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mcp-server-polymarket

mcp-server-polymarket

by tukorama
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Get order books

get_order_books
Read-onlyIdempotent

Retrieve order books for Polymarket outcome tokens, showing best prices and sizes per side with tick size and minimum order size for market analysis.

Instructions

Order books for outcome tokens, best prices first on each side, with tick size and minimum order size. Prices are probabilities (0-1) in pUSD; sizes are shares.

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": {
      "token_ids": "<token_ids>"
    },
    "name": "get_order_books"
  }
}

Input Schema

NameRequiredDescriptionDefault
depthNoLevels per side.
token_idsYesToken ids.

Output Schema

NameRequiredDescriptionDefault
booksYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so safety is covered; the description adds genuinely new behavioral context by specifying price units and semantics (probabilities 0-1 in pUSD), size units (shares), per-side ordering, and that tick size and minimum order size are returned. It does not address empty/illiquid books, invalid token ids, or the 50-token cap.

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?

Two short sentences, front-loaded with the resource and ordering, then unit semantics. Every clause carries information an agent would otherwise have to guess.

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?

An output schema exists, so return values need not be spelled out, and the description covers the essentials an agent needs to interpret the payload (ordering, price scale, size units). Only minor gaps remain: nothing about behavior for unknown or inactive token ids and no pointer to how to obtain token ids.

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 both parameters are already documented in the schema (depth as levels per side, token_ids as token ids). The description adds only indirect meaning for token_ids by calling them 'outcome tokens', and says nothing about how depth interacts with the ordering it describes. Baseline 3 is appropriate.

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?

States the specific resource (order books for outcome tokens) and adds what each side is ordered by ('best prices first on each side'), which lets an agent tell it apart from the market-listing sibling without opening the schema. It stops short of naming the sibling that would be used to discover token ids, so differentiation is implied rather than explicit.

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?

There is no when-to-use or when-not-to-use guidance, no mention of prerequisites (you need token ids, presumably from list_order_book_markets or get_market), and no exclusions. Usage is only inferable from the resource name.

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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