Documentation Index Fetch the complete documentation index at: https://rekko.ai/docs/llms.txt
Use this file to discover all available pages before exploring further.
# Install in one command uvx rekko-mcp
What this page covers
What MCP is and why it matters for prediction market research
Installing and configuring rekko-mcp for Claude Code and Cursor
Workflow examples: screening, analysis, arbitrage, portfolio
Available MCP tools (25+)
When to use MCP vs the REST API
What is MCP? The Model Context Protocol (MCP) lets AI coding assistants call external tools during a conversation. Instead of copy-pasting API calls, you describe what you want in natural language and the assistant uses the right API endpoints automatically.
Rekko’s MCP server (rekko-mcp) exposes 25+ tools covering market data, deep analysis, trading signals, arbitrage detection, and portfolio management. Your AI assistant calls these tools behind the scenes while you focus on the research question.
Installation Requirements Claude Code Plugin install (recommended)
Manual .mcp.json
claude plugin install rekko
Cursor Create or edit .cursor/mcp.json in your project root:
{ "mcpServers" : { "rekko" : { "command" : "uvx" , "args" : [ "rekko-mcp" ], "env" : { "REKKO_API_KEY" : "rk_free_your_key_here" } } } }
Verify installation Ask your assistant: “List the top 5 prediction markets by volume.” If rekko-mcp is configured correctly, it will call the list_markets tool and return formatted results.
Workflow examples 1. Market screening You say: “Find Kalshi markets with high volume that might have mispriced odds.”What happens behind the scenes:
Assistant calls list_markets(source="kalshi", limit=20) to fetch active markets
Calls screen_markets(...) to score them by volume, movement, and category
Presents the top candidates with scores and recommended actions
Example output: Top Kalshi markets by opportunity score: 1. KXFED-26APR30 — "Fed rate decision April 2026" Score: 82 | Volume: $1.2M | Action: analyze 2. KXBITCOIN-26APR — "Bitcoin above $150K by April?" Score: 74 | Volume: $890K | Action: analyze 3. KXINFLATION-26MAY — "CPI above 2.5% in May?" Score: 68 | Volume: $540K | Action: watch
2. Deep analysis You say: “Analyze the Fed rate decision market on Kalshi. I want to understand the key factors driving the price.”What happens:
Calls analyze_market(bet_text="Fed rate decision April 2026", platform="kalshi")
Returns an analysis_id — the research pipeline takes 30-90 seconds
Polls check_analysis_status(analysis_id) until complete
Retrieves the full analysis with probability, confidence, edge, key factors, and risks
Example output: Analysis complete for KXFED-26APR30: Probability: 71% (market: 62%) — Edge: +9 points Confidence: 82% | Risk: low Recommendation: BUY YES Key factors: - PCE inflation at 2.1% — within Fed's comfort zone - Three FOMC members signaled openness to cuts - Jobless claims trending upward (225K → 238K) Risks: - Strong employment report could reverse dovish signals - Tariff escalation could reignite inflation expectations Sources analyzed: 14
3. Arbitrage hunting You say: “Are there any arbitrage opportunities between Kalshi and Polymarket right now?”What happens:
Calls get_arbitrage(min_spread=0.02) for cached results (instant)
If you ask for fresh data, calls get_arbitrage_live(min_spread=0.02) (10-30 seconds)
Returns matched events with spreads, scores, and which platform is cheaper
4. Portfolio management You say: “Show my shadow portfolio and suggest what to do next.”What happens:
Calls get_portfolio(mode="shadow") to list open positions
Calls get_performance(mode="shadow") for aggregate stats
May call check_resolutions() to settle any resolved markets
Presents positions, P&L, win rate, and suggestions
5. Trading signals You say: “Should I buy the Bitcoin 150 K m a r k e t ? I h a v e a 150K market? I have a 150 K ma r k e t ? I ha v e a What happens:
Calls get_portfolio_strategy(...) with your current positions and bankroll
Returns a portfolio-aware signal accounting for correlation between positions
Includes Kelly-optimal size, hedge recommendations, and concentration warnings
6. Market data refresh You say: “Refresh the Kalshi market data.”What happens:
Calls run_scraper(platform="kalshi") to pull the latest markets
Fresh data is available for subsequent queries
Market intelligence Tool Description list_marketsBrowse active markets, filter by platform get_marketGet a single market with pricing data search_marketsSearch markets by text query get_market_historyPrice and volume history (48h, 7d, 30d) get_resolutionResolution timing and mechanism get_execution_guidanceOptimal trade execution analysis
Screening and discovery Tool Description screen_marketsBatch score markets with volume and movement filters get_calibrationSignal accuracy metrics (free, no auth)
Deep research Tool Description analyze_marketTrigger a deep AI analysis pipeline (async) check_analysis_statusPoll analysis progress get_analysisRetrieve completed analysis list_analysesBrowse recent analyses
Strategy and portfolio Tool Description get_strategyTrading signal with Kelly sizing (blocks 30-90s) get_portfolio_strategyPortfolio-aware signal with correlation get_consensusAggregated agent consensus probability
Arbitrage Tool Description get_arbitrageCached cross-platform opportunities get_arbitrage_liveFresh scan (10-30 seconds)
Correlation Tool Description get_correlationCross-market correlation analysis
Trading Tool Description place_shadow_tradePaper trade for tracking report_tradeReport a trade for consensus aggregation get_portfolioCurrent positions and P&L get_performanceWin rate, ROI, and edge metrics check_resolutionsSettle resolved markets
Data refresh Tool Description run_scraperRefresh market data from a platform
Webhooks Tool Description create_webhookRegister event webhook list_webhooksList your webhooks delete_webhookRemove a webhook
MCP vs REST API Scenario Use MCP Use REST API Interactive research in your IDE Yes Automated trading bot Yes Quick market check during coding Yes Production pipeline Yes Portfolio review Yes Webhook/streaming integration Yes One-off analysis during development Yes Scheduled batch processing Yes
MCP is ideal for exploratory research and ad-hoc queries. The REST API is better for automated systems that run without human interaction.
Tips for effective MCP usage Be specific about platforms. “Show me Kalshi markets” is faster than “show me markets” because the tool skips Polymarket data.Request expansions explicitly. “Analyze this market and show me the causal factors” triggers the ?expand=causal parameter automatically.Chain analyses. “Analyze the top 3 markets from that screening” works — the assistant remembers prior results and makes sequential tool calls.Use shadow trading. “Place a shadow trade on the Fed market, $500 on YES” lets you track performance without risking real money.What’s next
MCP tools reference Full parameter documentation for all 25+ tools.
Build a trading bot When you are ready to automate, use the REST API.
REST API quickstart Get an API key and make your first call in 5 minutes.
