When Agents Guess, Systems Break
Autonomous agents make thousands of decisions without human oversight. One bad calculation cascades through your entire pipeline.
Task: Process 10,000 customer records, convert timestamps, calculate ages
LLM guesses wrong on 2% of date calculations
→ 200 records with incorrect ages, compliance violations, refund claims
Task: Calculate totals with tax, apply discounts, convert currencies
LLM rounds incorrectly, misses decimal precision
→ $0.01-$0.10 errors per invoice × 50,000 invoices = $2,500+ discrepancy
Task: Generate UUIDs for new records, hash sensitive fields, validate formats
LLM invents malformed UUIDs, inconsistent hash outputs
→ Database constraint violations, failed joins, broken references
Real Agent Workflow: Order Processing
See how an autonomous agent handles a multi-step order fulfillment task with TinyFn tools.
E-Commerce Order Agent
When a new order comes in, your agent needs to validate the data, calculate shipping, apply promotions, and generate tracking info—all without human intervention. Every step needs to be deterministic.
Validate customer email
RFC-compliant validation, not regex guessing
validate/email → true (valid format)Calculate shipping date
Add 5 business days, handling weekends and holidays
datetime/add_business_days → 2026-02-10Apply promo discount
Calculate 25% off $149.97 with proper rounding
finance/calculate_discount → $112.48 finalGenerate order ID
Create RFC 4122 compliant UUID for tracking
generate/uuid → 7c9e6679-...Hash customer data
SHA-256 hash for PII in analytics
hash/sha256 → a3f2b8c1...Convert timezone for email
Show delivery time in customer's local timezone
time/convert → 2:00 PM PSTWhy Deterministic Tools Matter
Autonomous agents can't ask for clarification. They need tools that work the same way every time.
What "Deterministic" Means
LLM Response (Non-deterministic)
Ask "What's 15% of $283.47?" three times, get three slightly different answers based on token sampling.
TinyFn Tool (Deterministic)
Call math/percentage(283.47, 15) one million times, get 42.52 every single time.
Works With Your Agent Framework
TinyFn MCP integrates with any framework that supports the Model Context Protocol.
Pydantic AI
Python agents with type-safe tool definitions
from pydantic_ai import Agent
Vercel AI SDK
TypeScript/JavaScript agent pipelines
import { generateText } from 'ai'
LangChain
Multi-step agent chains and workflows
from langchain.agents import AgentExecutor
Claude Code
Native MCP support for agentic coding
claude --mcp-config mcp.json
Tool Categories
30+ categories covering everything autonomous agents need.
Validation
Email, URL, UUID, phone, JSONConversion
Units, currency, temperatureHash & Crypto
SHA-256, MD5, HMAC, bcryptDate & Time
Parsing, formatting, zonesFinance
Discounts, interest, paymentsEncoding
Base64, URL, HTML, JWTQuick Setup
Add TinyFn to any MCP-compatible agent framework.
{
"mcpServers": {
"tinyfn": {
"url": "https://api.tinyfn.io/mcp/all/",
"headers": {
"X-API-Key": "your-api-key"
}
}
}
}
Works with any MCP client
TinyFn MCP integrates with Claude Desktop, Cursor, Windsurf, VS Code, and any framework that supports the Model Context Protocol. Get your free API key and start building reliable agents.
Build reliable AI agents
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