AI-native web search, content retrieval, and answers via Exa.
Exa ships in the w6w first-party pack. It declares 9 actions, 3 health checks, and the host runs its code in a sandbox that never sees the credential.
io.w6w.exaExa is a search engine built for AI: instead of ten blue links, it returns embeddings-ranked, LLM-summarized web results built for a workflow to consume directly. This app covers its core surface — Search (prompt-engineered web search with several latency/depth modes), Get Contents (crawled text/highlights/summaries for known URLs), Find Similar Links (semantic similarity search from a seed URL), and Answer (a direct, cited answer synthesized from web search) — plus a slice of the newer Websets API, which runs an ongoing entity search (companies, people, publications, …) rather than one page of results: create, look up, list and delete a Webset, and list the items it has found.
Exa charges per call rather than by subscription, which shapes two choices here: the auth connection test and both health checks read GET /v0/teams/me (free account metadata) instead of a live search, and a dedicated health check declares the one thing the API genuinely does not expose — a queryable prepaid credit balance — as absent rather than guessing at it.
Three routes to the same 9 actions. The Workflow tab is generated from Exa's own manifest and carries its real ids, so it is copy-pasteable; the Code and CLI examples are the same call for any action on any app, so every app-specific value in them is a blank you fill in.
create-webset Start a Webset: an ongoing search for entities matching a natural-language query.
A workflow step names the app and the action, and the editor fills in the
connection when you pick one. This is the Step shape from the
workflow spec, carrying Exa's real ids.
{
"manifestVersion": "2",
"name": "exa-example",
"steps": [
{
"id": "answer",
"uses": {
"app": "io.w6w.exa",
"action": "answer",
"connection": "conn_YOUR_CONNECTION_ID"
},
"with": {
"query": "<query>"
}
}
]
}answer create-webset find-similar get-contents get-webset +4 more actions available
Every app-specific value here is a blank you have to fill in. An
app action is reached through the connection that authenticates it, so the
address is a connection id, not the app id — and connections belong to your account,
so a public page cannot know yours. Create one for Exa, then fill in
the three blanks: conn_YOUR_CONNECTION_ID, the action key, and the
parameters that action declares. The call itself is real — the shape is transcribed
from the studio's own snippet builder, which prints the same kind of blanks — but
nothing in it is specific to Exa. The Workflow tab is where this app's
real ids are.
npm install @w6w/sdkyarn add @w6w/sdkpnpm add @w6w/sdkdeno add npm:@w6w/sdkimport { W6wClient, isActionRun } from "@w6w/sdk";
// Reads W6W_BASE_URL and W6W_TOKEN from the environment when omitted.
const client = new W6wClient();
const envelope = await client.run({
urn: "conn_YOUR_CONNECTION_ID",
action: "answer",
payload: {
query: "<value>",
// text: "<value>",
// model: "<value>",
// systemPrompt: "<value>",
// userLocation: "<value>",
// outputSchema: "<value>",
},
});
if (isActionRun(envelope)) console.log(envelope.value); npm install -g @w6w/cli w6w run conn_YOUR_CONNECTION_ID --action answer --payload '{"query":"<value>"}' Give an AI agent Exa — without giving it Exa's credentials. One MCP endpoint exposes every app, function and workflow the caller is entitled to, as tools it can discover and run. Access is granted per team while we onboard.
One tool call{
"name": "w6w_invoke",
"arguments": {
"ref": "app:io.w6w.exa#answer",
"input": {
"query": "<query>"
}
}
}
Every tool names its target with a single ref. The
app: form above doesn't name a connection at all — the
host resolves which of the caller's Exa connections to sign
with, and refuses rather than guesses when the answer is ambiguous.
The token is attached host-side, at the moment of the call. It is never a tool argument, never in the model's context, and never in a transcript — so a prompt injection has nothing to exfiltrate.
Tools are derived per end user from what that person has actually connected and is entitled to — not one shared bot identity carrying the union of everyone's access.
Multi-step work runs on the workflow engine and returns a run handle the agent can poll — retries, branching and state survive the conversation that started them.
Exa's declared health checks are on the surface too, so an agent can tell "the vendor is down" from "your credential expired" before it burns a retry on either.
The MCP surface is part of the hosted platform. Exa itself is MIT, and the runtime that executes it is source-available (FSL).
Exa declares its own checks, so its health is a property of the app rather than something the host guesses at.
Component status from status.exa.ai's components.json: Search API (People, Default), Websets, Exa MCP.
Active/queued request concurrency against this team's limits, from GET /v0/teams/me.
Not exposed: the Exa OpenAPI spec documents no account/credits/balance endpoint — only each response's own after-the-fact costDollars.