Random Generator MCP Tools for AI Agents

Your agent generates "random" test data but produces suspiciously similar outputs every time. LLMs don't have access to random number generators — they output what's statistically likely. These tools generate genuinely random data across many types.

All Random Tools (35)

Your agent gets access to 35 random tools via the /mcp/random/ endpoint. Here's the complete list:

Tool	Description
`random/integer`	Random Integer
`random/float`	Random Float
`random/boolean`	Random Boolean
`random/choice`	Random Choice
`random/weighted-choice`	Random Weighted Choice
`random/shuffle`	Random Shuffle
`random/string`	Random String
`random/bytes`	Random Bytes
`random/uuid`	Random Uuid
`random/gaussian`	Random Gaussian
`random/date`	Random Date
`random/time`	Random Time
`random/color`	Random Color
`random/name`	Random Name
`random/email`	Random Email
`random/phone`	Random Phone
`random/ip`	Random Ip
`random/mac`	Random Mac
`random/coordinates`	Random Coordinates
`random/dice`	Random Dice
`random/coin`	Random Coin
`random/card`	Random Card
`random/password`	Random Password
`random/hex`	Random Hex
`random/element`	Random Element
`random/emoji`	Random Emoji
`random/address`	Random Address
`random/company`	Random Company
`random/job`	Random Job
`random/person`	Random Person
`random/text`	Random Text
`random/username`	Random Username
`random/url`	Random Url
`random/credit-card`	Random Credit Card
`random/locales`	List Locales

Agent Scenarios

Here's how real agents use these tools:

1. Test data generation agent

A QA agent generates random user profiles with names, emails, and dates for load testing.

Tool Call: random/integer

{ "min": 1, "max": 1000000 }

2. Seed data agent

A development agent creates random but realistic data for database seeding.

Tool Call: random/date

{ "start": "2020-01-01", "end": "2026-12-31" }

3. Sampling agent

A data science agent generates random floats for Monte Carlo simulation inputs.

Tool Call: random/float

{ "min": 0, "max": 1 }

MCP Setup

Add random tools to your agent in under 2 minutes. Choose your client:

Claude Desktop / Claude Code

Add this to your MCP config:

{
  "mcpServers": {
    "tinyfn-random": {
      "url": "https://api.tinyfn.io/mcp/random/",
      "headers": {
        "X-API-Key": "your-api-key"
      }
    }
  }
}

Cursor

Go to Settings > MCP and add a new server:

Type: SSE
URL: https://api.tinyfn.io/mcp/random/sse
Headers: X-API-Key: your-api-key

Tip: Use the category-specific endpoint (/mcp/random/) for the best experience. The all-in-one endpoint (/mcp/all/) works too but has 500+ tools which some clients handle less efficiently.

When to Use These Tools

Use random MCP tools when your agent needs to:

Guarantee correctness — when wrong answers have real consequences
Process user data — when you're operating on actual user input, not hypothetical examples
Maintain consistency — when the same input must always produce the same output

You don't need these tools for casual conversation or rough estimates. Use them when precision matters.

Ready to add random tools to your agent?

Get Free API Key 100 requests/month free. No credit card required.

Frequently Asked Questions

How is TinyFn random generation different from LLM output?

TinyFn uses Python's random module (or secrets for crypto), which produces truly random numbers from system entropy. LLMs generate numbers that appear random but are actually deterministic predictions.

What types of random data can TinyFn generate?

TinyFn generates random integers, floats, booleans, strings, UUIDs, dates, colors, names, emails, IPs, coordinates, and supports weighted choices and gaussian distributions.

Can TinyFn generate reproducible random data?

TinyFn generates fresh random data on each call. For reproducible sequences, use a seed-based approach in your own code with TinyFn providing the random values.