Integrate MIT DBLP with Claude, Cursor, Chatbots & AI Agents MCP Server
GDPR Free for SubscribersCompatible with every major AI agent and IDE
GeminiGet author on MIT DBLP
The PID can be found in DBLP URLs (e.g. for "https://dblp.org/pid/b/YoshuaBengio" the PID is "b/YoshuaBengio"). Get author profile by DBLP PID
Get author publications on MIT DBLP
Returns up to 40 most recent publications with full metadata. Use the author name as it appears on DBLP. Get all publications by a specific author
Get author stats on MIT DBLP
Essential for evaluating research productivity and impact. Get publication statistics for an author
Get coauthors on MIT DBLP
Returns a ranked list of collaborators ordered by number of joint publications. Essential for understanding research collaboration patterns. Get co-author network of a researcher
Get publication on MIT DBLP
g. "journals/cacm/Knuth74", "conf/nips/VaswaniSPUJGKP17"). The key uniquely identifies every record in DBLP. Get publication details by DBLP key
Get venue on MIT DBLP
Use conference abbreviations (ICML, NeurIPS, SIGMOD) or full journal names. Get venue details (conference or journal)
Get venue publications on MIT DBLP
Essential for exploring what was published at a particular conference edition (e.g. NeurIPS 2024). Get papers published at a specific venue
Search ai papers on MIT DBLP
These are the premier conferences for artificial intelligence and machine learning research. Search AI and machine learning papers at top venues
Search authors on MIT DBLP
Returns author names, DBLP profile URLs, and disambiguation notes. DBLP meticulously disambiguates authors with the same name. Search computer science authors on DBLP
Search by year on MIT DBLP
Useful for tracking research trends over time or finding papers from a specific conference edition. Search publications filtered by year
Search database papers on MIT DBLP
Search database papers at top venues
Search in venue on MIT DBLP
Combine a venue name with an optional topic query to find relevant papers at a particular venue. Search for papers within a specific venue
Search publications on MIT DBLP
Covers all major conferences (NeurIPS, ICML, SIGMOD, VLDB, OSDI) and journals (JACM, TOCS, VLDBJ). Returns titles, authors, venues, years, DOIs, and DBLP keys. Search 6M+ computer science publications on DBLP
Search systems papers on MIT DBLP
Search systems papers at top venues
Search theory papers on MIT DBLP
Search theoretical CS papers at top venues
Search venues on MIT DBLP
Returns venue names, DBLP URLs, and types. Search CS conferences and journals
Security & Code Integrity Audit
Every tool in the MIT DBLP MCP Server is continuously audited by the Vinkius Security Engine. We guarantee zero-trust payload isolation, strict data boundaries, and deterministic execution for enterprise-grade AI agents.
How Vinkius protects your data
Is there a risk of the AI "going crazy" and deleting important company data?
No. With Vinkius, the AI operates on "rails". It can only make the exact moves you authorized in the tool's settings. It cannot invent routes, access other networks in your company, or decide to delete random files. If the action isn't in the approved catalog, the attempt is blocked instantly.
What venues does DBLP cover?
DBLP indexes all major CS conferences (NeurIPS, ICML, SIGMOD, OSDI, STOC) and journals (JACM, TOCS, IEEE TPAMI). It covers over 6 million publications from thousands of venues worldwide.
How does the AI access my passwords and credentials?
It simply doesn't. On Vinkius, your passwords, API keys, and login details are kept in a secure vault. The AI (like ChatGPT or Claude) merely "asks" Vinkius to perform the task. Vinkius opens the door, does the work, and hands the result back to the AI. Your credentials are never seen, read, or learned by the artificial intelligence.
Does the AI train on my tools or API data?
No. Vinkius enforces a strict Zero-Retention policy. Your data simply passes through our secure servers to complete the requested action and is instantly forgotten. Nothing you do here is ever stored, logged, or used to train any artificial intelligence.
Triggering MIT DBLP via Natural Language
This integration supports direct MCP execution, enabling your chatbots to query and modify data within these specific environments.
Connecting academic research with Cursor
Use MIT DBLP to interface with academic research via natural language. The toolkit provides Cursor with LLM-friendly schemas for knowledge management tasks.
Cursor Copilot for bibliography
Use MIT DBLP to manage bibliography via conversational interfaces. The integration centralizes access control for knowledge management operations performed by ChatGPT.
MIT DBLP. Runs on everything.
From IDE to framework. Every connection governed by Vinkius.
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TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
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