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PropLine — Sports Betting Odds & Prop Resolution

by io.github.proplineapi

Get event context

propline_get_event_context
Read-onlyIdempotent

Game context for an event — the conditions a prop settles under. MLB: probable starting pitchers and their throwing hand (L/R/S — platoon-split context for every batter prop), a confirmed-lineup flag, the home-plate umpire, and first-pitch weather (temperature, wind, precipitation) at outdoor / open-roof venues (indoor venues return weather=null). NFL & NCAAF: the venue and kickoff weather. The same block is embedded in get_event_results, so every graded prop carries its conditions — unique to PropLine. Free tier. 404 when no context is on file for the event yet.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
event_idYes
sport_keyYes

Schema Changelog

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

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false. The description adds valuable behavior: indoor venues return weather=null, the free tier, and a 404 when no context exists. These details go beyond what annotations provide, enriching transparency.

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

Conciseness4/5

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

The description is front-loaded with the core purpose, then organizes sport-specific details, and ends with free tier and error behavior. It is dense but not overly long; every sentence adds meaningful context, though it could be trimmed slightly.

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?

It covers the contents for MLB and NFL/NCAAF, the indoor-venue weather edge case, the relationship to get_event_results, and the 404 error. The lack of a response structure is a minor gap, but given the small parameter set and no output schema, it is largely complete.

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?

With schema_description_coverage at 0%, the description must compensate for parameter meaning. It never explains sport_key or event_id values or constraints, only implicitly referencing sports and 'event' in the 404 note. The schema provides only types and required flags, leaving the agent to infer usage.

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 clearly states the tool provides 'Game context for an event — the conditions a prop settles under' and details sport-specific content. It distinguishes from siblings like get_event_results by noting the same block is embedded there, establishing a unique standalone purpose.

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 clear context by outlining MLB, NFL & NCAAF specifics and mentions that the same block is embedded in get_event_results, implying when to use this standalone tool. However, it doesn't explicitly state exclusions or say 'use this instead of X,' so it stops short of fully explicit guidance.

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

All PropLine — Sports Betting Odds & Prop Resolution toolsInspect
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TDQS

A4.1/5.0
Disambiguation3/5

The tools are mostly distinct by purpose, but several overlap in areas like odds retrieval (get_odds vs get_best_line vs get_event_ev) and historical data (get_odds_history vs get_odds_closing vs export_odds_history). Descriptions are detailed and clarify distinctions, but the close functional relationships (e.g., get_event_movement vs get_odds_history) may cause selection ambiguity for an agent.

Naming Consistency4/5

The naming pattern is largely consistent: propline_<verb>_<noun> with verbs like get, list, export. Most tools follow this structure (e.g., get_event_results, list_events, list_sports). Deviations include 'propline_export_odds_history' (export instead of get) and a few longer names like 'propline_get_mlb_grand_salami' and 'propline_get_nhl_daily_goals_total' that break the simple verb_noun pattern but are still readable. Overall, the naming is predictable with minor exceptions.

Tool Count4/5

With 23 tools for a sports betting odds and prop resolution server, the count is on the higher side but still within a reasonable range given the domain's complexity (odds, EV, movement, results, player trends, webhooks, exports). Each tool serves a distinct function, though some could be consolidated (e.g., grand salami and NHL daily totals could be one). Slightly heavy but not excessive.

Completeness4/5

The tool set covers the core lifecycle: discover sports and events (list_sports, list_events), retrieve odds and markets (get_odds, list_event_markets), analyze EV and lines (get_event_ev, get_best_line, get_event_movement), track results and player stats (get_event_results, get_event_stats, get_player_history, get_player_trends), and backfill via exports. Missing features include webhook management (deliberately omitted) and possibly batch operations, but the surface is comprehensive for the stated purpose.

Resources