Alternative · News & journalism
Boring News vs
SimpleFunctions.
Same Polymarket signal, different surface. Boring News converts prediction-market odds into a daily AI-driven media show for passive consumption on YouTube, X, and podcast platforms. SimpleFunctions ships the agent layer beneath those same odds: a causal-tree thesis system, autonomous trading autopilot, calibrated world model across 48K+ contracts, and a 56-tool MCP server for any agent runtime.
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 workflows that need programmatic access to prediction-market signals — calibrated probabilities with public Brier scores, causal-tree thesis modelling with auto-evaluation cycles, computed indicators across the full 48K-contract universe (implied yield, cliff risk, liquidity availability score), and a 56-tool MCP server that drops into Claude Code or Cursor in one command.
Choose Boring News if
Boring News is the right choice if you want prediction-market-informed news delivered as a passive media product — a daily show on YouTube, X, or your podcast app, requiring no technical setup, no API key, and no trading infrastructure. It serves people who want broadcast-format clarity, not builders who need to query signals programmatically.
Boring News converts Polymarket odds into a daily broadcast; SimpleFunctions exposes those same odds as a programmable agent layer, with Kalshi added.
At a glance
Three things that
actually differ.
Everything Boring News gives you — a Polymarket-odds-informed view of current events — SimpleFunctions also gives you, via live programmatic access to the same Polymarket contracts plus Kalshi's full 48K+ market universe.
On top of that, SF ships a causal-tree thesis system, an autonomous trading agent (Portfolio Autopilot, 1M-context LLM, 7-gate risk cascade), and 56 MCP tools that no current prediction-market data or media product exposes.
SF publishes live Brier scores at /api/calibration — Kalshi 0.20, Polymarket 0.12 on T-24h price, past 90 days — so you can audit its accuracy rather than take it on faith.
Side by side
9 dimensions · verified 2026-04SimpleFunctionsKalshi + Polymarket normalised, 48K+ active contracts indexed.
Boring NewsPolymarket-based; Kalshi is not mentioned in public materials.
SimpleFunctionsProgrammatic REST API, CLI (60+ commands), and 56-tool MCP server providing machine-readable access to all contracts.
Boring NewsDaily video on YouTube, X posts, and podcast episodes — consumed passively, not queried programmatically.
SimpleFunctionsGET /api/public/market/{ticker}?depth=true — bid/ask ladder, spread, and slippage estimates.
Boring NewsNot published.
SimpleFunctionsImplied yield, cliff risk index, liquidity availability score, event overround, and τ-days pre-computed across 48K contracts at /screen.
Boring NewsNot published.
SimpleFunctionsLive Brier scores at /api/calibration — by venue, category, and price bucket.
Boring NewsNot published.
SimpleFunctionsPOST /api/thesis/create decomposes any sentence into a causal tree, scans for tradeable edges, and runs a continuous evaluation heartbeat.
Boring NewsNot in scope — Boring News is a media product, not an analytical tool.
SimpleFunctionsPortfolio Autopilot: 1M-context LLM, 13 data sources, 7-gate risk cascade before any execution.
Boring NewsNot in scope.
SimpleFunctions56 tools via claude mcp add simplefunctions --url https://simplefunctions.dev/api/mcp/mcp.
Boring NewsNo MCP server published.
SimpleFunctionsPublic REST, MCP, and CLI reads require no authentication. Thesis and intent execution: no charge up to 15M tokens, then pay-per-token.
Boring NewsNo pricing information published publicly.
Methodology
Verified 2026-04 from public sources only — Boring News's documentation, public website, and publicly observable behaviour. We never claim non-public information about Boring News'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 needs machine-readable Polymarket and Kalshi signals in a unified feed.
SimpleFunctions · best fit
SF exposes both venues via a unified REST API, CLI, and 56-tool MCP server. The /api/agent/world endpoint delivers a calibrated world snapshot in ~800 tokens, and /api/public/cross-venue/pairs surfaces arbitrage-matched contract pairs ready for agent consumption.
Boring News
Boring News is a broadcast product with no public API. An agent cannot query it programmatically or extract structured contract data from it.
Scenario 02
Staying current on what prediction markets are saying about major world events without any technical setup.
SimpleFunctions
SF provides the data programmatically but requires querying — it is not a passive media product and does not produce curated daily summaries you can subscribe to.
Boring News · best fit
Boring News is built for exactly this use case. Subscribe on YouTube, X, or a podcast app and receive a daily AI-driven briefing grounded in Polymarket odds. No API key, no code, no infrastructure.
Scenario 03
Decomposing a macro thesis — for example, 'US enters recession in 2026' — into testable sub-claims mapped to live contracts.
SimpleFunctions · best fit
POST /api/thesis/create with the sentence. SF decomposes it into a causal tree, propagates probabilities across nodes, identifies Kalshi and Polymarket contracts relevant to each sub-claim, and starts an evaluation heartbeat that refreshes on news and price changes.
Boring News
Not in scope — Boring News produces editorial content, not causal analysis tied to live contract prices.
Scenario 04
Auditing prediction-market accuracy before committing a research workflow to a data source.
SimpleFunctions · best fit
SF publishes live Brier scores at /api/calibration broken down by venue, category, and price bucket. You can curl the endpoint and verify the numbers yourself before writing a single line of integration code.
Boring News
Boring News does not publish calibration or accuracy metrics for its odds-based editorial process.
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
What is the fundamental difference between SimpleFunctions and Boring News?+
SimpleFunctions is programmatic infrastructure — a REST API, CLI, and MCP server for agents and researchers who need machine-readable prediction-market signals from Kalshi and Polymarket. Boring News is a media product: a daily AI-driven news show that uses Polymarket odds as editorial context, distributed passively on YouTube, X, and podcast platforms. They serve almost entirely different audiences and are not substitutes for each other.
How does SimpleFunctions' causal thesis system work?+
POST /api/thesis/create with a plain-English sentence. SF decomposes it into a causal tree of testable sub-claims, propagates implied probabilities across nodes, and scans Kalshi and Polymarket for contracts tradeable as edges against each sub-claim. An evaluation heartbeat then runs continuously: news scan, price refresh, milestone check, LLM evaluation, confidence update. You can inject external signals via /api/thesis/{id}/signal, and public theses are forkable by other users.
Can SimpleFunctions replace Boring News for daily news consumption?+
No, and it is not trying to. Boring News is optimised for passive broadcast consumption — you watch or listen and receive a prediction-market-informed editorial summary. SF is programmatic infrastructure: you query it, not tune into it. If you need to know what markets price on a specific question, SF's /api/public/scan or the /screen indicators surface that signal. If you want a curated daily briefing in your podcast app, Boring News serves that need directly.
What is Portfolio Autopilot and how does it differ from reading a news show?+
Portfolio Autopilot is SF's autonomous trading agent. It uses a 1M-context LLM, 13 data sources, and a 7-gate risk cascade — kill switch, position limits, drawdown gate, regime check, and more — to evaluate and execute trades across Kalshi and Polymarket. It is designed for users who want algorithmic exposure to prediction markets with transparent, auditable risk controls. Boring News is an editorial product; it does not execute trades or expose a risk-management framework.
Does SimpleFunctions have an MCP server?+
Yes. Run claude mcp add simplefunctions --url https://simplefunctions.dev/api/mcp/mcp to add 56 tools to Claude Code or any MCP-compatible client. Tools span market lookup, thesis creation and signal injection, cross-venue arbitrage scanning, indicator retrieval, portfolio queries, and the calibrated world-state snapshot. No configuration beyond the one-liner. Boring News has no published MCP server.
Where can I verify SimpleFunctions' accuracy claims?+
SF publishes live Brier scores at /api/calibration, broken down by venue, category, and price bucket. Current baselines are Kalshi 0.20 and Polymarket 0.12 on T-24h price, computed over the past 90 days. You can re-verify with a curl call at any time. Boring News does not publish equivalent calibration or accuracy data for its Polymarket-informed editorial process.
Does Boring News cover Kalshi, or only Polymarket?+
Based on publicly available information, Boring News uses Polymarket prediction-market odds as the structural foundation for its news show. Kalshi is not mentioned in their public materials. SimpleFunctions covers both Kalshi and Polymarket, normalised into a unified 48K+ contract index accessible via REST API, CLI, and MCP server.
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.