polymarket-mcp-server

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Get Polymarket price history

polymarket_get_price_history

Read-onlyIdempotent

Fetch historical prices and implied probabilities for a Polymarket market outcome to track movement and find entry or exit points, plus summary stats.

Instructions

Get the historical price (implied probability over time) for one market outcome, plus summary stats.

Use this to see how a market moved and where you might have entered or exited. Identify the outcome by token_id (preferred) OR slug + outcome.

Args:

token_id (string, optional): the ~77-digit CLOB token id.
slug (string, optional) + outcome (string, optional): e.g. slug + "Yes".
interval ('1h'|'6h'|'1d'|'1w'|'1m'|'max'): look-back window (default '1w').
fidelity (number, optional): minutes between points.
max_points (number): downsample to at most this many points (default 150).
response_format ('markdown' | 'json'): default 'markdown'.

Returns: { tokenId, outcome, interval, count, truncated, summary:{first,last,min,max,changeAbs,changePct,from,to}, points:[{t, iso, p}] }. Prices are 0-1 (probability). 'count' is the number of returned points; 'truncated' indicates downsampling.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`slug`	No	Market slug — alternative to token_id. Combine with 'outcome'.
`outcome`	No	Outcome name to select when using 'slug' (e.g. 'Yes' or 'No'). Defaults to the first outcome.
`fidelity`	No	Resolution in minutes between points (optional; the API picks a sensible default).
`interval`	No	Look-back window: 1h, 6h, 1d, 1w, 1m or max (default 1w).	1w
`token_id`	No	CLOB token id (the ~77-digit id for ONE outcome). Preferred when you already have it.
`max_points`	No	Downsample the series to at most this many points (default 150).
`response_format`	No	Output format: 'markdown' (concise, human-readable; default) or 'json' (full structured data).	markdown

Output Schema

TableJSON Schema

Name	Required	Description	Default
`count`	Yes
`points`	Yes
`outcome`	Yes
`summary`	Yes
`tokenId`	Yes
`interval`	Yes
`truncated`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Sep 28, 2026

TDQS

A4.4/5.0

Behavior4/5

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

With annotations already covering safety (readOnly, idempotent, destructive=false, openWorld), the description adds meaningful behavioral context: prices are 0-1 probabilities, 'count' is the number of returned points, and 'truncated' signals downsampling. This goes beyond the annotations, though it leans on the return section rather than describing operational traits like rate limits.

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 well front-loaded: purpose, then usage, then Args, then Returns. The Args block repeats most of the 100%-covered schema, which is somewhat wasteful, but the layout is scannable and each section stays compact.

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

Completeness5/5

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

For a 7-parameter read tool, the definition is complete: an output schema exists and the description still summarizes the return shape and downsampling semantics, annotations cover the safety profile, and all parameters (including defaults and the identification alternatives) are accounted for. Nothing needed to call it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3, but the description adds genuine meaning the schema lacks: it frames token_id vs slug+outcome as alternatives (the schema marks all params optional with no such relationship) and explicitly calls token_id 'preferred'. The remaining args largely restate schema text and defaults.

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 gives a specific verb ('Get'), a precise resource ('historical price ... for one market outcome') and an additional deliverable ('plus summary stats'), with the parenthetical 'implied probability over time' clarifying the domain. This is clearly distinguished from siblings like get_market or get_quote that deal with current state rather than a time series.

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?

It states a concrete use case ('see how a market moved and where you might have entered or exited'), which gives clear context for when to reach for it. However, it names no alternatives and offers no when-not guidance versus related tools such as get_market or get_quote.

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