MIT DBLP MCP Server for LlamaIndexGive LlamaIndex instant access to 16 tools to Get Author, Get Author Publications, Get Author Stats, and more

Name: MIT DBLP
Price: 29 USD
Availability: InStock
Rating: 2.2 (1 reviews)
Author: Vinkius

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LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add MIT DBLP as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

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The MIT DBLP MCP Server for LlamaIndex is a standout in the Knowledge Management category — giving your AI agent 16 tools to work with, ready to go from day one.

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python

import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to MIT DBLP. "
            "You have 16 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in MIT DBLP?"
    )
    print(response)

asyncio.run(main())

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About MIT DBLP MCP Server

Connect to the DBLP Computer Science Bibliography — the most comprehensive index of CS research, maintained by Schloss Dagstuhl.

LlamaIndex agents combine MIT DBLP tool responses with indexed documents for comprehensive, grounded answers. Connect 16 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

What you can do

Full-Text Search — Search 6M+ CS publications across all venues
Author Profiles — Explore researcher profiles and publication histories
Venue Browsing — Search conferences (NeurIPS, ICML, SIGMOD, OSDI) and journals (JACM, TOCS)
Co-Author Networks — Discover collaboration patterns between researchers
AI/ML Papers — Dedicated search for NeurIPS, ICML, ICLR, and AAAI papers
Systems Papers — Dedicated search for OSDI, SOSP, SIGCOMM, NSDI papers
Theory Papers — Dedicated search for STOC, FOCS, SODA papers
Database Papers — Dedicated search for SIGMOD, VLDB, ICDE papers
Author Statistics — Publication counts, venue distribution, and year-over-year trends

The MIT DBLP MCP Server exposes 16 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 16 MIT DBLP tools available for LlamaIndex

When LlamaIndex connects to MIT DBLP through Vinkius, your AI agent gets direct access to every tool listed below — spanning academic-research, bibliography, computer-science, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

get

Get 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

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

Get author stats on MIT DBLP

Essential for evaluating research productivity and impact. Get publication statistics for an author

get

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

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

Get venue on MIT DBLP

Use conference abbreviations (ICML, NeurIPS, SIGMOD) or full journal names. Get venue details (conference or journal)

get

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

Connect MIT DBLP to LlamaIndex via MCP

Follow these steps to wire MIT DBLP into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 16 tools from MIT DBLP

Why Use LlamaIndex with the MIT DBLP MCP Server

LlamaIndex provides unique advantages when paired with MIT DBLP through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine MIT DBLP tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain MIT DBLP tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query MIT DBLP, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what MIT DBLP tools were called, what data was returned, and how it influenced the final answer

MIT DBLP + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the MIT DBLP MCP Server delivers measurable value.

Hybrid search: combine MIT DBLP real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query MIT DBLP to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying MIT DBLP for fresh data

Analytical workflows: chain MIT DBLP queries with LlamaIndex's data connectors to build multi-source analytical reports

Example Prompts for MIT DBLP in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with MIT DBLP immediately.

"Find recent AI papers on large language models at NeurIPS"

"Search for publications by Yoshua Bengio"

"Find the latest database systems papers from SIGMOD and VLDB"

Troubleshooting MIT DBLP MCP Server with LlamaIndex

Common issues when connecting MIT DBLP to LlamaIndex through Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

MIT DBLP + LlamaIndex FAQ

Common questions about integrating MIT DBLP MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query MIT DBLP tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.