Fan Token Intel

Last 30 days

Uptime

100%

Response time

218 ms typical, 218 ms slowest 5%

Last check

1 h ago

Next check

in 5 h

How to call it

Add it to any MCP client that supports remote servers.

{
  "mcpServers": {
    "fan-token-intel": {
      "type": "http",
      "url": "https://mcp-production-f681.up.railway.app/mcp"
    }
  }
}

25 tools

• tokenintel_discover

  Discover available tools on the Fan Token Intel MCP server. Returns tool names and one-line descriptions, organized by category. Call with no arguments for all categories, or specify a category to filter. Categories: market_data, signals, sports, social, defi, agent, portfolio, v

• tokenintel_describe

  Get the full input schema for a specific tool. Returns the JSON Schema (parameters, types, required fields, descriptions) needed to call the tool via tokenintel_invoke. Use tokenintel_discover first to find tool names.

• tokenintel_invoke

  Invoke any tool on the Fan Token Intel MCP server by name. Pass the tool_name and its arguments. The result is identical to calling the tool directly. Auth and rate limits apply as normal. Use tokenintel_describe to get the required arguments first.

• tokenintel_register

  Get a free Fan Token Intel API key, self-serve — no human in the loop. Provide a name, an email, and terms_accepted=true; the key (ti_live_...) comes back in the response along with your tier and rate limits. Free-tier keys unlock the read-only descriptive data layer (60 req/min)

• tokenintel_briefing

  All-in-one ECOSYSTEM briefing: market regime, active signals, anomalies, health matrix, sports calendar, and whale activity in one response. Use instead of calling 6+ tools sequentially. USE THIS for a market-wide overview. USE tokenintel_token_context for a SINGLE-TOKEN deep div

• tokenintel_health_matrix

  Get health grades (A-F) for all tracked fan tokens. Each token is scored across trading volume, order-book liquidity, spread, holder distribution and price stability -- 5-pillar weighted: volume(25%) + liquidity(25%) + spread(20%) + holders(15%) + price_stability(15%). The grade

• tokenintel_market_regime

  Get current market conditions — BTC trend, CHZ momentum, fear/greed index, and the platform's market regime classification. Useful for filtering or adjusting signal confidence based on macro conditions.

• tokenintel_macro_context

  Get current crypto macro context: BTC dominance, CHZ price, funding rates, fear & greed index, and risk environment assessment.

• tokenintel_token_context

  SINGLE-TOKEN deep dive: realtime price, CEX whale flow, on-chain Chiliz Chain (FanX) liquidity with slippage at 1%/5% of reserves, and upcoming matches for one symbol. The default tool to call before evaluating a trading decision on a specific token. USE THIS when you have a targ

• tokenintel_realtime_prices

  Get the freshest available prices with staleness metadata. Returns price_age_seconds so agents know exactly how stale each price is. Lightweight and fast -- call this before any trade decision to get current prices. Supports multiple tokens in a single call.

• tokenintel_price_candles

  Historical OHLCV price candles for any fan token. Intervals: 1h, 4h, 1d. Up to 180 days lookback. Returns open, high, low, close, volume for each period. Use for backtesting, charting, trend analysis, or building your own signals.

• tokenintel_whale_flows

  Get real-time whale distribution data for a fan token. Shows the ratio of whale sells to total whale activity on CEX exchanges. sell_ratio = whale sell volume / total whale volume; the payload labels >0.65 'distribution' and <0.35 'accumulation' (descriptive labels, not a signal)

• tokenintel_social_sentiment

  Social sentiment for a fan token. The only live social source is the LunarCrush aggregated feed, and on the current plan it provides galaxy_score and alt_rank ONLY — sentiment and social_volume come back null (see lunarcrush.fields_unavailable); they are unavailable, not zero. Na

• tokenintel_capital_rotation

  Cross-token capital flow analysis. Shows which fan tokens are gaining vs losing volume relative to their recent average. Detects rotation: when whales exit one token, where does the capital go?

• tokenintel_match_impact_history

  Historical match price impact data for a fan token. Returns price snapshots at -24h, kickoff, fulltime, +1h, +24h with returns for each match. Filter by result (win/loss/draw), competition, venue. WINDOWS: return_total_pct is measured price_24h_before -> price_24h_after (it inclu

• tokenintel_match_correlation

  Historical match-to-price correlation. Ask 'what happens to BAR after Champions League wins?' and get backtested data with price impact percentages. Returns individual match records with price at kickoff, fulltime, +1h, +24h and aggregate stats (avg impact, win rate, best/worst).

• tokenintel_goal_direction_asymmetry

  THE event-impact moat: how a fan token reacts when its team SCORES vs CONCEDES a goal, market-adjusted vs CHZ at +15/+30/+60m. The blended 'all goals' number hides the real signal — scoring is ~priced-in, conceding moves price. Returns the scored-vs-conceded decomposition with sa

• tokenintel_event_reaction_profile

  Event-conditioned, market-adjusted (vs CHZ) token reaction profiles for football events — by event_type x event_side(for/against) x minute x scoreline_state x importance. Returns mean/median abnormal return, match-clustered t-stat, bootstrap 95% CI, hit rate, decay/persistence, n

• tokenintel_late_game_redcard_profile

  Red-card reaction profile (market-adjusted vs CHZ). Rare and high-impact: returns abnormal return at +15/+30/+60m with honest wide confidence intervals and sample size; flags cells with n<15. Descriptive history, not advice.

• tokenintel_match_event_replay

  Event-by-event reaction tape for a single match: each goal/red card with its minute, running score, scoreline state, and the market-adjusted token reaction at +15/+30/+60m (plus pre-event drift). The non-reconstructable moat artifact. match_id selects that fixture; token (+ optio

• tokenintel_match_odds

  Prediction-market odds curve for a single match from the in-play odds tape (odds_ticks): per-market (home/draw/away) implied-probability series with source labels (polymarket = CLOB midpoint, apifootball = de-vigged bookmaker odds), pre-match vs in-play segmentation against kicko

• tokenintel_odds_coverage

  Discover which matches have prediction-market odds coverage in the in-play odds tape (odds_ticks): per-match tick counts by source (polymarket = CLOB midpoint, apifootball = de-vigged bookmaker odds), in-play tick counts vs kickoff, capture span, live dataset totals (computed fro

• tokenintel_governance_validators

  List active validators on Chiliz Chain governance. Shows validator addresses and total CHZ delegated to each. Use this to find the best validator before staking.

• tokenintel_dex_depth

  Get DEX depth and slippage curves for fan token pools on Chiliz Chain. Computes constant-product (x*y=k) price impact at trade sizes [1%, 5%, 10%, 25%] of pool reserves. Useful for agents evaluating execution costs before trading. Data from latest on-chain liquidity snapshots.

• tokenintel_dex_liquidity

  Get on-chain DEX liquidity data for fan tokens on Chiliz Chain. Returns pool TVL, depth, token reserves, and estimated slippage. Critical for agents that want to understand execution costs before trading on-chain.

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