Accelerating the development of carbon capture materials necessitates rapid synthesis of fragmented scientific knowledge. To address this challenge, we developed an LLM-powered pipeline that extracts and structures insights from over 40,000 peer-reviewed publications, enabling data-driven decisions for CO₂ capture technology implementation. Our workflow integrates prompt engineering and text clustering to systematically identify material performance trends (adsorption capacity, surface area) and techno-economic indicators (stability, regenerability). We provide insights on "hidden gem" materials underexplored potential and explore property variations in widely studied materials. Extracted data will be made publicly available via an interactive dashboard, empowering the community to accelerate material design. By transforming unstructured literature into structured decision frameworks, we enable rapid prioritization of R&D investments in carbon capture.