Odds De-vig MCP Server

get_event_consensus

Retrieve a consensus line for a specific event by removing bookmaker vig from The Odds API odds. Choose a de-vig method, set minimum bookmakers, and optionally remove outliers to compute fair probabilities.

Instructions

Get consensus line for a specific event

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "eventId": "<eventId>"
    },
    "name": "get_event_consensus"
  }
}

Input Schema

Name	Required	Description	Default
`eventId`	Yes	Event ID from The Odds API
`deVigMethod`	No	Method for removing vig (default: proportional)	proportional
`minBookmakers`	No	Minimum number of bookmakers for consensus (default: 3)
`removeOutliers`	No	Remove worst outlier bookmakers (default: false)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Aug 22, 2026

TDQS

A3.5/5.0

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 describes the tool's output (consensus line) but does not disclose specific behavioral traits such as whether it performs computations like de-vigging, how it handles missing data, or if it is read-only. It only hints at calculation through parameters like deVigMethod and removeOutliers.

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 a single, concise sentence that clearly states the tool's purpose without unnecessary words. It is front-loaded and efficient.

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

Completeness3/5

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

Given the tool has 4 parameters, no output schema, and no annotations, the description provides minimal context. It does not explain return value structure, error handling, or prerequisites like what constitutes a valid eventId. However, the parameter schema is well-documented, which compensates somewhat.

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 the schema already documents all four parameters with descriptions. The tool description adds no extra meaning beyond what the schema provides. Baseline 3 is appropriate as the description does not compensate with additional insights.

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 'Get consensus line for a specific event' clearly indicates the tool retrieves consensus odds for a given event, with 'event' being the resource. It differentiates from siblings like 'get_today_mlb' and 'get_upcoming_odds' by focusing on consensus for a specific event rather than listings or raw odds, though it doesn't explicitly name alternatives.

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

Usage Guidelines3/5

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

The description implies usage when an event ID is known and consensus data is needed, but does not explicitly state when to use it over siblings or when not to use it. Siblings like 'get_upcoming_odds' suggest alternatives for odds data, but no direct comparison is made.

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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