Fan Token Intel
REMOTE · MCP-PRODUCTION-F681.UP.RAILWAY.APP · SCANNED SEP 24
Fan-token intelligence for Chiliz Chain: prices, whale flows, match event impact. 22 read tools.
Available components
How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. How we score → Why this is hard to score →
Endpoint Security57
- The endpoint's TLS certificate is valid, in date, and uses a strong key. View diagnostics → Pass
- Authorisation not fully verified: no authorisation is required to call this server, and 25 tool(s) never declared a destructiveHint. The MCP spec treats an absent hint as destructive by default, so we cannot call this surface safe. See how to fix → View diagnostics → Unverified
- HTTPS is enforced; there's no plaintext access path. View diagnostics → Pass
- HSTS check failed: the Strict-Transport-Security header is absent. See how to fix → View diagnostics → Fail
- DNSSEC check failed: this domain isn't protected by DNSSEC. See how to fix → View diagnostics → Fail
Transport & Reachability100
- Verified streamable-http transport via a live MCP handshake. View diagnostics → Pass
Schema Quality & AI Usability82
- 100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).Pass
- AI-judged instruction clarity (excellent).Pass
- Context-footprint check failed: tool/resource definitions use about 4148 tokens (~143/item across 29 items; 25 tools + 4 resources), over budget; trim descriptions and params. See how to fix → Fail
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management100
- No destabilizing schema changes in the last 30 days.Pass
Tool Coverage99
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 98% of tool parameters carry a description.Partial
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 25 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 27 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
How do I install the Fan Token Intel MCP server?
Fan Token Intel is a hosted endpoint at https://mcp-production-f681.up.railway.app/mcp, so there is nothing to install locally. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
remote · mcp-production-f681.up.railway.app
claude mcp add --transport http brunopessoa22-fan-token-intel 'https://mcp-production-f681.up.railway.app/mcp'
{
"mcpServers": {
"brunopessoa22-fan-token-intel": {
"url": "https://mcp-production-f681.up.railway.app/mcp"
}
}
} {
"servers": {
"brunopessoa22-fan-token-intel": {
"type": "http",
"url": "https://mcp-production-f681.up.railway.app/mcp"
}
}
} [mcp_servers.brunopessoa22-fan-token-intel] url = "https://mcp-production-f681.up.railway.app/mcp"
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"brunopessoa22-fan-token-intel": {
"type": "remote",
"url": "https://mcp-production-f681.up.railway.app/mcp",
"enabled": true
}
}
} openclaw mcp add brunopessoa22-fan-token-intel --url 'https://mcp-production-f681.up.railway.app/mcp' --transport streamable-http
mcp_servers:
brunopessoa22-fan-token-intel:
url: "https://mcp-production-f681.up.railway.app/mcp" {
"McpServers": {
"brunopessoa22-fan-token-intel": {
"Transport": "http",
"Url": "https://mcp-production-f681.up.railway.app/mcp"
}
}
} assistant mcp add brunopessoa22-fan-token-intel -t streamable-http -u 'https://mcp-production-f681.up.railway.app/mcp'
{
"mcpServers": {
"brunopessoa22-fan-token-intel": {
"type": "http",
"url": "https://mcp-production-f681.up.railway.app/mcp"
}
}
} The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.
Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 9 Sept 26 −1
No change was recorded against any check on this day. Schema Quality & AI Usability went from 83 to 82.
- 2 Sept 26 0
- The server rewrote its instructions, which are the text every model session reads security
- Tool “tokenintel_health_matrix” rewrote its description, which is the text the model reads security
- Tool “tokenintel_whale_flows” rewrote its description, which is the text the model reads security
- Schema quality: 127 → 143 ▼ functional
- “tokenintel_capital_rotation” added an optional parameter “limit” cosmetic
- “tokenintel_capital_rotation” added an optional parameter “min_volume_usd” cosmetic
- “tokenintel_dex_liquidity” added an optional parameter “limit” cosmetic
- 26 Aug 26 80
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
- 25 Aug 26 0
- Stability: 0.97 → pass security
- 11 Aug 26 0
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
- 7 Aug 26 0
- The server no longer declares the “experimental” capability functional
- 1 Aug 26 0
- Tool “tokenintel_health_matrix” rewrote its description, which is the text the model reads security
- 31 Jul 26 0
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 24 Sept 2026 · Probed https://mcp-production-f681.up.railway.app/mcp
TLS valid
Negotiated TLS 1.3 with TLS_AES_128_GCM_SHA256 .
| Subject | Issuer | Valid from | Valid until | Key | Signature | Serial |
|---|---|---|---|---|---|---|
| CN=*.up.railway.app | CN=YE1,O=Let's Encrypt,C=US | 29 Jul 2026 | 27 Oct 2026 | ECDSA 256 | ECDSA-SHA384 | 6da79bb561da3efeb0e751ca21abd3999fe |
| SANs: *.up.railway.app, up.railway.app | ||||||
| CN=YE1,O=Let's Encrypt,C=US (CA) | CN=Root YE,O=ISRG,C=US | 3 Sept 2025 | 2 Sept 2028 | ECDSA 384 | ECDSA-SHA384 | 5ddd70dd31f801c85c186a7a04b80afe |
| CN=Root YE,O=ISRG,C=US (CA) | CN=ISRG Root X2,O=Internet Security Research Group,C=US | 13 May 2026 | 2 Sept 2032 | ECDSA 384 | ECDSA-SHA384 | 872165fc34b6e5fba8add5b3705fb53a |
| CN=ISRG Root X2,O=Internet Security Research Group,C=US (CA) | CN=ISRG Root X1,O=Internet Security Research Group,C=US | 13 May 2026 | 2 Sept 2032 | ECDSA 384 | SHA256-RSA | 6c8f1dc727c7117f7baf853ac980f9cd |
Background: What to check on a remote MCP endpoint →
DNSSEC insecure
Validation of mcp-production-f681.up.railway.app. — Not signed
| Zone | DS | Keys | Algorithms | Outcome |
|---|---|---|---|---|
| . | trust_anchor | 20326, 38696 | 8, 8 | Verified |
| app. | present | 23684 | 8 | Verified |
| railway.app. | absent | Unsigned (proven) parent-signed NSEC/NSEC3 proves an unsigned delegation |
Authentication No authorisation required
The endpoint answered without asking for a token. Anyone who knows the URL can reach it.
| Result | No authorisation required |
|---|---|
| HTTP status | 200 |
Background: How OAuth 2.1 works in the 2026 MCP spec →
Transports 2 probes
| Transport | URL | Outcome | Status | Location |
|---|---|---|---|---|
| streamable-http | https://mcp-production-f681.up.railway.app/mcp | Verified | 200 | |
| http (plaintext) | http://mcp-production-f681.up.railway.app/mcp | HTTPS enforced | 301 | https://mcp-production-f681.up.railway.app/mcp |
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
tokenintel_briefing ~157
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 dive (price, signals, health, whale flow, sports catalyst, news — all for one symbol). Returns data, not recommendations -- interpret results yourself.
| Name | Type | Req | Description |
|---|---|---|---|
| focus | string | – | Optional token symbol to focus on (e.g., 'BAR'). Omit for full ecosystem view. |
| timeframe | string | – | Briefing depth: 'morning' (24h window, default) or 'weekly' (7-day trends). |
No output schema declared.
No examples provided.
tokenintel_capital_rotation ~144
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?
| Name | Type | Req | Description |
|---|---|---|---|
| hours | integer | – | Compare last N hours vs prior period. Default: 24. |
| limit | integer | – | Rows returned: the strongest movers by |relative_change_pct| (inflows and outflows both kept). Default 20; counts always cover the whole universe. |
| min_volume_usd | number | – | Hide dust: tokens whose current AND prior rolling-24h volume are both below this. Default $1,000; pass 0 for everything. |
No output schema declared.
No examples provided.
tokenintel_describe ~80
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.
| Name | Type | Req | Description |
|---|---|---|---|
| tool_name | string | yes | The tool name to describe (e.g. 'tokenintel_whale_flows'). |
No output schema declared.
No examples provided.
tokenintel_dex_depth ~99
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.
| Name | Type | Req | Description |
|---|---|---|---|
| token | string | – | Token symbol (optional). If omitted, returns all CHZ pairs sorted by TVL. |
No output schema declared.
No examples provided.
tokenintel_dex_liquidity ~109
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.
| Name | Type | Req | Description |
|---|---|---|---|
| limit | integer | – | Max pools when no token is given (sorted by TVL). Default 25; pools_total reports the full count. |
| token | string | – | Token symbol (optional). If omitted, returns all pools sorted by TVL. |
No output schema declared.
No examples provided.
tokenintel_discover ~106
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, volume, chain_info. Tip: connect with ?modules=market_data,signals to load only specific categories.
| Name | Type | Req | Description |
|---|---|---|---|
| category | string | – | Filter to a specific category (optional). Omit for all. |
No output schema declared.
No examples provided.
tokenintel_event_reaction_profile ~220
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_events, n_matches, FDR. Omit a dimension to pool. Every cell carries its sample size — descriptive history, not advice.
| Name | Type | Req | Description |
|---|---|---|---|
| clean_only | boolean | – | Only non-overlapping events (conservative). Default true. |
| event_side | string | – | 'for' = token's team scored / opponent sent off; 'against' = conceded / own red card. |
| event_type | string | – | Event type. |
| horizon_min | integer | – | Reaction horizon. Default 30. |
| importance | string | – | Match importance bucket (e.g. high/medium/low). |
| minute_bucket | string | – | – |
| scoreline_state | string | – | Token team's state BEFORE the event. |
No output schema declared.
No examples provided.
tokenintel_goal_direction_asymmetry ~128
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 sample sizes and directional hit rates. Only computable here (needs the token<->team map). Descriptive history, not advice.
| Name | Type | Req | Description |
|---|---|---|---|
| minute_bucket | string | – | Optional: restrict to goals in this match-minute bucket. |
No output schema declared.
No examples provided.
tokenintel_governance_validators ~43
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.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
tokenintel_health_matrix ~261
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 is the token's percentile standing WITHIN the fan-token universe (A=top 10%, B=next 20%, C=middle 40%, D=next 20%, F=bottom 10%); health_score stays the absolute 0-100 pillar score. A pillar whose collector delivered no data is excluded and the remaining weights are renormalized (see missing_pillars), never scored as 0. Use this to quickly filter which tokens deserve attention relative to their peers. Detailed mode (default) includes the per-pillar sub-scores; pass response_format='concise' to get just symbol/grade/score/change (~70% smaller) when you don't need team/league/volume/age detail.
| Name | Type | Req | Description |
|---|---|---|---|
| response_format | string | – | 'detailed' (default) = all fields + legend; 'concise' = symbol/grade/score/change_24h only. |
No output schema declared.
No examples provided.
tokenintel_invoke ~104
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.
| Name | Type | Req | Description |
|---|---|---|---|
| arguments | object | – | Arguments to pass to the tool (matches the tool's inputSchema). |
| tool_name | string | yes | The tool to invoke (e.g. 'tokenintel_whale_flows'). |
No output schema declared.
No examples provided.
tokenintel_late_game_redcard_profile ~114
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.
| Name | Type | Req | Description |
|---|---|---|---|
| event_side | string | – | 'against' = token team's player sent off; 'for' = opponent sent off. |
| minute_bucket | string | – | Optional match-minute bucket (e.g. '76-90' for late reds). |
No output schema declared.
No examples provided.
tokenintel_macro_context ~36
Get current crypto macro context: BTC dominance, CHZ price, funding rates, fear & greed index, and risk environment assessment.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
tokenintel_market_regime ~49
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.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
tokenintel_match_correlation ~147
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).
| Name | Type | Req | Description |
|---|---|---|---|
| competition_filter | string | – | Filter by competition type |
| limit | integer | – | Number of matches to return (default 20, max 100) |
| result_filter | string | – | Filter by match result |
| token | string | yes | Token symbol (e.g., BAR, PSG, JUV) |
| venue_filter | string | – | Filter by home/away |
No output schema declared.
No examples provided.
tokenintel_match_event_replay ~178
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 (+ optional date) resolves ONE fixture (the date-selected or most recent) and returns its tape, match metadata, and an other_matches index. Events are never merged across fixtures.
| Name | Type | Req | Description |
|---|---|---|---|
| date | string | – | Optional YYYY-MM-DD; with token, selects that day's fixture instead of the most recent. |
| match_id | string | – | The matches.match_id (e.g. 'apifb_1391197'). |
| token | string | – | Token symbol — resolves its most recent (or date-selected) measured fixture. |
No output schema declared.
No examples provided.
tokenintel_match_impact_history ~204
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 includes the pregame move, so it can differ in sign from a kickoff-anchored return); return_ko_to_24h_pct is kickoff -> +24h. See the 'semantics' block in the response. Use for backtesting sports-driven strategies.
| Name | Type | Req | Description |
|---|---|---|---|
| days | integer | – | Lookback in days (max 365). Default: 90. |
| limit | integer | – | Max matches (max 200). Default: 100. |
| result | string | – | Filter by match result. Default: all. |
| token | string | yes | Token symbol (e.g., 'BAR'). |
No output schema declared.
No examples provided.
tokenintel_match_odds ~283
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 kickoff, and open/close/min/max summary stats per market. Settlement wind-down artifacts (ticks after a market first prints prob >= 0.99, or after full-time +15min) are excluded by default and counted via excluded_settlement_ticks. Curves are downsampled to <=300 points per market (labeled). match_id selects a fixture directly; token (+ optional date) resolves the most recent covered fixture. Use tokenintel_odds_coverage to discover which matches have odds data.
| Name | Type | Req | Description |
|---|---|---|---|
| date | string | – | Optional YYYY-MM-DD; with token, selects that day's fixture instead of the most recent. |
| include_settlement_ticks | boolean | – | Include post-settlement wind-down ticks in the curves (default false). |
| match_id | string | – | The matches/odds_ticks match_id (e.g. 'apifb_1591866'). Covers fixtures with no fan token too. |
| token | string | – | Fan token symbol — resolves its most recent (or date-selected) fixture with odds coverage. |
No output schema declared.
No examples provided.
tokenintel_odds_coverage ~210
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 from the table, never hardcoded), and upcoming fixtures already mapped for capture. In-play odds are unbackfillable — a match that passed uncaptured stays uncovered. Use tokenintel_match_odds to fetch a covered match's probability curves.
| Name | Type | Req | Description |
|---|---|---|---|
| days_ahead | integer | – | Include upcoming mapped fixtures kicking off within N days (0-90, default 7). 0 disables the upcoming section. |
| days_back | integer | – | Only matches with kickoff within the last N days (1-365). Default: all captured history. |
| token | string | – | Filter to one fan token's fixtures (e.g. PSG). Fixtures with no fan token are excluded when set. |
No output schema declared.
No examples provided.
tokenintel_price_candles ~155
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.
| Name | Type | Req | Description |
|---|---|---|---|
| days | integer | – | Lookback in days (max 180). Default: 30. |
| interval | string | – | Candle interval. Default: 4h. |
| limit | integer | – | Max candles to return (max 500). Default: 200. |
| token | string | yes | Token symbol (e.g., 'BAR', 'PSG', 'CHZ'). |
No output schema declared.
No examples provided.
tokenintel_realtime_prices ~82
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.
| Name | Type | Req | Description |
|---|---|---|---|
| tokens | string | yes | Comma-separated token symbols (e.g., 'BAR,PSG,JUV') |
No output schema declared.
No examples provided.
tokenintel_register ~196
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); premium event-impact tools stay metered via x402. Pass the key as 'Authorization: Bearer ti_live_xxx' (HTTP) or the TOKENINTEL_API_KEY env var (stdio). Rate-limited to one registration per 10 minutes per caller.
| Name | Type | Req | Description |
|---|---|---|---|
| string | yes | Contact email. The key may require clicking the emailed verification link before authenticated calls succeed. | |
| name | string | yes | Agent display name (3-100 chars) |
| terms_accepted | boolean | yes | Must be true to accept the Terms of Use and Privacy Policy (https://fantokenintel.com/legal). |
No output schema declared.
No examples provided.
tokenintel_social_sentiment ~196
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. Native X/Twitter ingestion was retired 2026-03-01 and native Reddit/YouTube ingestion has never run in production, so those blocks read 0 — data_sources labels each pipeline (active / no_recent_data / inactive_since_<date> / never_active). overall_sentiment is computed only from sources that actually reported activity and is null when none did. Descriptive community-mood data, not a recommendation.
| Name | Type | Req | Description |
|---|---|---|---|
| hours | integer | – | Lookback window in hours (default: 24, max: 168) |
| token | string | yes | Token symbol (e.g., ASR, BAR, PSG). Required. |
No output schema declared.
No examples provided.
tokenintel_token_context ~115
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 target token in mind. USE tokenintel_briefing when you want the market-wide overview instead.
| Name | Type | Req | Description |
|---|---|---|---|
| token | string | yes | Token symbol (e.g., ASR, BAR, CHZ) |
No output schema declared.
No examples provided.
tokenintel_whale_flows ~274
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). Data aggregated from CEX exchanges in real-time. USE THIS for aggregate buy/sell pressure on CEX. USE tokenintel_whale_trades for individual trade rows. USE tokenintel_dex_whales for on-chain (Chiliz Chain) swap whales.
| Name | Type | Req | Description |
|---|---|---|---|
| exchange | string | – | Filter by specific exchange (optional). Options: binance, okx, htx, kucoin, bybit, gate, mexc, mercadobitcoin, upbit, coinbase |
| min_trade_usd | number | – | Minimum trade size in USD (default: 1000). The source table ingests fan-token trades from $10 up, most of it retail-sized; pass 0 to include every trade. |
| timeframe_hours | integer | – | Lookback window in hours (default: 4) |
| token | string | yes | Token symbol (e.g., ASR, BAR, CHZ, CITY, ATM, ACM, JUV, PSG) |
No output schema declared.
No examples provided.
What is the Fan Token Intel MCP server?
Fan Token Intel is an MCP server listed in the public MCP registry as io.github.BrunoPessoa22/fan-token-intel. Fan-token intelligence for Chiliz Chain: prices, whale flows, match event impact. 22 read tools. This page covers its hosted endpoint (https://mcp-production-f681.up.railway.app/mcp).
Is the Fan Token Intel MCP server safe to use?
Fan Token Intel scores 79 out of 100 on VerifyMCP. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.
What tools does the Fan Token Intel MCP server expose?
Fan Token Intel exposes 25 tools: tokenintel_discover, tokenintel_describe, tokenintel_invoke, tokenintel_register, tokenintel_briefing, and 20 more. Their descriptions and schemas cost roughly 3,690 tokens of context every time the server is loaded.
Does the Fan Token Intel MCP server require authentication?
No. We connected to Fan Token Intel without credentials and it answered, so anything it exposes is reachable by anyone who knows the address.
Is the Fan Token Intel MCP server still maintained?
Fan Token Intel is still listed as active in the MCP registry. We last reached this channel on 24 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.