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Binance MCP Server

Binance MCP Server

by Lubodi-Code
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

place_order

Place buy or sell orders on Binance Spot. Specify symbol, side, order type, and quantity, with price required for limit orders.

Instructions

Crea una orden de compra/venta. symbol: ej 'BTCUSDT' side: 'BUY' o 'SELL' order_type: 'MARKET' o 'LIMIT' quantity: cantidad del activo base price: requerido solo para LIMIT time_in_force: GTC / IOC / FOK (solo LIMIT)

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": {
      "symbol": "<symbol>",
      "side": "<side>"
    },
    "name": "place_order"
  }
}

Input Schema

NameRequiredDescriptionDefault
sideYes
priceNo
symbolYes
quantityNo
order_typeNoMARKET
time_in_forceNoGTC

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions parameter constraints (price only for LIMIT, time_in_force only for LIMIT) but does not disclose that placing an order executes a financial transaction, may require permissions/funds, or what happens after submission. No info on idempotency or error 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 a compact, bullet-list format covering each parameter succinctly with examples. No redundant or filler content; every line adds information.

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?

The tool is moderately complex with no output schema or annotations. The description covers purpose and parameters well but omits usage context, return values (e.g., order ID), and operational behavior. It is adequate for parameter reference but not fully complete for decision-making.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description fully compensates by explaining each parameter with examples and constraints. It defines symbol, side, order_type, quantity (base asset), price (required only for LIMIT), and time_in_force (GTC/IOC/FOK, only LIMIT), adding meaning beyond the bare 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?

The description clearly states 'Crea una orden de compra/venta' (creates a buy/sell order), using a specific verb and resource. This distinguishes it from siblings like get_price, cancel_order, and withdraw, as it is the only one that places orders.

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 implies usage through the purpose but does not explicitly state when to use this tool versus alternatives (e.g., 'use get_price to check prices before placing an order'). There is no mention of prerequisites, exclusions, or context like market vs limit behavior beyond parameter constraints.

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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