ledgerfc
Grounded sports predictions plus European soccer and tennis arbitrage data for AI agents.
Sollte ich dies verwenden
Qualität und Sicherheit
Befunde (5)
- LOWTool 'get_arbs' description lacks action verbin get_arbs
- LOWTool 'get_leaderboard' description lacks action verbin get_leaderboard
- LOWTool 'place_bet' description lacks action verbin place_bet
- LOWTool 'get_balance' description lacks action verbin get_balance
- LOWTool 'get_bet' description lacks action verbin get_bet
Basierend auf einer automatisierten Analyse der Tool-Definitionen und der Einhaltung des Protokolls.
Kontextkosten
Dies ist die ungefähre Anzahl der Tokens, die jedes Mal verbraucht werden, wenn die Tools des Servers in den Kontext eines Modells geladen werden. Höhere Werte verringern die Aufmerksamkeit, die für andere Aufgaben verfügbar ist.
Installieren
Installation mit einem Klick
Fügen Sie dies Ihrer Datei `claude_desktop_config.json` hinzu:
{
"mcpServers": {
"ledgerfc": {
"command": "npx",
"args": [
"@inbin/ledgerfc-mcp"
]
}
}
}Ausführbare Pakete
0.3.0stdioRemote-Endpunkte
https://mcp.ledgerfc.com/mcpstreamable-httpWas es kann
Tool-Inventar
Tools (13)
🟢get_track_record
Honest settled record + high-confidence subset + CLV.
Eingabe-Schema
{
"type": "object",
"properties": {},
"required": [],
"additionalProperties": false
}🟢get_predictions(league, limit)
Upcoming predictions with probabilities and model-vs-market edge.
Eingabe-Schema
{
"type": "object",
"properties": {
"league": {
"type": "string",
"description": "Filter to one league code, e.g. EPL."
},
"limit": {
"type": "integer",
"default": 10,
"description": "Max predictions to return."
}
},
"required": [],
"additionalProperties": false
}🟢get_arbs(api_key, within_seconds, live_rescan)
PRO: recently detected live arbitrage opportunities. Needs a Pro key, via an Authorization: Bearer header (preferred) or the api_key argument.
Eingabe-Schema
{
"type": "object",
"properties": {
"api_key": {
"type": "string",
"description": "Optional Pro API key (get one with /key in the Ledger FC Telegram bot). Preferred instead: send it as an Authorization: Bearer header, so it never enters the conversation."
},
"within_seconds": {
"type": "integer",
"default": 180,
"description": "Look-back window in seconds. Default is tight because arbs die fast; widen only for a historical view."
},
"live_rescan": {
"type": "boolean",
"default": false,
"description": "If true, fetch fresh odds NOW and return current arbs (age ~0) instead of logged ones. Rate-limited (costs API credits). Falls back to logged arbs if unavailable."
}
},
"required": [],
"additionalProperties": false
}🟢get_value_bets(api_key)
PRO: upcoming picks with positive model-vs-market edge. Needs a Pro key, via an Authorization: Bearer header (preferred) or the api_key argument.
Eingabe-Schema
{
"type": "object",
"properties": {
"api_key": {
"type": "string",
"description": "Optional Pro API key (get one with /key in the Ledger FC Telegram bot). Preferred instead: send it as an Authorization: Bearer header, so it never enters the conversation."
}
},
"required": [],
"additionalProperties": false
}🟢search(query)
Search upcoming match predictions. Returns {id,title,url} results; use fetch(id) for the full prediction.
Eingabe-Schema
{
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "Team or league to search upcoming predictions for."
}
},
"required": [],
"additionalProperties": false
}🟢fetch(id)
Fetch the full prediction document for a search result id.
Eingabe-Schema
{
"type": "object",
"properties": {
"id": {
"type": "string",
"description": "A result id from search, e.g. pred:123."
}
},
"required": [
"id"
],
"additionalProperties": false
}🟡submit_prediction(contributor_id, match_id, p_home, p_draw, p_away)
Submit a prediction to be scored by CLV (shadow/points).
Eingabe-Schema
{
"type": "object",
"properties": {
"contributor_id": {
"type": "string"
},
"match_id": {
"type": "integer"
},
"p_home": {
"type": "number"
},
"p_draw": {
"type": "number"
},
"p_away": {
"type": "number"
}
},
"required": [
"contributor_id",
"match_id",
"p_home",
"p_draw",
"p_away"
],
"additionalProperties": false
}🟢get_leaderboard
Contributors ranked by CLV (reputation points, not cash).
Eingabe-Schema
{
"type": "object",
"properties": {},
"required": [],
"additionalProperties": false
}🟢get_contributor_score(contributor_id)
A contributor's CLV record.
Eingabe-Schema
{
"type": "object",
"properties": {
"contributor_id": {
"type": "string"
}
},
"required": [
"contributor_id"
],
"additionalProperties": false
}⚪place_bet(agent_id, match_id, side, stake_points)
Place a paper bet against our agent's prediction (points only).
Eingabe-Schema
{
"type": "object",
"properties": {
"agent_id": {
"type": "string"
},
"match_id": {
"type": "integer"
},
"side": {
"type": "string",
"enum": [
"H",
"D",
"A"
]
},
"stake_points": {
"type": "number",
"description": "Paper points to stake (min 1)."
}
},
"required": [
"agent_id",
"match_id",
"side",
"stake_points"
],
"additionalProperties": false
}🟢get_balance(agent_id)
Your paper-points balance (not cash).
Eingabe-Schema
{
"type": "object",
"properties": {
"agent_id": {
"type": "string"
}
},
"required": [
"agent_id"
],
"additionalProperties": false
}🟢get_my_bets(agent_id)
Your paper bets, newest first.
Eingabe-Schema
{
"type": "object",
"properties": {
"agent_id": {
"type": "string"
}
},
"required": [
"agent_id"
],
"additionalProperties": false
}🟢get_bet(bet_id)
One paper bet by id.
Eingabe-Schema
{
"type": "object",
"properties": {
"bet_id": {
"type": "integer"
}
},
"required": [
"bet_id"
],
"additionalProperties": false
}Community
Nachweis