Use Google Search Results Scraper with Hermes Agent
Connect Hermes Agent to structured google serps, ads, ai overviews, paa, organic results so your agent can research, monitor, summarize, and take action without manual copy-paste.
Quick answer
Give Hermes Agent a structured google serps, ads, ai overviews, paa, organic results feed, then ask it to turn the results into summaries, lead lists, monitoring alerts, briefs, or follow-up tasks. This workflow is for people who want the agent to do useful research work instead of only chatting.
When you need this
- ✓You need repeatable google serps, ads, ai overviews, paa, organic results without manually copying pages into chat.
- ✓You want Hermes Agent to analyze google serps, ads, ai overviews, paa, organic results and produce decisions, not just raw rows.
- ✓You need the workflow to run from chat, cron, a terminal prompt, or a scheduled Hermes task.
- ✓You want a reusable pattern for giving Hermes Agent fresh external data.
What you can do with it
How to use it with Hermes Agent
- 1
Create an account on the data platform
Use the setup link below to create an account. It gives you $5 of credit, which is more than enough to test this Google Search Results Scraper workflow before you spend anything.
Create account and get $5 credit - 2
Add your API token to Hermes
Store the API token as APIFY_TOKEN in the Hermes environment. Do not paste the token into prompts or public files.
- 3
Run the data collection from Hermes
Ask Hermes to call the connected data API or MCP tool with your target query, for example: top Google results for “AI agent cron jobs” in the US with People Also Ask.
- 4
Make Hermes reason over the dataset
Tell Hermes the output format you want: lead list, ranked opportunities, monitoring alert, spreadsheet-ready CSV, or executive brief.
Recommended data API
Use Google Search Results Scraper (`apify/google-search-scraper`) as the collection layer. It gives your agent structured google serps, ads, ai overviews, paa, organic results without making you build and maintain a scraper from scratch.
Copy-paste prompt
You are Hermes Agent. Use Apify Actor apify/google-search-scraper (Google Search Results Scraper) to collect data for this request:
top Google results for “AI agent cron jobs” in the US with People Also Ask
After the Actor run finishes, inspect the dataset and return:
1. a short executive summary
2. the 10 most important records with source URLs
3. patterns, anomalies, or opportunities
4. recommended next actions
5. any data-quality caveats or blocked/missing fieldsAPI example
# Run the Apify Actor, then let Hermes analyze the dataset
curl -s -X POST \
"https://api.apify.com/v2/acts/apify~google-search-scraper/runs?token=$APIFY_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"query": "top Google results for “AI agent cron jobs” in the US with People Also Ask",
"maxItems": 100
}'
# In Hermes Agent, ask:
# "Read the latest Apify dataset for Google Search Results Scraper and turn it into an action plan."MCP / tool prompt example
# Hermes prompt after connecting Apify MCP
Use the Apify Actor "Google Search Results Scraper" (apify/google-search-scraper) to collect:
top Google results for “AI agent cron jobs” in the US with People Also Ask
Then:
1. remove duplicates and low-quality rows
2. summarize the strongest patterns
3. create a prioritized next-action list
4. save the source dataset link in the final answerCommon failure modes
The Actor returns too many rows for the context window
Have Hermes sample, aggregate, or write the dataset to a file before summarizing. Do not paste thousands of raw rows into a prompt.
Inputs are too broad
Start with a narrow target such as `top Google results for “AI agent cron jobs” in the US with People Also Ask` and increase maxItems only after the workflow produces useful output.
The model treats scraped data as fully verified truth
Ask Hermes to label uncertainty, preserve source URLs, and separate raw observations from recommendations.
Costs grow when the workflow is scheduled too often
Run manually first, then schedule daily/weekly only for workflows that produce business value.
Alternatives
- •Use the official platform API when it has the exact endpoint you need and the limits are acceptable.
- •Use Hermes browser automation for one-off research, but use the managed data API for repeatable collection and scheduling.
- •Use a custom scraper only when the the managed data API Actor cannot capture the fields or compliance constraints you need.
FAQ
Can Hermes Agent use Google Search Results Scraper?
Yes. Hermes can call the connected data API or MCP tool, then reason over the dataset produced by Google Search Results Scraper.
Do I need to write scraper code?
Usually no. The point of this pattern is to let the data API handle collection while Hermes handles reasoning, QA, summarization, and follow-up actions.
Should this be scheduled?
Schedule it only after a manual run proves the output is valuable. Hermes cron jobs are useful for daily monitoring, but bad inputs at scale create noisy reports.