Mindket
English
English简体中文
Sign inSign up
StoreMCPSkillsCalculatorLearnPriceBlog
Discover
Research312Writing59Business95Legal13Finance & accounting33Marketing & SEO175Developer1,422Productivity391Education81Companions14
Help and support
Language
English简体中文

Brave web search with an AI-written query and ranked links

by Mindketn8n workflowResearch
Newversion 1 · updated
Nodes16Apps4Like

Overview

  1. Webhook
  2. Auto-fixing Output Parser6
  3. Auto-fixing Output Parser
  4. Structured Output Parser1
  5. Anthropic Chat Model
  6. OpenAI Chat Model
  7. Structured Output Parser2
  8. Parser Model
  9. Agent Model
  10. Date & Time
  11. Semantic Search -Query Maker
  12. Query
  13. Query-1 Combined
  14. Semantic Search Result Re-Ranker
  15. Respond to Webhook
  16. Webhook Call
Brave web search with an AI-written query and ranked links, picture 1
‹2 / 2›

An n8n workflow that takes a research question by webhook, has a Google Gemini model write a search query, searches the web with Brave and has a second Gemini call rank the results. It replies with ten links.

Brave web search with an AI-written query and ranked links is an n8n workflow in the Research category, listed by Mindket. It is free. This is version 1, last updated on . Download it on this page or copy its JSON, then import it into an n8n canvas. Nothing runs until you activate it in n8n.

At a glance

Runs in
  • n8n Cloud: import the file into a new workflow there
  • Your own n8n server: the same file and steps
  • Inside another workflow: copy Webhook Call there and point it at this workflow’s production address
  • Another trigger: replace Webhook with a form, a chat or a schedule, and point the expressions that read the question at the new node

Platform

n8nWorkflow automation, in n8n’s cloud or on your own server
Connects 4 apps

How it works

Trigger

Web request

It starts when a GET request reaches the semantic-search webhook with:

  • Research Question, the question to search for

Actions

  1. The workflow adds today’s date
  2. A Gemini model writes one short search query from the question, and a second model repairs the reply if it does not fit
  3. Brave Search returns web results for that query
  4. A Code step joins each result’s title, address and description into one text
  5. A second Gemini call ranks the results against the question and extracts what the descriptions say
  6. The webhook replies with ten ranked links and the extracted notes, as JSON text

Result

A JSON reply with ten ranked links, each with a title, a link and a description, and a note on what they say about the question

Integrations

What you need before you start.

Brave Search

Web search

Returns web results for the query, each with a title, an address and a short description.

NeedsBrave Search API key, on its prepaid plan

Google Gemini

Language model

Writes the search query, ranks the results and repairs a reply that does not fit.

NeedsGoogle Gemini API key

Anthropic

Spare language model

Can replace Gemini in the chains. It is connected to nothing as shipped.

NeedsAnthropic API key, only if you use it

OpenAI

Spare language model

Can replace Gemini in the chains. It is connected to nothing as shipped.

NeedsOpenAI API key, only if you use it

Workflow check

Checked by Mindket on 13 Nov 2026

Steps
7 steps, starting when its webhook is called
Not reached
3 nodes no run reaches: Webhook Call, Anthropic Chat Model and OpenAI Chat Model
AI
2 steps call an AI model: Semantic Search -Query Maker and Semantic Search Result Re-Ranker
Sign-ins
Signs in to: Google Gemini and api.search.brave.com
API keys
No API key is left in the file; 1 blank in it for your own key
Step types
Mindket’s checker reads all 6 of its step types

Read from the workflow’s file, not from a run.

About

What it is

This n8n workflow answers a research question with a short list of web links. A caller sends the question to a webhook. A Gemini model turns it into a search query, and Brave Search returns web results for that query. A second Gemini call ranks the results against the question and picks ten. The webhook replies with the ten links, each with a title and a description, plus the facts those descriptions give. Twenty nodes do the work, four of them sticky notes.

Who it suits

Builders who want a search step inside a bigger n8n workflow or agent, one that returns ranked links instead of raw results. Skip it if you need the full text of the pages, since it reads only the titles and short descriptions that Brave returns.

Who uses it, and how
IndustryWho uses itHow they use itExample
ResearchAnalystsGet a ranked reading list for a questionAn analyst asks about new battery rules in Europe and gets ten links ordered by fit.
MarketingContent teamsFind sources for an articleA writer asks for recent surveys on remote work and picks links from the list.
SoftwareWorkflow buildersAdd a search step to an agent or a larger workflowA builder calls the webhook from another workflow and passes the links on.
SalesAccount researchersSee what the web says about a company or a topicA rep asks about a prospect’s latest product launch.

You need a little n8n: import a file, add a Google Gemini credential, paste a Brave key and call a webhook.

Where to use it

Any n8n that can reach Google’s Gemini API and Brave’s search API will run it. The answer goes back to whoever called the webhook, so it also works as a step that another workflow calls.

  • n8n Cloud: import the file into a new workflow there
  • Your own n8n server: the same file and steps
  • Inside another workflow: copy Webhook Call there and point it at this workflow’s production address
  • Another trigger: replace Webhook with a form, a chat or a schedule, and point the expressions that read the question at the new node
  • Another model: the file ships spare Anthropic and OpenAI model nodes that can replace Gemini

Setup

Download saves a zip with workflow.json and Mindket’s setup notes in your downloads folder. Setup is one model credential and one search key.

What you need first
NeedDetail
n8nOn n8n Cloud or on a server of your own
Google GeminiAn API key
Brave Search APIAn account and an API key, on its prepaid plan
  1. In n8n, create a workflow, open its menu, choose Import from File and pick workflow.json.
  2. Add a Google Gemini (PaLM) API credential with your key and select it in Parser Model and Agent Model. Both are set to models/gemini-3.6-flash, the swap for the file’s gemini-1.5-flash-002, which Google no longer lists.
  3. In Query, replace <YOUR_BRAVE_API_KEY> in the X-Subscription-Token header with your Brave key. Brave’s free plan is gone, so the key needs its prepaid plan.
  4. Open Webhook and press Listen for test event. In Webhook Call, replace <YOUR_N8N_HOST> with the address of your n8n and execute that node. You can also open the test address in a browser with ?Research%20Question= and your question after it.
  5. Read the reply in the caller, or in the output of Respond to Webhook. For regular use, activate the workflow and call /webhook/semantic-search instead of /webhook-test/semantic-search.

How to use it

Send a GET request with the question in a query field called Research Question. The workflow writes one search query from it, runs that search on Brave and ranks what comes back. The reply is JSON text. It holds Highest_RANKEDURL_1 to Highest_RANKEDURL_10, each with a title, a link and a description, and an Information_extracted field.

What to change for a different result
To changeWhere
The questionThe Research Question field of the request
How the search query is writtenThe prompt and the example in Semantic Search -Query Maker
How results are rankedThe prompts in Semantic Search Result Re-Ranker
The shape of the replyStructured Output Parser2 and the body of Respond to Webhook
The modelsAgent Model runs both chains and Parser Model runs the repairs
The search keyThe header in Query

Example

A caller asks for recent reports on Europe’s energy prices.

The reply holds ten links ordered by how well their titles and descriptions fit the question, with a note on what they say. Brave returns only a title, a link and a short description for each result, so the ranking judges those and not the pages. Open the links before you rely on them.

For newcomers and experts

If you are new. n8n draws a workflow as boxes joined by lines, and each box, a node, does one job. A webhook is an address that starts the workflow when something calls it, and the workflow sends its answer back to that caller. Search engines match words, so a long question often finds nothing. A model first shortens the question into a query, then reads the results and puts the best ones first.

For experts. Webhook answers through Respond to Webhook, because its response mode is set to that node. Both chains use Agent Model. Semantic Search -Query Maker holds a worked example in its messages and writes reasoning_summary and final_search_query through Structured Output Parser1. An Auto-fixing Output Parser with Parser Model repairs a bad reply. Query-1 Combined is a Code node that turns every web.results entry into one text block, and the Re-Ranker uses Structured Output Parser2 the same way.

Where to look closer
NodeWhat it doesWhat to know
WebhookTakes the question from the Research Question fieldA GET request by default, with no authentication
Date & TimeGives both prompts today’s dateIt is the currentDate field
Semantic Search -Query MakerWrites one search queryIts prompt asks for short queries, since long ones return nothing
QueryCalls Brave’s web searchOne request per run, with the key in a header
Query-1 CombinedJoins each result’s title, address and descriptionIt writes a line saying no results were found when there are none
Semantic Search Result Re-RankerRanks the results and extracts factsIts prompts disagree on three links or ten
Respond to WebhookReturns the ten links as JSON textThe values go in without escaping
Webhook CallCalls the webhook with a sample questionIt is connected to nothing

Good to know

The search API is no longer free, the models the file named are gone, and the webhook has no password.

  • Brave: its free plan is gone. Its pricing page, read on 12 November 2026, lists a prepaid plan at $5.00 per 1,000 requests that includes $5 in free credits every month. One run makes one search request
  • Gemini: Google’s deprecations page, read that day, lists gemini-2.0-flash for shutdown on 1 June 2026 with gemini-3.6-flash as the replacement, and gemini-1.5-flash-002 is no longer listed. Agent Model also sets all four of Gemini’s safety filters to block nothing
  • Spare models: Anthropic’s deprecations page, read that day, calls claude-haiku-4-5-20251001 Active. It also says Claude 4.7 and later models reject temperature and top_p set to non-default values. If you pick one of those, clear both options in Anthropic Chat Model. OpenAI Chat Model sets no model, so it takes the node’s default, gpt-5-mini. OpenAI lists that for shutdown on 11 December 2026 with gpt-5.6-terra as the replacement, so pick a model in it before you use it
  • Prompts: the system message of Semantic Search Result Re-Ranker says to rank the top 3, while its prompt and the output shape ask for 10. The reply carries 10. The prompt also asks for a follow-up query when the results are weak, and the output has no field for one, so it is lost
  • Reply: Respond to Webhook writes titles and descriptions into JSON text without escaping them, so a double quote in one of them breaks the JSON
  • Expressions: they read earlier nodes with $item("0").$node["Name"], an older form that n8n still runs but does not document
  • Open webhook: anyone who has its address can start a run and use your Brave and Gemini quota
  • Billing: each run makes two Gemini calls and one Brave request, plus a repair call when a parser rejects a reply
  • Your data: the question and the search results go to Google, and the search query goes to Brave
  • Credentials: the JSON holds none

README and files

README

Brave web search with an AI-written query and ranked links

An n8n workflow that answers a research question with a short list of web links. A webhook takes the question, a Google
Gemini model turns it into a search query, Brave Search returns results, and a second Gemini call ranks them and picks ten.
The webhook replies with the ten links and a note on what they say.

What is inside

  • workflow.json: the workflow as n8n exports it, 20 nodes, four of them sticky notes. It holds no credential. The notes cover
    the Brave key, the webhook call, changing the trigger and the spare model nodes.
  • README.md: these notes.

What we changed from the original copy

  • The three model nodes (Gemini, Anthropic and OpenAI) were linked to credentials in their author's n8n. The links are gone,
    so select your own.
  • The Gemini model was models/gemini-1.5-flash-002, which Google no longer lists. Both Gemini nodes now use
    models/gemini-3.6-flash.
  • The spare Anthropic node used claude-3-5-haiku-20241022, which Anthropic retired on 19 February 2026. It now uses
    claude-haiku-4-5-20251001, the model Anthropic names as its replacement.
  • The webhook's path was a generated id. It is now semantic-search, and the webhook's own id is gone.
  • Webhook Call pointed at a test address on its author's n8n host. It now points at
    https://<YOUR_N8N_HOST>/webhook-test/semantic-search.
  • The Brave key slot held the text <Insert Your API Key Here>. It now holds <YOUR_BRAVE_API_KEY>.
  • Two sticky notes were rewritten. The first described Brave's free plan, which is gone. The second named two nodes that do not
    exist, and it now names the real ones.
  • The export's workflow id, version id and instance id are gone.
  • Nothing else. The Code node needed no change.

Before you start

  • An n8n instance, on n8n Cloud or your own server.
  • A Google Gemini API key.
  • A Brave Search API account and key, on its prepaid plan.

Set it up

  1. In n8n, create a workflow, open its menu and choose Import from File. Pick workflow.json.
  2. Add a Google Gemini (PaLM) API credential with your key. Select it in Parser Model and Agent Model.
  3. In Query, replace <YOUR_BRAVE_API_KEY> in the X-Subscription-Token header with your Brave key.
  4. Open Webhook and press Listen for test event. In Webhook Call, replace <YOUR_N8N_HOST> with the address of your n8n and
    execute that node. You can also open the test address in a browser with ?Research%20Question= and your question after it.
  5. Read the reply in the caller, or in the output of Respond to Webhook.
  6. For regular use, activate the workflow and call /webhook/semantic-search instead of /webhook-test/semantic-search.

How a run goes

  1. Webhook takes a GET request and reads the question from the query field Research Question. It does not answer yet.
  2. Date & Time adds today's date.
  3. Semantic Search -Query Maker asks Agent Model for one short search query. Its prompt holds a worked example, and the
    answer is held to two fields, reasoning_summary and final_search_query, by Structured Output Parser1.
    Auto-fixing Output Parser sends a bad reply to Parser Model for a repair.
  4. Query sends the query to Brave's web search at https://api.search.brave.com/res/v1/web/search with your key in a header.
  5. Query-1 Combined, a Code node, writes the title, address and description of every result into one text, or a line saying
    no results were found.
  6. Semantic Search Result Re-Ranker gives that text, the question, the query and the date to Agent Model, which ranks the
    results and extracts what the descriptions say. The answer is held to ten ranked links and an Information_extracted field by
    Structured Output Parser2, with a second Auto-fixing Output Parser for repairs.
  7. Respond to Webhook replies to the caller with the ten links and the extracted notes, written as JSON text.

Webhook Call is a separate node that calls the webhook with a sample question. It is connected to nothing. The spare
Anthropic Chat Model and OpenAI Chat Model nodes are connected to nothing either.

Change the look

  • The question: the Research Question field of the request.
  • How the search query is written: the prompt and the example in Semantic Search -Query Maker.
  • How results are ranked: the prompts in Semantic Search Result Re-Ranker.
  • The shape of the reply: Structured Output Parser2 and the body of Respond to Webhook.
  • The models: Agent Model runs both chains and Parser Model runs the repairs. To use Claude or an OpenAI model instead, link
    the spare node to the chains and the parsers in place of the Gemini node.

Good to know

  • Brave: its free plan is gone. Its pricing page, read on 12 November 2026, lists a prepaid plan at $5.00 per 1,000 requests that
    includes $5 in free credits every month. One run makes one search request.
  • Gemini: Google's deprecations page, read that day, lists gemini-2.0-flash for shutdown on 1 June 2026 with gemini-3.6-flash
    as the replacement, and gemini-1.5-flash-002 is no longer listed. Agent Model also sets all four of Gemini's safety
    filters to block nothing.
  • Spare models: Anthropic's deprecations page, read that day, calls claude-haiku-4-5-20251001 Active. It also says Claude 4.7
    and later models reject temperature and top_p set to non-default values. If you pick one of those, clear both options in
    Anthropic Chat Model. OpenAI Chat Model sets no model, so it takes the node's default, gpt-5-mini. OpenAI lists that for
    shutdown on 11 December 2026 with gpt-5.6-terra as the replacement, so pick a model in it before you use it.
  • The ranking prompts disagree: the system message of Semantic Search Result Re-Ranker says to rank the top 3, while its prompt
    and the output shape ask for 10. The reply carries 10. The prompt also asks for a follow-up query when the results are weak, and
    the output has no field for one, so it is lost.
  • Respond to Webhook writes titles and descriptions into JSON text without escaping them, so a double quote in one of them
    breaks the JSON.
  • The expressions read earlier nodes with $item("0").$node["Name"]. n8n still runs that older form but does not document it.
  • The webhook has no authentication, so anyone who has its address can start a run and use your Brave and Gemini quota.
  • Each run makes two Gemini calls and one Brave request, plus a repair call when a parser rejects a reply.
  • Your data: the question and the search results go to Google, and the search query goes to Brave.
Files
NOTICE.md  688 B
README.md  6 KB
workflow.json  38 KB

3 files, 45 KB, downloaded as a zip.

What’s new

  • Version 1 · 2026-11-12

Reviews

No ratings yet

Write a review

No reviews yet.

More from Mindket

See all from Mindket

anaksor-ocr

Sokheng · Kit

Reads Khmer and English text from documents, receipts and photos of signs, using a detector for text lines and a recogniser for each line. Suits developers who…

New

Qwen2.5-7B-Instruct-GGUF by Qwen

Qwen · Kit

Qwen2.5-7B-Instruct as GGUF files in eight quantization sizes, to chat with locally through llama.cpp. For people who want a capable 7.6B model on their own co…

New

ACE-Step 1.5 XL SFT

ACE-Step · Kit

Generates music from text with a 4B diffusion decoder, 50 steps and guidance control, aiming for higher audio quality than the base. For creators with a GPU of…

New

Similar in Research

See all in Research

Merlin-Cancer-Super

AbdomenAtlas · Kit

Detects and outlines tumors in 9 organs on CT scans, trained with the R-Super method that learns from radiology reports. A research model for medical imaging g…

New

EarthJev

dBenf · Kit

Answers typed questions about satellite image patches from all 12 Sentinel-2 bands, returning a probability for each option without writing text. A Qwen3.5-0.8…

New

getting-over-it-rl-jax

zimmerk4 · Kit

Plays the full game Getting Over It from the bottom to the end with a small trained policy network that learned inside a JAX physics simulator. For reinforceme…

New