prediction_markets_search
Search live prediction markets across Polymarket and Kalshi in one call. Returns a single normalised shape for both venues — question, implied probability (0-1), volume, end date, venue and URL — so you never have to reconcile two different price formats. Raw venue fields are preserved.
This record as markdown: /tools/io-github-getgapup-gapup-mcp/prediction-markets-search.md
What prediction_markets_search does on Gapup Mcp
AI agents call prediction_markets_search to retrieve information from Gapup Mcp without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
async | boolean | — | If true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client ti |
limit | integer | — | Maximum markets to return (default 20) |
query | string | — | Free-text filter on the market question. Omit to get the most active markets. |
venues | array | — | Which venues to query (default both) |
includeRaw | boolean | — | Include each venue's original fields (default false) |
includeClosed | boolean | — | Include settled markets (default false) |
Parameters from the server's own tool schema.
Why prediction_markets_search is rated Low
Tool queries and retrieves public prediction market data without modifying, executing, or risking financial exposure.
From the tool's definition Search live prediction markets. Returns question, implied probability, volume, end date, venue and URL.
Attacks that exploit this kind of access
The rule that runs prediction_markets_search safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Gapup Mcp, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For prediction_markets_search, this is the rule to start with:
prediction_markets_search is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Gapup Mcp, apply this rule, and every prediction_markets_search call is checked against it from then on.
Questions about prediction_markets_search
Search live prediction markets across Polymarket and Kalshi in one call. Returns a single normalised shape for both venues — question, implied probability (0-1), volume, end date, venue and URL — so you never have to reconcile two different price formats. Raw venue fields are preserved. It is categorised as a Read tool in the Gapup Mcp MCP Server, which means it retrieves data without modifying state.
prediction_markets_search accepts 6 parameters: async, limit, query, venues, includeRaw, includeClosed. The full parameter table on this page comes from the server's own tool schema.
Register the Gapup MCP server in PolicyLayer and add a rule for prediction_markets_search: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Gapup Mcp. Nothing to install.
prediction_markets_search is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the prediction_markets_search rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for prediction_markets_search. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
prediction_markets_search is provided by the Gapup MCP server (https://mcp.gapup.io/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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