Skip to main content
Glama
Sign In

Realtap

by io.github.CSteenkamp
OverviewDiscussionsAdmin

Token liquidity: depth and liquidity flow

get_token_liquidity
Read-onlyIdempotent

Liquidity of one token. Depth: for each constant-product pool paired with ADA, the ADA that moves the pool's price 2 % up (buying) and the ADA received when selling moves it 2 % down, by the pool's own curve and fee (pools of other kinds, other pairings or without a fee are listed with the reason and left out of the sums). Flow: liquidity added and removed over the window (value of both sides in ADA at the pool price before each order settled; withdrawals are estimates from their LP share), net flow per wallet and the latest orders. Every figure carries what it covers: coverage names the window, the pools measured and the DEXes with no liquidity orders recorded.

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": {
      "unit": "<unit>"
    },
    "name": "get_token_liquidity"
  }
}

Input Schema

NameRequiredDescriptionDefault
unitYesToken unit: 56-hex policy id followed by the asset name in hex (no separator). Get it from `search` or `list_tokens`.
limitNoHow many wallets and orders to return (1-25, default 10).
windowNoHow far back the flow figures look.7d

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior5/5

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

Annotations already declare a safe read-only, idempotent, open-world query, and the description goes well beyond them: it discloses that non-qualifying pools are listed with a reason and excluded from sums, that withdrawals are estimates derived from LP share, and that every figure carries a `coverage` note naming the window, measured pools and DEXes with no orders. These are meaningful accuracy caveats an agent would otherwise have to discover empirically.

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 the one-line purpose, then split into clearly labeled Depth and Flow sections, so structure is strong. The sentences are long and heavily parenthetical, which makes them dense to parse, but each clause conveys substantive measurement detail rather than filler.

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?

With no output schema, the description carries the return-value burden and does so well by naming each returned block (depth per pool, flow, net flow per wallet, latest orders, coverage). It stops short of describing result shape or ordering, but the content is sufficient for an agent to call this correctly and interpret the numbers.

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 unit format, limit bounds and window enum are already fully documented; the description adds no format or constraint detail beyond what the schema provides. It only implicitly ties `window` to the flow figures, which is marginal added value over the schema's own text.

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 resource (one token's liquidity) and enumerates exactly what it returns: depth measured as ADA moved for a 2% price impact each way, plus flow of additions/removals, net flow per wallet and latest orders. That level of operational specificity clearly separates it from siblings like get_pool (single pool) or get_defi_tvl (protocol-level).

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

Usage Guidelines3/5

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

The description scopes usage implicitly by explaining that only constant-product ADA-paired pools with a fee are summed, which tells the agent when this tool's numbers are valid. But it never states when to choose this over get_pool, get_defi_tvl, get_token_prices, or get_recent_trades, and offers no exclusions or alternatives.

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

All Realtap toolsInspect
Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources