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
import { defineSchema, defineTable } from "convex/server";
import { v } from "convex/values";
export default defineSchema({
messages: defineTable({
isViewer: v.boolean(),
sessionId: v.string(),
text: v.string(),
}).index("bySessionId", ["sessionId"]),
documents: defineTable({
url: v.string(),
text: v.string(),
}).index("byUrl", ["url"]),
chunks: defineTable({
documentId: v.id("documents"),
text: v.string(),
embeddingId: v.union(v.id("embeddings"), v.null()),
})
.index("byDocumentId", ["documentId"])
.index("byEmbeddingId", ["embeddingId"]),
embeddings: defineTable({
embedding: v.array(v.number()),
chunkId: v.id("chunks"),
})
.index("byChunkId", ["chunkId"])
.vectorIndex("byEmbedding", {
vectorField: "embedding",
dimensions: 1536,
}),
});