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CoinLobster MCP

CoinLobster MCP

Official
by CoinLobster
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

One-call trade context

trade_context
Read-onlyIdempotent

Retrieve pre-trade market context for any crypto pair: price, funding, open interest, whale flow, and recent liquidations in a single call. Add position_usd for carry arithmetic.

Instructions

The pre-trade context blob in one call: price, cross-venue funding with time-to-next-funding and carry arithmetic (optional position_usd), open interest, whale flow vs the coin's own baseline, and recent visible liquidations, on ANY streamed pair keyless. compact: true returns the one-line composed answer (about 30 tokens). A paid developer plan adds the percentile judgment vs the pair's own recorded days, whale USD magnitudes, full 24h stats and the crowding score. Strictly descriptive: state plus recorded history, no advice. Descriptive market data only. More depth on a developer plan: coinlobster.com/developers?utm_source=mcp&utm_medium=agent

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "trade_context"
  }
}

Input Schema

NameRequiredDescriptionDefault
pairNo
compactNo
position_usdNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.3/5.0
Behavior5/5

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

Beyond the annotations (readOnlyHint=true, idempotentHint=true), the description adds valuable behavioral context: 'Strictly descriptive: state plus recorded history, no advice' and 'Descriptive market data only.' It also discloses the limitation that certain metrics require a paid plan, and explains the compact mode's token count.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose and list of contents, but it becomes verbose and redundant. 'Strictly descriptive: state plus recorded history, no advice' and 'Descriptive market data only' say the same thing twice, and the trailing developer-plan URL with UTM parameters is unnecessary for tool invocation.

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

Completeness3/5

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

With no output schema, the description needs to explain the return structure, but it only provides a high-level list of content areas. It does not describe the response format, field names, units, time ranges, or how the non-compact output is organized. The paid-plan caveat is useful, but the absence of output details leaves the agent guessing about the actual result shape.

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 description coverage is 0%, but the description compensates for all three parameters: pair is explained as 'ANY streamed pair keyless', compact is defined as returning a one-line composed answer of about 30 tokens, and position_usd is tied to 'carry arithmetic'. This provides meaningful semantics beyond the bare schema types.

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 returns a pre-trade context blob in one call, enumerating the key data points (price, funding, open interest, whale flow, liquidations). This specific verb+resource framing distinguishes it from the specialized sibling tools like whale_trades or liquidations by emphasizing the aggregated, one-call nature.

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?

The phrase 'pre-trade context blob in one call' clearly indicates when to use it: when you need a comprehensive market context before a trade. It notes the compact option for a shorter answer, but does not explicitly say when not to use it or name alternative tools for narrower queries.

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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