_verify. The inconsistency is readable but not predictable.

Tool Count4/5

16 tools for a multi-source market data server is reasonable; there are no outright redundant tools, though a few (think, fusion_capabilities) feel auxiliary. The count is slightly above ideal but well within acceptable bounds.

Completeness2/5

The server provides extensive read-only browsing (soul_bounties, soul_insights) but lacks corresponding action tools like claiming a bounty or purchasing insights, creating dead ends. For a 'market', there are no execute/trade/buy operations, leaving significant gaps for agent workflows.

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