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jupiter_prediction_events

List binary prediction events on real-world events from Polymarket or Kalshi. Filter by category, sort by volume or date, and include market data.

Instructions

List Jupiter prediction events — binary markets on real-world events. Filter by category, sort by volume or date, include market data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
providerNoData source (default: polymarket)
includeMarketsNoInclude market data in response
categoryNoFilter: all, crypto, sports, politics, esports, culture, economics, tech
sortByNoSort field
sortDirectionNoSort order
filterNoNamed filter: new (24h), live (active), trending
startNoPagination start index
endNoPagination end index

Implementation Reference

  • Handler function for the jupiter_prediction_events tool. Calls client.predictionEvents(args) and returns the result as JSON.
    async (args) => {
      const result = await client.predictionEvents(args);
      return JSON.stringify(result, null, 2);
    },
  • Zod schema defining input parameters for jupiter_prediction_events: provider (kalshi|polymarket), includeMarkets, category, sortBy, sortDirection, filter, start, end.
    {
      provider: z.enum(["kalshi", "polymarket"]).optional().describe("Data source (default: polymarket)"),
      includeMarkets: z.boolean().optional().describe("Include market data in response"),
      category: z.string().optional().describe("Filter: all, crypto, sports, politics, esports, culture, economics, tech"),
      sortBy: z.enum(["volume", "beginAt"]).optional().describe("Sort field"),
      sortDirection: z.enum(["asc", "desc"]).optional().describe("Sort order"),
      filter: z.enum(["new", "live", "trending"]).optional().describe("Named filter: new (24h), live (active), trending"),
      start: z.number().optional().describe("Pagination start index"),
      end: z.number().optional().describe("Pagination end index"),
    },
  • Registration function registerPredictionTools which calls register() with name 'jupiter_prediction_events', description, schema, and handler.
    export function registerPredictionTools(register: ToolRegistrar, client: JupiterClient) {
      register(
        "jupiter_prediction_events",
        "List Jupiter prediction events — binary markets on real-world events. Filter by category, sort by volume or date, include market data.",
        {
          provider: z.enum(["kalshi", "polymarket"]).optional().describe("Data source (default: polymarket)"),
          includeMarkets: z.boolean().optional().describe("Include market data in response"),
          category: z.string().optional().describe("Filter: all, crypto, sports, politics, esports, culture, economics, tech"),
          sortBy: z.enum(["volume", "beginAt"]).optional().describe("Sort field"),
          sortDirection: z.enum(["asc", "desc"]).optional().describe("Sort order"),
          filter: z.enum(["new", "live", "trending"]).optional().describe("Named filter: new (24h), live (active), trending"),
          start: z.number().optional().describe("Pagination start index"),
          end: z.number().optional().describe("Pagination end index"),
        },
        async (args) => {
          const result = await client.predictionEvents(args);
          return JSON.stringify(result, null, 2);
        },
      );
    }
  • src/index.ts:26-26 (registration)
    Import of registerPredictionTools from ./tools/prediction.js for the MCP server entry point.
    import { registerPredictionTools } from "./tools/prediction.js";
  • src/index.ts:67-67 (registration)
    Invocation of registerPredictionTools with the MCP register function and JupiterClient instance.
    registerPredictionTools(register, client);
  • JupiterClient.predictionEvents() method that makes the HTTP GET request to /prediction/v1/events with optional query parameters.
    async predictionEvents(params?: {
      provider?: "kalshi" | "polymarket";
      includeMarkets?: boolean;
      category?: string;
      sortBy?: "volume" | "beginAt";
      sortDirection?: "asc" | "desc";
      filter?: "new" | "live" | "trending";
      start?: number;
      end?: number;
    }) {
      return this.request("/prediction/v1/events", { params: params as any });
    }
  • ToolRegistrar type definition used by registerPredictionTools and all other tool registration functions.
    export type ToolRegistrar = (
      name: string,
      description: string,
      schema: Record<string, z.ZodType>,
      handler: (args: any) => Promise<string>,
    ) => void;
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must disclose behavioral traits. It only states the tool lists events and can include market data, but omits any mention of read-only behavior, authentication needs, rate limits, or side effects. This is insufficient for a tool with no annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loading the purpose and then listing key capabilities. Every word is justified, with no fluff or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 8 parameters and no output schema, the description is adequate but incomplete. It does not explain pagination behavior, return format, or how filters interact. However, for a simple list tool, it covers the basics.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% coverage with parameter descriptions. The tool description repeats some parameter info (category, sortBy, includeMarkets) but adds no new meaning beyond what is already in the schema. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool lists Jupiter prediction events, which are binary markets on real-world events. This distinguishes it from sibling tools focused on trading, lending, and swaps, making the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for listing prediction events with filters and sorting, and the context of sibling tools makes when to use this tool clear. However, it does not explicitly state when not to use it or alternative tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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