Coin Flip MCP Server
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Coin Flip MCP Serverflip a coin to decide who goes first"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Coin Flip MCP Server
An MCP server that provides true random coin flips using random.org's randomness API. This server demonstrates the Model Context Protocol by providing a tool for generating random outcomes with configurable sides.
Features
Tools
flip_coin- Flip a coin with configurable number of sidesOptional
sidesparameter (default: 2)Uses true randomness from random.org
Special handling for edge cases (0, 1, or negative sides)
For 2 sides: Returns "Heads" or "Tails"
For 3 sides: Returns "Heads", "Tails", or "_"
For n>3 sides: Returns "It landed on side X"
Related MCP server: MCP Lottery Demo
Development
Install dependencies:
npm installBuild the server:
npm run buildFor development with auto-rebuild:
npm run watchInstallation
To use with Claude Desktop, add the server config:
On MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"coin-flip": {
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-coin-flip"]
}
}
}Example Usage
Once connected to an MCP client like Claude Desktop, you can use natural language to interact with the coin flip tool. For example:
"Flip a coin"
"Roll a 6-sided die"
"Give me a random number between 1 and 20"
The server will use true randomness from random.org to generate the result.
Debugging
Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the MCP Inspector:
npx @modelcontextprotocol/inspector node build/index.jsContributing
Contributions are welcome! Please feel free to submit a Pull Request.
License
MIT
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
Related MCP Connectors
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.
OpenAI-compatible LLM MCP (7 tools); chat via balance key or x402 USDC on Base
Pay-per-call agent tools via x402 (USDC on Base): chat, prices, funding, RNG. No account or keys.
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