Skip to main content
Glama
DanielTomaro13

sportsdata-mcp

kalshi_markets

Fetch prediction-market quotes and filter by event, series, or status. Get bid/ask prices, volume, and liquidity for market analysis.

Instructions

Prediction-market catalogue with current quotes — filter by event/series ticker or status. Paginated by cursor.

Returns: {cursor, markets:[{ticker, event_ticker, market_type, title, status, yes_bid_dollars, yes_ask_dollars, no_bid_dollars, no_ask_dollars, last_price_dollars, volume_fp, volume_24h_fp, open_interest_fp, liquidity_dollars, open_time, close_time, expiration_time, rules_primary}]}

Example: First page of open markets

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
cursorNo
statusNo
tickersNo
event_tickerNo
series_tickerNo
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses pagination via cursor, returns structure with all fields, and the example hints at behavior (first page). It does not mention rate limits or authentication, but for a read-only catalogue that is acceptable. No contradictions.

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 concise and well-structured: first sentence states purpose and key filters, then a returns block with all fields, then an example. Every sentence adds value with no redundancy.

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 6 parameters, no output schema, and no annotations, the description covers core functionality (listing, filtering, pagination) but misses details on the tickers array parameter and default limit. The example helps but is minimal. Overall adequate but not thorough.

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 0%, so the description must compensate. It explains event_ticker, series_ticker, and status as filters, and the example implies status='open'. However, it omits explanation of limit, cursor, and the tickers array. This adds meaning for half the parameters but leaves gaps.

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 identifies it as a prediction-market catalogue with current quotes, and specifies filter options (event/series ticker, status) and pagination. This distinguishes it from siblings like kalshi_market (single market) and kalshi_trades. The example 'First page of open markets' reinforces the listing purpose.

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 through filters (by event/series ticker or status) but does not explicitly state when to use this tool versus alternatives (e.g., kalshi_market for details, kalshi_events for event data). It lacks when-not-to-use guidance.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/DanielTomaro13/sportsdata-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server