predictfun-mcp

predictfun-mcp is a skill for Claude Code, Codex from PaulieB14/predictfun-subgraphs. It costs 36 tokens per session (1,498 once invoked), scanned A, original, MIT.

An MCP skill for reading and analyzing Predict.fun prediction-market data on BNB Chain, a blockchain network.

In plain words
What is it for?
It helps inspect platform statistics, rank and research markets, profile traders, review recent activity, analyze yield, and find large positions.
Why use it?
It organizes platform, market, trader, activity, and yield information into defined analysis tools. This reduces the need to assemble those details manually from blockchain data.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: built for openclaw.

Good fit It helps inspect platform statistics, rank and research markets, profile traders, review recent activity, analyze yield, and find large positions.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/paulieb14/predictfun-subgraphs/mcp-server
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add PaulieB14/predictfun-subgraphs --skill mcp-server
Clone the repo
git clone --depth 1 https://github.com/PaulieB14/predictfun-subgraphs

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for predictfun-mcp

README.md
[![agentmods](https://agentmods.dev/badge/skills/paulieb14/predictfun-subgraphs/mcp-server.svg)](https://agentmods.dev/skills/paulieb14/predictfun-subgraphs/mcp-server)
Your own site
<a href="https://agentmods.dev/skills/paulieb14/predictfun-subgraphs/mcp-server"><img src="https://agentmods.dev/badge/skills/paulieb14/predictfun-subgraphs/mcp-server.svg" alt="Measured on agentmods" height="20"></a>
Per session 36 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,498 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00036 $0.01498
Opus 5 $0.00018 $0.00749
Sonnet 5 $0.00007 $0.00300
Haiku 4.5 $0.00004 $0.00150

Measured 7d ago against content hash 8bc791c095a3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

predictfun-mcp scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.

The scan reads SKILL.md. This mod also ships 3 executable files (dist/index.d.ts, dist/index.js, src/index.ts), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

mcp-server/SKILL.md · 94 lines

How it starts

The opening of the file, as written. The whole thing — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Predict.fun MCP

Structured access to Predict.fun prediction market data on BNB Chain — platform stats, market analysis, trader profiling, yield mechanics, and behavioral meta-tools.

Tools

  • get_platform_stats — Full platform overview: volume, OI, yield, sync status
  • get_top_markets — Rank markets by volume, open interest, or trade count. OI mode flags zombie OI. NegRisk markets show human-readable names (e.g., "Will Spain win the 2026 FIFA World Cup?")
  • get_market_details — Deep dive: OI, resolution, top holders (User/Bot/EOA/Protocol labels), orderbook stats, oracle contract identification, zombie OI detection with redemption context
  • get_trader_profile — Full P&L: trades, positions, payouts, yield rewards. Distinguishes Privy smart wallet users from bots and protocol contracts
  • get_recent_activity — Latest trades, splits, merges, redemptions, or yield claims
  • get_yield_overview — Venus Protocol yield stats with context: on-chain claims are protocol-level settlements, per-user yield accrues via position value snapshots
  • get_whale_positions — Largest holders with % of market OI, market names, User/Bot/EOA labels (protocol contracts filtered at query level)
  • get_leaderboard — Top traders by volume, payouts, or trade count with User/Bot/EOA labels (protocol contracts filtered at query level)
  • get_resolved_markets — Recently settled markets with outcomes and condition IDs
  • query_subgraph — Custom GraphQL against any of the three subgraphs
  • find_trader_persona — Classify a trader: whale, yield farmer, arbitrageur, early mover, sniper
  • scan_trader_personas — Find traders matching a behavioral archetype (protocol contracts excluded from whale scan)
  • tag_market_structure — Tag a market by type (standard, neg_risk, ct_yield, bond), resolution latency, liquidity, oracle type with contract identification, tail risk with zombie OI flags
  • scan_markets_by_structure — Find markets by structural filter

Read the full file on GitHub · 94 lines

Files

What ships with it

9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 7d ago First seen · 94 lines · 36 tokens per session scan A 8bc791c095a3

Subscribe to this mod's changes

predictfun-mcp is a skill published in the GitHub repository PaulieB14/predictfun-subgraphs (0 stars, last pushed 5mo ago), licensed MIT. It adds 36 tokens to every session and 1,498 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.