Skip to main content
Glama

Convex MCP server

Official
by get-convex
hydration.tsx1.64 kB
import { useMemo } from "react"; import { useQuery } from "../react/client.js"; import { FunctionReference, makeFunctionReference } from "../server/api.js"; import { jsonToConvex } from "../values/index.js"; /** * The preloaded query payload, which should be passed to a client component * and passed to {@link usePreloadedQuery}. * * @public */ export type Preloaded<Query extends FunctionReference<"query">> = { __type: Query; _name: string; _argsJSON: string; _valueJSON: string; }; /** * Load a reactive query within a React component using a `Preloaded` payload * from a Server Component returned by {@link nextjs.preloadQuery}. * * This React hook contains internal state that will cause a rerender * whenever the query result changes. * * Throws an error if not used under {@link ConvexProvider}. * * @param preloadedQuery - The `Preloaded` query payload from a Server Component. * @returns the result of the query. Initially returns the result fetched * by the Server Component. Subsequently returns the result fetched by the client. * * @public */ export function usePreloadedQuery<Query extends FunctionReference<"query">>( preloadedQuery: Preloaded<Query>, ): Query["_returnType"] { const args = useMemo( () => jsonToConvex(preloadedQuery._argsJSON), [preloadedQuery._argsJSON], ) as Query["_args"]; const preloadedResult = useMemo( () => jsonToConvex(preloadedQuery._valueJSON), [preloadedQuery._valueJSON], ); const result = useQuery( makeFunctionReference(preloadedQuery._name) as Query, args, ); return result === undefined ? preloadedResult : result; }

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/get-convex/convex-backend'

If you have feedback or need assistance with the MCP directory API, please join our Discord server