webdata-tools-mcp

Get prediction market odds (Kalshi, Polymarket, Manifold, PredictIt)

get_prediction_markets

Read-onlyIdempotent

Search Kalshi, Polymarket, Manifold and PredictIt markets to compare implied probabilities, prices, volume and liquidity for event forecasting and news research.

Instructions

Prediction markets from Kalshi, Polymarket, Manifold and PredictIt in one table: the market-implied probability, every outcome price, bid and ask, 24-hour and 7-day change, volume, liquidity, open interest, close date, status and, once settled, the result. Search by keyword or category, or pass market links or tickers; optional daily price history. Use for event forecasting, news context and research. Runs the Apify Actor tacps126/prediction-markets on your Apify account (about $0.003 per market; spend per call is capped at $0.5).

Input Schema

Name	Required	Description	Default
`search`	No	Keywords, e.g. "fed rate", "bitcoin", "election". Empty = the busiest markets.
`status`	No	open, closed (settled, with result) or all.	open
`markets`	No	Market or event links, Kalshi tickers or Polymarket slugs.
`sort_by`	No	Order of results.	volume24h
`max_items`	No	Maximum results to return (default 30, max 1000). Cost scales with this.
`platforms`	No	Which platforms (default kalshi and polymarket).
`categories`	No	Only markets in these categories.
`extra_input`	No	Advanced: extra Actor input fields, merged over the defaults.
`history_days`	No	Add a daily price history of this many days (Kalshi and Polymarket). 0 = none.
`min_volume_24h`	No	Minimum 24-hour volume (dollars on Polymarket, contracts on Kalshi).
`closes_within_days`	No	Only markets that close within this many days.

Output Schema

Name	Required	Description
`tool`	Yes	Name of the tool that produced the result.
`count`	Yes	Number of records the Actor returned.
`items`	Yes	The records. Long text fields are shortened to 600 characters.
`shown`	Yes	Number of records included in `items` (can be lower than count when the result is long).
`truncated`	Yes	True when records were left out to keep the result short; ask for fewer items.

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.14.0Nov 2, 2026

TDQS

A4/5.0

Behavior4/5

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

Annotations already declare readOnly/openWorld/idempotent/non-destructive, so the description isn't carrying the safety burden. It adds genuinely new operational facts the annotations don't: the tool proxies the Apify Actor tacps126/prediction-markets on the user's own Apify account, costs about $0.003 per market, and hard-caps spend at $0.5 per call. It does not discuss run latency or failure modes for unsupported tickers.

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

Conciseness3/5

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

Lead sentence is a very long stacked list of every returned field, which is redundant given the tool has an output schema. The cost/execution note is valuable and belongs early, but the enumeration of return columns should have been trimmed in favor of the schema.

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?

For an 11-parameter, open-world scraping tool with no required params, the description covers cost model, spend cap, platform defaults and history option — enough to call it correctly. Return-value explanation is unnecessary since an output schema exists, so that omission costs nothing.

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%, so every parameter is already documented with enums, defaults and units. The description restates the search-modes and the optional daily price history without adding format or edge-case detail (e.g. what happens when both `search` and `markets` are supplied, or how `markets` interacts with `platforms`). Baseline 3 applies.

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?

States a specific verb and resource ('Get prediction markets') plus the four source platforms and the exact fields returned (implied probability, bid/ask, volume, liquidity, close date, settlement result). No sibling tool covers prediction markets, so the domain is unambiguous.

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?

Explicitly names the retrieval modes ('search by keyword or category, or pass market links or tickers') and the intended use cases ('event forecasting, news context and research'). It lacks any when-not guidance or comparison to an alternative tool, which keeps it below a 5, but the context is clear.

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