Alternative · On-chain market
Azuro vs
SimpleFunctions.
Azuro provides on-chain EVM infrastructure for developers building decentralized sportsbooks and event-prediction front-ends with shared liquidity. SimpleFunctions is the agent layer above off-chain prediction markets: a causal-tree thesis system with auto-evaluation cycles, an autonomous trading agent with a 7-gate risk cascade, computed indicators across 48K+ contracts, and a 56-tool MCP server that plugs into any AI agent in one command.
Verified 2026-04 · public sources only · live SF data from /calibration
Verdict
Pick the one that fits how
you actually work.
Choose SimpleFunctions if
You are building agents, autonomous trading systems, or research pipelines that need more than raw market data — calibrated probabilities with public Brier scores, a causal-tree thesis system that decomposes any claim into testable sub-claims and scans Kalshi and Polymarket for edges, regime classification across 48K contracts, computed indicators (implied yield, cliff risk, liquidity availability score), and a 56-tool MCP server ready for Claude Code or Cursor in one command.
Choose Azuro if
You are building a decentralized sportsbook or event-prediction front-end on EVM chains. Azuro provides the shared LiquidityTree, vAMM, and AzuroSDK that power products like BetSwirl and BookmakerXYZ. If your product requires on-chain pooled liquidity infrastructure rather than programmatic access to off-chain prediction markets, Azuro is the right layer.
Azuro is on-chain EVM infrastructure for sportsbook builders. SimpleFunctions is an off-chain agent layer for prediction market traders, researchers, and autonomous systems.
At a glance
Three things that
actually differ.
Everything Azuro gives you — event-prediction infrastructure, shared liquidity, and SDK tooling for building market front-ends — SimpleFunctions also gives you as normalized REST and MCP access to Kalshi and Polymarket with cross-venue pricing and orderbook depth.
On top of that, SF ships a causal-tree thesis system, an autonomous trading agent (Portfolio Autopilot, 1M-context LLM, 7-gate risk cascade), computed indicators across 48K+ contracts, and 56 MCP tools no current on-chain protocol exposes.
SF publishes live Brier scores at /api/calibration — Kalshi 0.20, Polymarket 0.12 on T-24h price, past 90 days. Azuro is a liquidity infrastructure layer and does not publish a prediction accuracy baseline.
Side by side
10 dimensions · verified 2026-04SimpleFunctionsNormalised prices across Kalshi and Polymarket, 48K+ active contracts indexed live.
AzuroEVM-native sports and event prediction markets with shared on-chain liquidity; distinct from Kalshi and Polymarket.
SimpleFunctionsOff-chain REST API, MCP server, and CLI — no wallet or gas required.
AzuroOn-chain EVM smart contracts with a vAMM and LiquidityTree; interactions require on-chain transactions.
SimpleFunctionsREST endpoints, 56-tool MCP server (claude mcp add simplefunctions), and a CLI (npm i -g @spfunctions/cli) for scripting and agent integration.
AzuroAzuroSDK for building EVM-native sportsbook and event-prediction front-ends; currently powers products like BetSwirl and BookmakerXYZ.
SimpleFunctionsGET /api/public/market/{ticker}?depth=true returns bid/ask ladder, spread, and slippage estimates.
AzuroLiquidity is pooled via vAMM; no traditional orderbook ladder is exposed.
SimpleFunctionsImplied yield, cliff risk index, liquidity availability score, event overround, τ-days, and regime label — pre-computed across 48K contracts at /screen.
AzuroNot published; Azuro is a liquidity infrastructure layer, not a market analytics product.
SimpleFunctionsLive Brier scores at /api/calibration — Kalshi 0.20, Polymarket 0.12 on T-24h price, past 90 days.
AzuroNot published; Azuro does not produce a probability accuracy baseline.
SimpleFunctionsPOST /api/thesis/create decomposes any claim into a testable causal tree, scans Kalshi and Polymarket for edges, and runs an auto-evaluation heartbeat.
AzuroNot in scope; Azuro provides liquidity infrastructure, not a thesis or research layer.
SimpleFunctionsPortfolio Autopilot — 1M-context LLM, 13 data sources, 7-gate risk cascade before each trade execution.
AzuroNot in scope.
SimpleFunctions56 tools via claude mcp add simplefunctions --url https://simplefunctions.dev/api/mcp/mcp; works with Claude Code, Cursor, and any MCP client.
AzuroNo MCP server published.
SimpleFunctionsPublic REST, MCP, and CLI reads require no authentication. Thesis and intent execution: free up to 15M tokens, then pay-per-token.
AzuroOn-chain protocol; fees are governed by smart contract parameters rather than a subscription tier. Public documentation does not specify a flat rate.
Methodology
Verified 2026-04 from public sources only — Azuro's documentation, public website, and publicly observable behaviour. We never claim non-public information about Azuro's internals. SimpleFunctions claims on this page are computed live from /api/calibration, /api/public/cross-venue/pairs, and /api/public/markets — you can re-verify them yourself with curl.
Use cases
Same data, different
best fit per scenario.
Scenario 01
Building an AI agent that monitors prediction market contracts and executes trades autonomously.
SimpleFunctions · best fit
SF exposes a 56-tool MCP server, a causal-thesis pipeline, and Portfolio Autopilot with a 7-gate risk cascade. The agent layer is designed for this exact pattern — read markets, evaluate theses, execute with risk gates.
Azuro
Azuro targets human-facing front-end builders on EVM, not programmatic agent integrations on off-chain venues. It does not offer a REST or MCP interface aligned to this workflow.
Scenario 02
Launching a decentralized sportsbook product on an EVM chain with pooled liquidity.
SimpleFunctions
SF does not provide on-chain smart contract infrastructure or a shared liquidity pool. It is not the right tool for building a decentralized sportsbook.
Azuro · best fit
Azuro exists precisely for this. Its LiquidityTree, vAMM, and AzuroSDK provide the on-chain primitives for building products like BetSwirl and BookmakerXYZ — this is their core product focus.
Scenario 03
Decomposing a geopolitical thesis into a set of tradeable prediction market contracts.
SimpleFunctions · best fit
POST /api/thesis/create accepts any natural-language claim, decomposes it into a causal tree of testable sub-claims, and scans Kalshi and Polymarket for contracts where an edge exists. An evaluation heartbeat refreshes confidence as news arrives.
Azuro
Azuro does not offer a thesis decomposition or research layer. Its scope is on-chain liquidity infrastructure for sportsbook builders.
Scenario 04
Scanning cross-venue arbitrage opportunities between Kalshi and Polymarket in real time.
SimpleFunctions · best fit
GET /api/public/cross-venue/pairs?preset=arb returns matched pairs with normalised prices and spread. Computed indicators — implied yield, event overround — are pre-calculated across 48K contracts.
Azuro
Azuro operates on EVM chains with its own liquidity pool and does not index Kalshi or Polymarket contracts. Cross-venue arbitrage scanning against those venues is outside its scope.
Live data
The SimpleFunctions claims on this page are not marketing copy. Brier scores, market counts, and cross-venue pair counts are computed live from /calibration, /screen, and /api/public/cross-venue/pairs. All public, all free, all CC-BY-4.0.
FAQ
How does SimpleFunctions' causal thesis system work?+
POST /api/thesis/create takes any natural-language claim — for example, 'The Fed cuts rates before December' — and decomposes it into a causal tree of testable sub-claims. Each node is mapped to contracts on Kalshi and Polymarket where a tradeable edge exists. An evaluation heartbeat runs continuously: news scan, price refresh, milestone check, LLM evaluation, and confidence update. You can inject new signals via /api/thesis/{id}/signal. Public theses are forkable. No current prediction market data product offers this pipeline.
What is Portfolio Autopilot and how does the risk cascade work?+
Portfolio Autopilot is SF's autonomous trading agent. It uses a 1M-context LLM and 13 data sources to identify and size positions. Before any trade executes, it passes through a 7-gate risk cascade: kill switch, position limits, drawdown gate, regime check, and additional safeguards. The system logs every decision for audit. It is designed for autonomous operation rather than a human-in-the-loop dashboard workflow.
Does SimpleFunctions have an MCP server?+
Yes. Run claude mcp add simplefunctions --url https://simplefunctions.dev/api/mcp/mcp to register 56 tools in Claude Code, Cursor, or any MCP-compatible client. Tools cover market search, thesis creation, cross-venue arbitrage scanning, world snapshot, orderbook depth, computed indicators, and more. No authentication is required for read operations.
Can SimpleFunctions connect to Azuro or EVM prediction markets?+
No. SimpleFunctions indexes Kalshi and Polymarket — off-chain, regulated prediction markets. Azuro operates on EVM chains as a decentralized sportsbook and event-prediction protocol. These are distinct ecosystems. If your goal is on-chain sportsbook infrastructure with pooled liquidity, Azuro's AzuroSDK is the right starting point. If your goal is programmatic access to off-chain prediction markets for agents or research, SF is the appropriate layer.
How does SF's calibration baseline work, and why does it matter?+
GET /api/calibration returns SF's own Brier scores broken down by venue, category, and price bucket. Current figures: Kalshi 0.20, Polymarket 0.12 on T-24h price, past 90 days. Brier score measures probability accuracy — lower is better. Publishing this lets you verify SF's accuracy before committing capital. Azuro is a liquidity infrastructure layer and does not publish a probability accuracy baseline.
What computed indicators does SimpleFunctions expose?+
SF pre-computes six indicators across 48K+ active contracts: IY (implied yield), CRI (cliff risk index, measuring non-linear settlement risk), LAS (liquidity availability score), EE (event overround, measuring book margin), τ-days (time to settlement), and a regime label that classifies each market's adverse-selection environment. All are available at /screen without authentication and queryable via the MCP server.
Who should choose Azuro over SimpleFunctions?+
Developers building decentralized sportsbook or event-prediction front-ends on EVM chains. Azuro provides the shared LiquidityTree, vAMM, and AzuroSDK that power products like BetSwirl and BookmakerXYZ. If your product requires on-chain pooled liquidity infrastructure for sports markets, Azuro is purpose-built for that audience. SF does not offer on-chain smart contract infrastructure and is not the right tool for that use case.
Start for free.
Public endpoints are free for normal usage and rate-limited for reliability. Authenticated endpoints are free up to 15M tokens, then pay per token. No credit card to start.