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Glama

Odds Api

by io.github.pipeworx-io

Odds Api Quota

odds_api_quota
Read-onlyIdempotent

Monthly request credits left and used on the key serving this call, read from The Odds API usage headers. Says whether the odds and scores tools can return data right now and how large the plan is.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
hintNoPresent when found is false: what to call instead to tell a spent quota from a bad key.
noteNoHow the monthly reset behaves.
usedNoRequest credits already spent this billing month.
errorNoPresent only when the balance is spent: always "account_limited". The read succeeded; the allowance behind the key did not survive it.
foundYesFalse when The Odds API did not return usage headers on this response.
reasonNoPresent when found is false: why the balance could not be read.
messageNoPresent only when the balance is spent: names the monthly exhaustion, the anniversary reset, and the tools that still answer for free.
exhaustedNoTrue when no credits remain, so the metered odds and scores tools cannot return data.
remainingNoRequest credits left on the key for the current billing month.
checked_atNoWhen the balance was read, ISO 8601.
plan_requestsNoPlan size for the month (remaining + used).
last_call_costNoCredits the caller's previous request consumed.

Schema Changelog

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

  1. Changed2 schema fields changed
    • addedOutput schema / properties / error
      Added value: +{
+  "description": "Present only when the balance is spent: always \"account_limited\". The read succeeded; the allowance behind the key did not survive it.",
+  "type": "string"
+}
    • addedOutput schema / properties / message
      Added value: +{
+  "description": "Present only when the balance is spent: names the monthly exhaustion, the anniversary reset, and the tools that still answer for free.",
+  "type": "string"
+}
  2. Added

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already convey read-only and non-destructive behavior. The description adds useful behavioral detail beyond annotations: it reads from The Odds API usage headers, reflects the key serving the call, and indicates real-time availability of related tools. No contradiction 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?

Two sentences, concise and front-loaded with the most important information: what is measured and where it is read from. Every clause adds value and there is no redundancy or filler.

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?

For a zero-parameter, read-only quota tool with an output schema and comprehensive annotations, the description covers what it returns (credits left/used, availability, plan size) and why it is useful. Nothing essential is missing.

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?

The tool has zero parameters, so the schema fully covers parameter information. The description adds relevant context about the implicit 'key serving this call' and the data source, which is appropriate even though no explicit parameters exist.

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 names a specific resource (monthly request credits) and a clear action (reading usage headers), and it explains what the tool reports: credits left/used, current availability of odds/scores tools, and plan size. This clearly differentiates it from data-returning siblings like get_odds and get_scores.

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 makes the usage context clear: use it to check quota state and whether odds/scores tools can return data right now. It does not explicitly name alternatives or state when not to use it, but for a quota-checking helper the context is understandable without exclusions.

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

A3.5/5.0
Disambiguation2/5

Several tool clusters have unclear boundaries: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route to the same 5,724 tools with only subtle behavioral differences, and bet_research, polymarket_edges, polymarket_arbitrage, and polymarket_kalshi_spread heavily overlap around prediction-market opportunity discovery. entity_profile, compare_entities, and recent_changes also fan out across the same SEC/news/patent sources, making selection ambiguous for agents.

Naming Consistency2/5

Naming mixes multiple conventions: snake_case verb_noun for odds tools (get_events, list_sports), vendor-prefixed clusters (ask_pipeworx_*, pipeworx_*, polymarket_*), and a few reversed noun-verb names like bet_research. CamelCase is used in ai_visibility_check and generate_llms_txt adds another style. Only the polymarket_* and pipeworx_* families are internally consistent, but the overall pattern is chaotic.

Tool Count2/5

37 tools is well beyond the typical well-scoped server, and the count feels inflated by unrelated meta-tools (suggest_questions, discover_tools, pipeworx_feedback, pipeworx_trending, generate_llms_txt, scan_dependency, remember/recall/forget) that have nothing to do with the server's stated 'Odds Api' purpose. The actual odds surface is only ~5 tools, so the vast majority of the catalog is off-scope padding.

Completeness3/5

The core odds domain is well covered: list_sports, get_events, get_odds, get_event_odds, and get_scores form a coherent lifecycle, plus quota introspection. However, for the server's actual broad-research scope there are noticeable gaps (e.g., no direct single-filing fetch tool despite heavy SEC coverage, a lone npm-dependency tool with no surrounding ecosystem, and no historical/past-odds endpoint), and the heterogeneous domains make completeness uneven.

Resources