Binance MCP Server 🚀

Created By
AnalyticAcea year ago
Unofficial tools and server implementation for Binance's Model Context Protocol (MCP). Designed to support developers building crypto trading AI Agents.
Overview

What is Binance MCP Server?

Binance MCP Server is an unofficial tool and server implementation for Binance's Model Context Protocol (MCP), designed to support developers in building AI agents for cryptocurrency trading.

How to use Binance MCP Server?

To use the Binance MCP Server, install it via Python package management, configure your Binance API credentials, and launch the server to connect your AI trading agents.

Key features of Binance MCP Server?

  • Secure API key-based authentication with Binance.
  • Real-time market data access including live price feeds and order book data.
  • Trading operations for placing, modifying, and canceling orders.
  • Portfolio management tools for tracking account balances and positions.
  • Smart notifications for market events and order updates.
  • Built-in risk management features for safe trading operations.

Use cases of Binance MCP Server?

  1. Developing AI trading bots that interact with Binance.
  2. Real-time market analysis and trading strategy implementation.
  3. Automated portfolio management and performance tracking.

FAQ from Binance MCP Server?

  • Can I use Binance MCP Server for live trading?

Yes, but ensure to test thoroughly on the Binance testnet first.

  • Is there documentation available?

Yes, comprehensive documentation is provided on the project's GitHub page.

  • What programming language is used?

The server is implemented in Python.

Project Info
Created At
a year ago
Updated At
a year ago
Author Name
AnalyticAce
Star
1
Language
Python
License
MIT license

Recommend Servers

View All
Docwand

14 hours ago
//beforeyouship — LLM Cost Modeling From Your Editor
@Indiegoing

Query realistic LLM cost models without leaving your editor. beforeyouship models the **true monthly cost** of an LLM app architecture — retries, prompt caching, batch discounts, infra overhead, and 3×/10× growth — across GPT-5.x, Claude, Gemini, DeepSeek, and more. Not a token calculator: a planning tool for the design phase, before you commit to a stack. **No API key needed to try it** — demo mode covers the six free-tier models. A Pro key from [beforeyouship.dev](https://beforeyouship.dev) unlocks the full 18-model catalog. ## What you can ask - "How much will a RAG chatbot cost at 10,000 requests/day?" - "Compare Claude Haiku vs Gemini Flash pricing for my workload" - "What's the cheapest model for a multi-step agent at scale?" - "Show me current per-token prices for Anthropic models" ## Tools ### `estimate_cost` Full cost model for an architecture at a given usage level. Returns Naive / Realistic / Worst Case monthly cost per model, 3×/10× growth scenarios, and an opinionated recommendation with reasoning. ### `get_model_prices` Current per-1M-token pricing — input, output, cached input, batch — with context windows and staleness metadata. ### `list_archetypes` Seven preset architecture patterns (simple chatbot, chatbot with history, RAG pipeline, multi-model router, coding assistant, document processor, multi-step agent) used as starting points for estimates. ## Setup **Claude Code:** ​```bash claude mcp add --transport http beforeyouship https://beforeyouship.dev/api/mcp ​``` **Cursor / other clients** — add a remote server: ​```json { "mcpServers": { "beforeyouship": { "type": "streamable-http", "url": "https://beforeyouship.dev/api/mcp" } } } ​``` Add an `Authorization: Bearer bys_...` header with a Pro key for the full catalog. ## Try it > Estimate the monthly cost of a RAG pipeline at 10,000 requests/day

14 hours ago