DP

DPLP MCP Server: DBLP Computer Science Search

Search the DBLP computer science bibliography with the DPLP MCP server to find authors, publications, and citations fast.

Quick Install
npx -y @szeider/mcp-dblp

Overview

The DPLP MCP Server provides a lightweight, MCP-compatible interface for searching the DBLP computer science bibliography. It exposes APIs that let language models and developer tools query DBLP metadata (authors, publications, venues, and citation relations) in a structured JSON form. By wrapping DBLP behind the Model Context Protocol (MCP), this server makes bibliographic search and citation lookup usable as a first-class tool in automated workflows and LLM toolchains.

This server is useful when you want low-latency programmatic access to DBLP data without scraping HTML pages or parsing the entire XML on every request. It indexes DBLP metadata to provide fast lookups, returns structured results (authors, titles, years, venues, citation links) and advertises itself via MCP tool descriptors so that LLM-driven agents can discover and call DBLP search functions directly.

Features

  • MCP-compatible tool discovery and execution (suitable for LLM integrations)
  • Search by author name, publication title, year, venue, or combinations
  • Retrieve publication metadata: title, authors, year, venue, DOI, URL
  • Citation lookup: list citing/cited works and simple citation graph traversal
  • Fast indexed search for sub-second queries on common workloads
  • Docker-ready and configurable for local or server deployment
  • JSON REST API responses for easy consumption by services or agents

Installation / Configuration

Prerequisites:

  • Docker (recommended) or a JVM/runtime capable of running the packaged server
  • DBLP data file (XML) or an already generated metadata index
  1. Run with Docker (recommended)
# Example: run container, mount local DBLP XML and expose port 8080
docker run --rm -p 8080:8080 \
  -v /path/to/dblp.xml:/data/dblp.xml:ro \
  -e DBLP_XML=/data/dblp.xml \
  ghcr.io/szeider/mcp-dblp:latest
  1. Run from a packaged JAR (if available)
# Build or download the JAR, then run with DBLP path and port
java -jar mcp-dblp.jar --dblp /path/to/dblp.xml --port 8080
  1. Environment / CLI configuration options (typical)
  • DBLP_XML: path to DBLP XML file (or path to pre-built index)
  • PORT: port to bind the HTTP server (default: 8080)
  • INDEX_DIR: directory to store or load a search index
  • MAX_RESULTS: default maximum number of results per query

Example systemd unit or environment:

[Service]
Environment=DBLP_XML=/data/dblp.xml
Environment=PORT=8080
ExecStart=/usr/bin/java -jar /opt/mcp-dblp/mcp-dblp.jar --dblp ${DBLP_XML} --port ${PORT}

Available Resources

The server exposes a small set of MCP-friendly resources (typical names and shapes):

  • Tool discovery endpoint (MCP descriptor)

    • GET /mcp/tools
    • Returns JSON array of tool descriptors (name, description, params)
  • Execution endpoint for tools

    • POST /mcp/run
    • Body: { “tool”: “dblp_search”, “input”: { … } }
    • Response: structured JSON results
  • Direct search endpoints (convenience)

    • GET /search/authors?q={query}&limit=10
    • GET /search/pubs?q={query}&year={year}&limit=10
    • GET /citations?id={publication_id}&direction=inbound|outbound

Sample MCP tool descriptor (simplified)

{
  "name": "dblp_search",
  "description": "Search DBLP for authors and publications",
  "parameters": {
    "type": "object",
    "properties": {
      "query": { "type": "string" },
      "filter": { "type": "object" }
    },
    "required": ["query"]
  }
}

Response shape for publication search

[
  {
    "id": "conf/icml/Smith20",
    "title": "Efficient ML Algorithms",
    "authors": ["Jane Smith", "A. Researcher"],
    "year": 2020,
    "venue": "ICML",
    "doi": "10.1145/...",
    "url": "https://dblp.org/rec/conf/icml/Smith20"
  }
]

Use Cases

  1. Integrating DBLP into an LLM agent
  • Use the MCP discovery endpoint to register a “dblp_search” tool.
  • The agent can call the tool to fetch author lists or publication metadata while composing answers, enabling up-to-date citations and references.
  1. Building a search UI or microservice
  • Provide a web front-end that queries /search/pubs and /search/authors endpoints.
  • Offer faceted filters (year, venue) using query parameters returned by the server.
  1. Citation analysis and simple graph queries
  • Retrieve inbound or outbound citations for a paper using /citations?id=…
  • Aggregate counts by year or author to detect trends or influential publications.
  1. Programmatic bibliography extraction
  • Batch-query author names and retrieve formatted metadata (title, venue, DOI) for export to BibTeX or RIS.

Query parameter reference

| Parameter | Type | Description | |———–