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Glama

MCPFax Macro & Market Intelligence

Polymarket market + order book

polymarket_market
Read-onlyIdempotent

One Polymarket market by Gamma id, slug or condition id, with its full outcome pricing and the LIVE CLOB order book for each outcome token: best bid, best ask, midpoint, spread and the top price levels with sizes. Use it before taking a position, to see real depth rather than only a last price. An outcome with no order book returns a null book rather than a fabricated price; an unknown identifier returns not_found and is not billed. Costs $0.008 USDC per call via x402 on Base; an unpaid call returns the payment challenge instead of data, and a call that returns no data is never settled so it costs nothing. Equivalent HTTP route: GET /polymarket/market.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoPolymarket Gamma market id Example: '908713'.
slugNoMarket slug, if you have no id Example: 'fed-rate-hike-in-2026'.
depthNoOrder-book levels per side, 1-20 (default 5) Example: '5'.
condition_idNoFull 0x-prefixed 32-byte condition id (66 chars), as returned by the markets/events/search tools Example: '0xf708d6652a477c59d7da116df8ff3d393b993e7037367b96cc33aa519cb48354'.

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the readOnly and idempotent hints, the description discloses specific behaviors: a null order book is returned if none exists (rather than fabricating a price), an unpaid call returns a payment challenge, and calls returning no data are never settled. This goes beyond the annotation hints and clarifies edge cases.

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 well-structured in a few sentences, each adding essential information about the return, usage context, and error handling. It is concise yet thorough, with no redundant or filler content.

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?

Given the absence of an output schema, the description thoroughly explains what the output contains (outcome pricing and order book details) and how edge cases are handled (null book, unpaid call, no data). It also covers the cost and settlement behavior, making it complete for an agent to decide when and how to invoke the tool.

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?

The schema already provides detailed descriptions for each of the four optional parameters, with examples. The tool description reinforces that these are alternative identifiers (gamma id, slug, condition id) and clarifies the depth parameter usages, adding slight context beyond the schema descriptions.

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 states the tool fetches a single Polymarket market by Gamma id, slug, or condition id, and returns outcome pricing and a live CLOB order book. It is specific and distinguishes from related tools by focusing on real order book depth rather than just last price.

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

Usage Guidelines5/5

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

The description gives explicit guidance to use this tool before taking a position to see real market depth, contrasting with only a last price. It also explains the cost (0.008 USDC via x402 on Base), potential payment challenge, and settlement behavior when no data is returned, covering practical usage considerations.

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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TDQS

A4.3/5.0
Disambiguation4/5

Most tools target distinct resources: defi_protocol vs defi_protocols are clearly list-vs-detail, and crypto_spot_prices vs defi_token_prices are explicitly differentiated. The main overlap is prediction_market_search vs polymarket_markets/manifold_markets, but the cross-venue purpose is clearly stated.

Naming Consistency5/5

All tool names use snake_case with a consistent resource-noun pattern (defi_, polymarket_, us_, etc.). Plural/singular variants are logical (defi_protocol vs defi_protocols, polymarket_market vs polymarket_markets), and no unconventional casing or verb-style mixing appears.

Tool Count4/5

18 tools is slightly above the ideal 3-15 range, but the server covers a broad domain (crypto, DeFi, prediction markets, macro, FX, rates), so each tool serves a distinct data type. The count feels justified by the breadth rather than redundant.

Completeness4/5

The surface covers major market intelligence categories well: prices, yields, TVL, prediction markets, macro indicators, and FX. Minor gaps exist (e.g., no equities/commodities, limited macro series, no historical crypto data), but the core workflows for macro and market overview are supported without dead ends.

Resources