MCP-DBLP

Provides real-time access to Wikipedia via Model Context Protocol, enabling large language models to search articles, retrieve full content, summaries, sections, links, and related topics across multiple languages for accurate and up-to-date contextual information.

Model Context Protocol server offering SAT, SMT, and constraint solving integration with Large Language Models, supporting MiniZinc, PySAT, and Z3 backends for interactive model creation, editing, and solving.

Provides Model Context Protocol (MCP) integration enabling large language models to perform advanced geographic data conversions, including format transformations between WKT, GeoJSON, CSV, TopoJSON, and KML, as well as reverse geocoding for coordinate-to-location mapping.

Model Context Protocol server enabling seamless search and download of academic papers from arXiv, PubMed, bioRxiv, and Sci-Hub with standardized output and integration for large language models.

Provides Model Context Protocol integration with a note-taking system, enabling AI models to manage notebooks, manipulate documents and blocks, handle files and assets, execute SQL queries, perform full-text search, export content, and utilize system and template functions for enhanced note data access and control.