Academia
Academia MCP is a research-focused server built by Ilya Gusev that provides comprehensive tools for scientific literature discovery, analysis, and reporting. It integrates with ArXiv, ACL Anthology, Semantic Scholar, Hugging Face datasets, and multiple web search providers (Exa, Brave, Tavily) to enable paper search, citation analysis, and reference tracking. The server includes LaTeX compilation capabilities, PDF processing, and optional LLM-powered features for document Q&A, paper review generation, and research proposal workflows using the "bitflip" methodology. It supports both HTTP and stdio transports with configurable tool availability based on API keys, making it useful for literature reviews, academic research workflows, citation analysis, and automated paper evaluation tasks.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-02.
Scan details: Circle-IR · 2026-09-02 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- ai-ml
- Source
- PulseMCP
- Repository
- github.com/ilyagusev/academia_mcp
- Author type
- human
- Last scanned
- 2026-09-02
- Updated
- 2026-09-02
Use via MCP
Resolve Academia from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.