Tanod MCP server

chainpeek: the Hyperliquid perp market list with mark, oracle, open interest, volume and max leverage

get_perp_markets

Read-onlyIdempotent

List Hyperliquid perpetual markets with mark, oracle, open interest, 24h volume, funding, and max leverage; filter by symbols, sort, and limit results.

Instructions

chainpeek: List Hyperliquid perpetual markets with mark, oracle, open interest and volume. For funding history use get_funding_rates. Returns the Hyperliquid perp market list: mark, oracle, premium, open interest, 24 h volume and change, max leverage, funding; filter by symbols, sort, limit. Hyperliquid perps only; cached up to 60 s; open interest USD = coins x mark. Data only, not trading advice. Bad input is a 422 (not charged). Typically 0.3-2 s. Price: USD 0.002. Free: 10 chain reads per IP per UTC day. Docs: https://tanod.dev/learn/ethereum-base-chain-data-mcp-server.html

Input Schema

TableJSON Schema

Name	Required	Description	Default
`sort`	No	volume (24 h, default), open_interest, funding, premium, leverage, change (24 h) or symbol.	volume
`limit`	No	Rows returned, 1-250 (default 50).
`order`	No	desc (default) or asc.	desc
`symbols`	No	Optional: only these perps (case-insensitive, at most 50). Unknown names are listed in symbols_not_found.

Output Schema

TableJSON Schema

Name	Required	Description
`note`	No
`cache`	No
`count`	No
`error`	No	Only on an error result: an object {code, message}, or the reason string of an x402 PaymentRequired object.
`source`	No
`markets`	No
`total_markets`	No
`symbols_not_found`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.3.0Oct 15, 2026

TDQS

A4.4/5.0

Behavior5/5

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

Annotations already cover the safety profile (readOnly/idempotent/non-destructive), yet the description still adds materially: 60 s cache staleness, open-interest unit formula (USD = coins x mark), 422 on bad input with no charge, 0.3-2 s latency, and pricing/free-tier limits. This is exactly the kind of operational context annotations cannot convey.

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?

Front-loaded with purpose and routing, then a dense block of operational facts that all earn their place (cache, units, error, latency, price). Slight redundancy: the field list is enumerated twice and overlaps with the title, which costs it a point.

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?

An output schema exists, so return values need no explanation, and the description fills every remaining gap an agent needs: scope limits, caching, unit conventions, error semantics, latency, and cost. Nothing required to invoke or interpret the call is missing.

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% and each parameter (sort, limit, order, symbols) is already documented in the schema, so the baseline is 3. The description only restates 'filter by `symbols`, sort, limit' and omits `order`, adding no syntax or semantics beyond the schema.

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 ('List Hyperliquid perpetual markets') plus the exact data scope (mark, oracle, open interest, volume, max leverage, funding). An agent can distinguish it from market-data siblings like get_funding_rates or get_dex_volume without opening a schema.

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?

Names an explicit alternative with its triggering condition: 'For funding history use get_funding_rates.' It also scopes the tool ('Hyperliquid perps only'), preventing accidental use for other venues. It doesn't address the other nearby funding siblings (compare_funding_rates, rank_funding_carry), so it stops short of exhaustive when/when-not routing.

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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