This MCP makes Hermes Agent 10x more powerful

Key Concepts

• Hermes Agent: A popular open-source AI agent framework that runs locally and can be extended with various tools.
• Apify: A cloud platform providing over 40,000 "actors" (web scrapers/automation tools) capable of extracting data from restrictive websites (e.g., LinkedIn, Google Maps, Instagram).
• MCP (Model Context Protocol): A standard that allows AI agents to connect to external data sources and tools, such as databases or web scrapers.
• Supabase: An open-source Firebase alternative used here as a database to store scraped leads and analysis results.
• Automation: The process of using cron jobs and scheduled tasks to create a self-sustaining loop of data collection, analysis, and reporting.

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1. Setting Up the Hermes Agent

The Hermes Agent is installed locally on a machine (e.g., MacBook) using a single command from its GitHub repository.

• Configuration: During setup, users must provide an API key (e.g., OpenRouter) and select an LLM (e.g., Opus 4.8 fast).
• Environment: The agent runs locally, allowing for private interaction and integration with local environment variables (.env).

2. Web Scraping with Apify

Apify acts as the "eyes" for the AI agent, bypassing the limitations of standard web browsing.

• Methodology: Users select an "actor" from the Apify store based on the target platform (e.g., LinkedIn).
• Process:
  1. Configure the actor with search parameters (e.g., job title, location).
  2. Run the actor to generate structured JSON data.
  3. Use the Universal MCP Connector to bridge the gap between the Apify dataset and a database like Supabase.
• Advantage: This approach avoids the need for account cookies or manual logins, reducing the risk of being banned by platforms with strict Terms of Service.

3. Database Integration (Supabase)

Supabase serves as the central repository for the scraped data.

• Setup: Create a project, define a schema (e.g., a leads table), and generate a Service Role Key to allow the Hermes Agent to read/write data.
• Security: The presenter emphasizes the importance of rotating API keys and keeping the Service Role Key private, as it grants full access to the database.

4. Agentic Workflow: Analysis and Automation

The core value lies in connecting the agent to the database to perform intelligent tasks.

• Step-by-Step Analysis:
  1. Prompting: The user instructs Hermes to read the leads table.
  2. Evaluation: The agent scores candidates (0–100) based on specific criteria (e.g., AI automation experience, seniority).
  3. Writing Back: The agent updates the database with scores, reasoning, and tags.
• Full Automation:
  • Hermes Side: A cron job is created within the agent to run the analysis daily at a set time (e.g., 8:00 AM).
  • Apify Side: The scraping task is scheduled to run at specific intervals (e.g., every 6 hours) to ensure the database is constantly refreshed with new leads.

5. Notable Quotes

• "Apify is one of the first tools you want to connect to any AI agent you build so that you make it instantly 10,000 times more powerful."
• "This is structured JSON—this is the stuff that AI agents dream of."
• "If you don't use an agent for that, a human has to do that... this alone would put you ahead of 99% of companies."

6. Synthesis and Conclusion

The combination of Hermes Agent and Apify creates a powerful, automated pipeline that transforms raw, unstructured web data into actionable business intelligence. By offloading repetitive tasks—such as lead qualification, candidate screening, or market research—to an AI agent, businesses can achieve significant operational efficiency. The workflow is highly scalable: once the MCP connection is established and the cron jobs are set, the system functions autonomously, allowing the user to focus on high-level decision-making rather than manual data processing.