How I turned a Spanish public-tenders scraper into a tool my AI agent can call

What happened

A developer created an Apify Actor to process and filter Spanish public tenders from the PLACSP platform, making it accessible to AI agents through the Apify MCP server. The tool includes filtering logic, a sector dictionary, and a pay-per-event model to ensure efficient and accurate query handling.

Why it matters

This tool demonstrates how AI agents can be integrated with public data sources to automate complex tasks like procurement research. It highlights the importance of structured data filtering and the role of AI in improving access to public information.

• Effective data filtering is crucial for making public data usable for AI agents.
• Sector-specific dictionaries enhance search accuracy by translating user queries into procurement terminology.
• Pay-per-event models optimize costs for AI-driven data processing.
• Input validation and error handling are essential for reliable AI tool integration.
• Integrating public data sources with AI agents can significantly improve business efficiency.

The bigger picture

The tool enables more efficient and accurate access to Spanish public tenders, reducing manual effort for businesses and improving the capabilities of AI agents in procurement research. It also sets a precedent for integrating public data sources with AI systems.

The article presents a practical example of how AI agents can be empowered to access and process public data, demonstrating the value of structured filtering and integration techniques in improving procurement research efficiency.

Technical details

• Apify Actor for data scraping and filtering
• CODICE XML schema with multiple namespaces
• Priority-based filtering with keyword, contract type, and CPV code
• Sector dictionary for expanding search terms into procurement language
• Pay-per-event pricing model with event name validation
• Apify MCP server integration for AI agent access

FAQ