Aira Semanticscholar MCP Server

The Aira Semanticscholar MCP server turns the Semantic Scholar Academic Graph API into a ready‑to‑use research companion for AI assistants. By exposing a rich set of tools, prompts, and resources, it lets Claude and other models perform sophisticated literature discovery, author profiling, citation network analysis, and even full‑text retrieval—all within a single conversational turn. This eliminates the need for developers to write custom API wrappers or handle authentication, letting them focus on higher‑level research workflows.

At its core, the server solves the problem of scattered scholarly data. Researchers and developers often need to query multiple endpoints—search, author details, citations, PDFs—to assemble a literature review. Aira consolidates these operations into a single, well‑documented MCP interface. The result is a streamlined pipeline where an AI assistant can ask for “top 10 recent papers on graph neural networks in biology” and instantly receive structured results, citation graphs, and even downloadable PDFs if access permits. This integration reduces latency, eliminates duplicate requests, and provides consistent error handling.

Key capabilities include:

• Comprehensive paper search with keyword, advanced filters (year, citation count, field of study), title matching, and batch retrieval.
• Author discovery that returns full profiles, metrics such as h‑index, and publication lists.
• Citation network traversal that explores citing papers, reference lists, and multi‑depth impact analysis.
• Field‑specific browsing of top papers by discipline or venue, with open‑access filtering.
• Full‑text access for arXiv and Wiley papers, including in‑memory PDF processing and text extraction—subject to institutional or subscription constraints.

In practice, developers can embed Aira into research assistants that:

• Generate literature reviews by automatically fetching and summarizing the latest studies on a topic.
• Identify collaboration opportunities by profiling authors’ work and citation overlap.
• Track research impact through dynamic citation network visualizations.
• Support systematic reviews by retrieving all relevant papers from a field and organizing them by venue or year.

Aira’s standout advantage lies in its rate‑controlled, authenticated access to Semantic Scholar and Wiley APIs. By respecting limits (e.g., 100 requests per 5 minutes for Semantic Scholar, 3 articles/second for Wiley) and offering optional TDM token configuration, it ensures reliable operation without overstepping usage policies. This robustness, combined with the ease of invoking sophisticated scholarly queries via MCP prompts, makes Aira a powerful asset for any AI‑driven research workflow.