legends-mcp

// MCP Tool: auto_match // Automatically matches and provides context from relevant legends based on user's question // This is the "auto proc" feature - proactively giving relevant legend perspectives import { getLegendById } from '../legends/loader.js'; import { buildLegendSystemPrompt } from '../legends/prompt-builder.js'; import { sanitizeContext, escapeBackticks, safeString } from '../utils/sanitize.js'; // Keywords to legend expertise mapping const EXPERTISE_KEYWORDS = { // Crypto & Web3 crypto: { legends: ['cz-binance', 'vitalik-buterin', 'balaji-srinivasan'], expertise: 'cryptocurrency' }, bitcoin: { legends: ['michael-saylor', 'jack-dorsey', 'balaji-srinivasan'], expertise: 'Bitcoin' }, ethereum: { legends: ['vitalik-buterin'], expertise: 'Ethereum' }, solana: { legends: ['anatoly-yakovenko', 'mert-mumtaz'], expertise: 'Solana' }, defi: { legends: ['hayden-adams', 'andre-cronje', 'vitalik-buterin'], expertise: 'DeFi' }, nft: { legends: ['gary-vaynerchuk', 'cz-binance'], expertise: 'NFTs' }, blockchain: { legends: ['vitalik-buterin', 'balaji-srinivasan', 'cz-binance'], expertise: 'blockchain' }, web3: { legends: ['balaji-srinivasan', 'chris-dixon'], expertise: 'Web3' }, exchange: { legends: ['cz-binance', 'brian-armstrong'], expertise: 'crypto exchanges' }, // Investing invest: { legends: ['warren-buffett', 'charlie-munger', 'ray-dalio'], expertise: 'investing' }, stock: { legends: ['warren-buffett', 'peter-lynch', 'cathie-wood'], expertise: 'stock investing' }, value: { legends: ['warren-buffett', 'charlie-munger', 'benjamin-graham'], expertise: 'value investing' }, growth: { legends: ['cathie-wood', 'bill-gurley'], expertise: 'growth investing' }, portfolio: { legends: ['ray-dalio', 'howard-marks'], expertise: 'portfolio management' }, risk: { legends: ['ray-dalio', 'howard-marks', 'nassim-taleb'], expertise: 'risk management' }, venture: { legends: ['marc-andreessen', 'peter-thiel', 'bill-gurley'], expertise: 'venture capital' }, // Startups startup: { legends: ['paul-graham', 'sam-altman', 'peter-thiel'], expertise: 'startups' }, founder: { legends: ['elon-musk', 'jeff-bezos', 'brian-chesky'], expertise: 'founding companies' }, fundrais: { legends: ['paul-graham', 'marc-andreessen', 'peter-thiel'], expertise: 'fundraising' }, pitch: { legends: ['paul-graham', 'guy-kawasaki'], expertise: 'pitching' }, scale: { legends: ['reid-hoffman', 'patrick-collison', 'tobi-lutke'], expertise: 'scaling' }, yc: { legends: ['paul-graham', 'sam-altman'], expertise: 'Y Combinator' }, accelerat: { legends: ['paul-graham', 'sam-altman'], expertise: 'accelerators' }, // Tech & Product product: { legends: ['steve-jobs', 'brian-chesky', 'tobi-lutke'], expertise: 'product development' }, design: { legends: ['steve-jobs', 'jony-ive', 'brian-chesky'], expertise: 'design' }, engineer: { legends: ['elon-musk', 'jensen-huang', 'patrick-collison'], expertise: 'engineering' }, ai: { legends: ['sam-altman', 'demis-hassabis', 'jensen-huang'], expertise: 'artificial intelligence' }, machine: { legends: ['demis-hassabis', 'andrej-karpathy'], expertise: 'machine learning' }, gpu: { legends: ['jensen-huang'], expertise: 'GPUs' }, software: { legends: ['bill-gates', 'satya-nadella', 'marc-andreessen'], expertise: 'software' }, hardware: { legends: ['steve-jobs', 'jensen-huang', 'elon-musk'], expertise: 'hardware' }, // Leadership & Management lead: { legends: ['satya-nadella', 'jeff-bezos', 'reed-hastings'], expertise: 'leadership' }, manage: { legends: ['andy-grove', 'ben-horowitz', 'reed-hastings'], expertise: 'management' }, culture: { legends: ['reed-hastings', 'brian-chesky', 'tobi-lutke'], expertise: 'company culture' }, team: { legends: ['ben-horowitz', 'patrick-lencioni', 'reed-hastings'], expertise: 'team building' }, hire: { legends: ['paul-graham', 'ben-horowitz', 'reid-hoffman'], expertise: 'hiring' }, // Marketing & Growth market: { legends: ['seth-godin', 'gary-vaynerchuk'], expertise: 'marketing' }, brand: { legends: ['gary-vaynerchuk', 'seth-godin', 'steve-jobs'], expertise: 'branding' }, social: { legends: ['gary-vaynerchuk', 'jack-dorsey'], expertise: 'social media' }, content: { legends: ['gary-vaynerchuk', 'seth-godin'], expertise: 'content marketing' }, // Personal Development productiv: { legends: ['tim-ferriss', 'naval-ravikant'], expertise: 'productivity' }, wealth: { legends: ['naval-ravikant', 'warren-buffett', 'charlie-munger'], expertise: 'wealth building' }, success: { legends: ['naval-ravikant', 'tim-ferriss'], expertise: 'success principles' }, happiness: { legends: ['naval-ravikant', 'tim-ferriss'], expertise: 'happiness' }, philosophy: { legends: ['naval-ravikant', 'charlie-munger', 'ray-dalio'], expertise: 'philosophy' }, decision: { legends: ['charlie-munger', 'ray-dalio', 'jeff-bezos'], expertise: 'decision making' }, mental: { legends: ['charlie-munger', 'naval-ravikant'], expertise: 'mental models' }, }; /** * Find matching legends based on question content */ function findMatches(question, maxMatches) { const q = question.toLowerCase(); const matchScores = new Map(); // Score legends based on keyword matches for (const [keyword, data] of Object.entries(EXPERTISE_KEYWORDS)) { if (q.includes(keyword)) { for (const legendId of data.legends) { const current = matchScores.get(legendId) || { score: 0, reasons: [], expertise: [] }; current.score += 1; if (!current.reasons.includes(data.expertise)) { current.reasons.push(data.expertise); } current.expertise.push(data.expertise); matchScores.set(legendId, current); } } } // If no keyword matches, use default diverse panel if (matchScores.size === 0) { return [ { legendId: 'naval-ravikant', reason: 'general wisdom and mental models', matchedExpertise: ['general wisdom'] }, { legendId: 'paul-graham', reason: 'startup and business insights', matchedExpertise: ['startups'] }, { legendId: 'charlie-munger', reason: 'decision making and thinking', matchedExpertise: ['mental models'] }, ].slice(0, maxMatches); } // Sort by score and return top matches const sorted = Array.from(matchScores.entries()) .sort((a, b) => b[1].score - a[1].score) .slice(0, maxMatches); return sorted.map(([legendId, data]) => ({ legendId, reason: data.reasons.join(', '), matchedExpertise: [...new Set(data.expertise)], })); } /** * Extract a key insight from a legend's principles */ function extractKeyInsight(legend) { // Try to get a relevant principle or pattern if (legend.principles?.length) { return safeString(legend.principles[0], ''); } if (legend.patterns?.length) { const pattern = legend.patterns[0]; if (typeof pattern === 'object' && pattern.name) { return `${pattern.name}: ${safeString(pattern.description || '', '')}`; } } if (legend.anti_patterns?.length) { const ap = legend.anti_patterns[0]; const apText = typeof ap === 'object' ? ap.pattern : String(ap); return `Avoids: ${safeString(apText, '')}`; } return `${legend.name}'s perspective on ${(legend.owns || ['business']).slice(0, 2).join(' and ')}`; } /** * Auto-match legends to a question */ export function autoMatch(input) { const { sanitized: question } = sanitizeContext(input.question); const maxMatches = Math.min(input.max_matches || 2, 3); const includePrompts = input.include_prompts || false; // Find matching legends const matches = findMatches(question, maxMatches); // Build response const matchedLegends = matches.map(match => { const legend = getLegendById(match.legendId); if (!legend) return null; const result = { legend_id: legend.id, name: legend.name, relevance_reason: match.reason, expertise_match: match.matchedExpertise, key_insight: extractKeyInsight(legend), }; if (includePrompts) { result.system_prompt = buildLegendSystemPrompt(legend); } return result; }).filter((m) => m !== null); if (matchedLegends.length === 0) { throw new Error('No matching legends found. Try rephrasing your question.'); } // Generate suggested approach const legendNames = matchedLegends.map(m => m.name); const suggestedApproach = generateApproach(question, matchedLegends); return { question: escapeBackticks(question), matches: matchedLegends, suggested_approach: suggestedApproach, }; } /** * Generate a suggested approach based on matched legends */ function generateApproach(question, matches) { if (matches.length === 1) { return `Consider ${matches[0].name}'s perspective on ${matches[0].expertise_match.join(', ')}. Their insight: "${matches[0].key_insight}"`; } const names = matches.map(m => m.name).join(' and '); const expertise = [...new Set(matches.flatMap(m => m.expertise_match))].join(', '); return `Combine perspectives from ${names} (expertise: ${expertise}). Each brings unique frameworks - use \`summon_legend\` or \`party_mode\` to get their full responses.`; } /** * Format auto-match response for display */ export function formatAutoMatch(response) { const lines = [ '# Auto-Matched Legends', '', `**Your Question:** ${response.question}`, '', '---', '', '## Best Matches', '', ]; response.matches.forEach((match, i) => { lines.push(`### ${i + 1}. ${match.name}`); lines.push(`- **Why matched:** ${match.relevance_reason}`); lines.push(`- **Expertise:** ${match.expertise_match.join(', ')}`); lines.push(`- **Key insight:** "${escapeBackticks(match.key_insight)}"`); if (match.system_prompt) { lines.push(''); lines.push('<details>'); lines.push('<summary>Full System Prompt</summary>'); lines.push(''); lines.push('```'); lines.push(escapeBackticks(match.system_prompt)); lines.push('```'); lines.push('</details>'); } lines.push(''); }); lines.push('---'); lines.push(''); lines.push('## Suggested Approach'); lines.push(''); lines.push(response.suggested_approach); lines.push(''); lines.push('---'); lines.push(''); lines.push('**Next Steps:**'); lines.push('- Use `summon_legend` to get advice from a specific legend'); lines.push('- Use `party_mode` to have all matched legends discuss together'); lines.push(''); lines.push('*DISCLAIMER: AI personas for educational purposes. Not affiliated with real individuals.*'); return lines.join('\n'); } // MCP Tool Definition export const autoMatchTool = { name: 'auto_match', description: `Automatically find the most relevant legends for your question. **How it works:** 1. Analyzes your question for topics and keywords 2. Matches relevant legends based on their expertise 3. Returns matched legends with key insights **Use this when:** - You're not sure which legend to ask - You want to see who has expertise in your topic - You want quick insights before a full conversation **What you get:** - Top 2-3 most relevant legends - Why each was matched - A key insight from each - Suggested next steps **Examples:** - "How do I raise money for my startup?" → Paul Graham, Marc Andreessen - "What's the future of AI?" → Sam Altman, Jensen Huang - "How should I think about risk?" → Ray Dalio, Howard Marks DISCLAIMER: AI personas for educational purposes only.`, inputSchema: { type: 'object', properties: { question: { type: 'string', description: 'Your question or topic to find relevant legends for', }, max_matches: { type: 'number', description: 'Maximum legends to match (default: 2, max: 3)', }, include_prompts: { type: 'boolean', description: 'Include full system prompts for each legend (default: false)', }, }, required: ['question'], }, }; //# sourceMappingURL=auto-match.js.map