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Odds De-vig MCP Server

Odds De-vig MCP Server

by Mavline
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

get_processed_odds

Retrieve sports odds with bookmaker vig removed to calculate fair probabilities, using configurable methods, markets, and consensus settings for accurate betting analysis.

Instructions

Get odds with vig removed and fair probabilities calculated

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_processed_odds"
  }
}

Input Schema

NameRequiredDescriptionDefault
sportNoSport key (default: baseball_mlb)baseball_mlb
marketsNoMarkets to get odds for (default: h2h)h2h
regionsNoRegions to get odds for (default: us)us
deVigMethodNoMethod for removing vig (default: proportional)proportional
minBookmakersNoMinimum number of bookmakers for consensus (default: 3)
commenceTimeToNoISO datetime for latest commence time (default: tomorrow)
removeOutliersNoRemove worst outlier bookmakers (default: false)
commenceTimeFromNoISO datetime for earliest commence time (default: today)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.1/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the key behavioral aspect (vig removal and probability calculation) which goes beyond a simple fetch. However, it does not mention rate limits, authentication, or output shape, and for an 8-param tool with no output schema, this is a moderate gap but not contradicting.

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?

A single, information-dense sentence that front-loads the core value proposition. Could arguably be more expensive with the parameter list, but it wastes no words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 8 parameters, no annotations, and no output schema, the description falls short. Key contextual gaps include: what does the return object look like, how does `removeOutliers` interact with `minBookmakers`, and what are the unit/semantics of odds returned. A tool of this complexity needs more than one sentence to be self-sufficient.

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%—every parameter has a description plus defaults. Per the rubric, high coverage sets baseline at 3. The description itself adds no extra parameter context beyond what the schema already provides, so it cannot score above baseline.

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?

Clear verb-resource pairing with a specific qualifier: 'Get odds with vig removed and fair probabilities calculated.' This distinguishes it from the raw odds tool `get_upcoming_odds` by emphasizing the processing transformation. However, it doesn't name sibling alternatives explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool vs. alternatives like `get_upcoming_odds` or `get_event_consensus`. The description implies a use case for fair/probability-adjusted odds but lacks any explicit when/when-not framing or reference to sibling tools.

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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