Coin Flip MCP Server
抛硬币 MCP 服务器
一个使用 random.org 随机性 API 提供真随机抛硬币功能的 MCP 服务器。该服务器通过提供可配置方向的随机结果生成工具来演示模型上下文协议 (MCP)。
特征
工具
flip_coin- 抛一枚可配置面数的硬币可选
sides参数(默认值:2)使用来自 random.org 的真正随机性
对边缘情况(0、1 或负数)的特殊处理
对于 2 面:返回“正面”或“反面”
对于三面:返回“正面”、“反面”或“_”
对于 n>3 面:返回“它落在 X 面上”
Related MCP server: MCP Lottery Demo
发展
安装依赖项:
npm install构建服务器:
npm run build对于使用自动重建的开发:
npm run watch安装
要与 Claude Desktop 一起使用,请添加服务器配置:
在 MacOS 上: ~/Library/Application Support/Claude/claude_desktop_config.json
在 Windows 上: %APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"coin-flip": {
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-coin-flip"]
}
}
}示例用法
连接到 Claude Desktop 等 MCP 客户端后,您可以使用自然语言与抛硬币工具进行交互。例如:
“抛硬币”
“掷一个六面骰子”
“给我一个 1 到 20 之间的随机数”
服务器将使用来自 random.org 的真正随机性来生成结果。
调试
由于 MCP 服务器通过 stdio 进行通信,调试起来可能比较困难。我们建议使用MCP Inspector :
npx @modelcontextprotocol/inspector node build/index.js贡献
欢迎贡献代码!欢迎提交 Pull 请求。
执照
麻省理工学院
Available Tools
1 toolflip_coinB
Flip a coin with n sides using true randomness from random.org. For 3-sided coins, try creative side names like:
past/present/future (temporal analysis)
true/unknown/false (epistemic states)
win/draw/lose (outcome evaluation)
rock/paper/scissors (cyclic relationships)
less/same/more (abstraction levels)
below/within/above (hierarchical positioning)
predecessor/current/successor (ordinal progression)
Meta-usage patterns:
Use less/same/more to guide abstraction level of discourse
Use past/present/future to determine temporal focus
Chain multiple flips to create decision trees
Use predecessor/current/successor for ordinal analysis
Ordinal Meta-patterns:
Use predecessor to refine previous concepts
Use current to stabilize existing patterns
Use successor to evolve into new forms
Default ternary values are -/0/+
| Name | Required | Description | Default |
|---|---|---|---|
| sideNames | No | Optional custom names for sides (must match number of sides) | |
| sides | No | Number of sides (default: 3) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the randomness source ('true randomness from random.org') and default behavior ('Default ternary values are -/0/+'), but it doesn't cover potential rate limits, error conditions, or output format details. This provides some behavioral context but leaves gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is overly verbose and poorly structured, with extensive examples and meta-patterns that may not all be necessary. It's front-loaded with the core purpose but then diverges into lengthy lists and patterns, reducing clarity and efficiency. Some content could be trimmed without losing essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (2 parameters, no output schema, no annotations), the description is somewhat complete but excessive. It covers purpose and usage ideas but lacks output details and could be more focused. The richness in examples compensates partially but doesn't fully align with the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, so the baseline is 3. The description adds value by explaining creative uses for 3-sided coins and meta-patterns, which indirectly clarifies parameter semantics (e.g., how 'sideNames' might be applied). However, it doesn't explicitly detail parameter meanings beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Flip a coin with n sides using true randomness from random.org.' This specifies the verb ('Flip'), resource ('coin'), and randomness source. However, it doesn't distinguish from siblings since there are none, so it can't achieve a perfect 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides implied usage through examples of 3-sided coins and meta-usage patterns, suggesting when to use specific configurations. However, it lacks explicit guidance on when to use this tool versus alternatives (none exist) or clear exclusions, keeping it at an intermediate level.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
v1.0.0- First observed
flip_coin
TDQS
Scored across 1 tool
With only one tool, there is no possibility of confusion or overlap between tools. The tool 'flip_coin' has a single, clearly defined purpose.
Since there is only one tool, naming consistency is inherently perfect. The tool name 'flip_coin' follows a clear verb_noun pattern.
A single tool is too few for a server's purpose, as it limits functionality and suggests an incomplete or overly narrow scope. While the tool is versatile, the server would benefit from additional tools to support more complex operations.
The server's domain appears to be random generation or decision-making, but with only one tool, there are significant gaps. For example, there are no tools for setting parameters, retrieving results, or managing multiple flips in a structured way, which limits agent workflows.
Maintenance
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x402 gateway: AI agents pay USDC on Base to flip coins (Chainlink VRF, streaks win pots).
Calibrated world model for AI agents. 40 tools: world state, markets, trading. Kalshi + Polymarket.
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