MCP-DBLP Server for Academic Literature & Citation Management

What does “MCP-DBLP” MCP Server do?

The MCP-DBLP server provides seamless access to the DBLP computer science bibliography database for Large Language Models (LLMs) using the Model Context Protocol (MCP). By integrating the DBLP API, MCP-DBLP enables AI assistants to search and retrieve academic publications, process citations, generate BibTeX entries, and perform fuzzy matching on publication titles and author names. It also supports the extraction and formatting of bibliographic information, embedded reference processing, and direct BibTeX export for high-accuracy citation management. With comprehensive search capabilities, filtering, and statistical analysis, MCP-DBLP empowers developers and researchers to enhance their workflows when working with academic literature, bibliographic data, and scholarly references.

List of Prompts

• Instructions Prompt:
  A reusable prompt template is included in instructions_prompt.md to be used together with text containing citations. On Claude Desktop, this prompt can be accessed via the electrical plug icon.

Ready to grow your business?

Start your free trial today and see results within days.

Request demo Log in

List of Resources

• (No explicit MCP resource primitives are mentioned in the provided documentation or code. If the server exposes resources, details are not listed.)

List of Tools

• search
  Search DBLP for publications using boolean queries. Supports operators like ‘and’/‘or’, result limits, year filtering, and venue substring filtering.
• fuzzy_title_search
  Perform a search for publications with fuzzy title matching.
• get_author_publications
  Retrieve all publications for a specific author.
• get_venue_info
  Get detailed information about a publication venue.
• calculate_statistics
  Generate statistics from publication search results.
• export_bibtex
  Export BibTeX entries directly from DBLP to files, bypassing LLM processing for accuracy.

Join our newsletter

Get latest tips, trends, and deals for free.

Email address

Subscribe

Use Cases of this MCP Server

• Academic Literature Search
  Developers and researchers can search the DBLP database for relevant academic papers using advanced boolean queries and filters, streamlining literature reviews and knowledge discovery.
• Citation Management
  Quickly generate and export accurate BibTeX entries for use in academic writing, presentations, or reference management tools.
• Author and Venue Exploration
  Retrieve all publications by a specific author or get detailed information about conferences and journals, aiding in research analytics and networking.
• Bibliographic Data Extraction
  Extract and structure bibliographic data from documents, making it easier to process embedded citations or references in manuscripts.
• Publication Metrics and Statistics
  Perform statistical analysis on publication data to identify trends, research output, or impact within specific venues or timeframes.

How to set it up

Windsurf

1. Prerequisites: Ensure Python 3.11+ and uv are installed.
2. Clone Repo:
   git clone https://github.com/szeider/mcp-dblp.git
3. Setup Environment:

   cd mcp-dblp
   uv venv
   source .venv/bin/activate
   uv pip install -e .
   

4. Configure: Edit the Windsurf MCP configuration file to include:

   {
     "mcpServers": {
       "mcp-dblp": {
         "command": "uv",
         "args": [
           "--directory",
           "/absolute/path/to/mcp-dblp/",
           "run",
           "mcp-dblp",
           "--exportdir",
           "/absolute/path/to/bibtex/export/folder/"
         ]
       }
     }
   }
   

5. Restart & Verify: Save, restart Windsurf, and confirm MCP-DBLP server appears in your tool list.

Claude

1. Prerequisites: Install Claude Desktop app and Python 3.11+.
2. Clone and Setup:

   git clone https://github.com/szeider/mcp-dblp.git
   cd mcp-dblp
   uv venv
   source .venv/bin/activate
   uv pip install -e .
   

3. Edit Config:
   • macOS/Linux: ~/Library/Application/Support/Claude/claude_desktop_config.json
   • Windows: %APPDATA%\Claude\claude_desktop_config.json
4. Add MCP-DBLP: Include:

   {
     "mcpServers": {
       "mcp-dblp": {
         "command": "uv",
         "args": [
           "--directory",
           "/absolute/path/to/mcp-dblp/",
           "run",
           "mcp-dblp",
           "--exportdir",
           "/absolute/path/to/bibtex/export/folder/"
         ]
       }
     }
   }
   

5. Save & Restart: Save configuration, restart Claude, and verify server is available.

Cursor

1. Ensure Prereqs: Python 3.11+ and uv are installed.
2. Install MCP-DBLP:

   git clone https://github.com/szeider/mcp-dblp.git
   cd mcp-dblp
   uv venv
   source .venv/bin/activate
   uv pip install -e .
   

3. Locate Cursor Config: Open your Cursor MCP configuration file.
4. Add Entry:

   {
     "mcpServers": {
       "mcp-dblp": {
         "command": "uv",
         "args": [
           "--directory",
           "/absolute/path/to/mcp-dblp/",
           "run",
           "mcp-dblp",
           "--exportdir",
           "/absolute/path/to/bibtex/export/folder/"
         ]
       }
     }
   }
   

5. Restart Cursor: Save and restart Cursor to activate MCP-DBLP.

Cline

1. Install Dependencies: Python 3.11+ and uv.
2. Clone and Prepare:

   git clone https://github.com/szeider/mcp-dblp.git
   cd mcp-dblp
   uv venv
   source .venv/bin/activate
   uv pip install -e .
   

3. Edit Cline Config: Locate the MCP server configuration.
4. Insert MCP-DBLP Block:

   {
     "mcpServers": {
       "mcp-dblp": {
         "command": "uv",
         "args": [
           "--directory",
           "/absolute/path/to/mcp-dblp/",
           "run",
           "mcp-dblp",
           "--exportdir",
           "/absolute/path/to/bibtex/export/folder/"
         ]
       }
     }
   }
   

5. Confirm & Restart: Save, restart Cline, and check tool availability.

Securing API Keys:
If API keys or secrets must be provided, use environment variables for security. Example configuration:

{
  "mcpServers": {
    "mcp-dblp": {
      "command": "uv",
      "args": [ ... ],
      "env": {
        "SOME_API_KEY": "${YOUR_API_KEY_ENV_VAR}"
      },
      "inputs": {
        "api_key": "${YOUR_API_KEY_ENV_VAR}"
      }
    }
  }
}

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "mcp-dblp": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “mcp-dblp” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Based on the above, MCP-DBLP offers strong documentation and tooling, but lacks explicit resource and sampling support in the visible documentation. The prompt template and tool coverage are excellent, but the absence of resource primitives and sampling lowers the comprehensiveness slightly.

MCP Score

Our Opinion:
MCP-DBLP is a robust and specialized MCP server, particularly well-suited for academic and bibliographic workflows. Its toolset is comprehensive for DBLP integration and citation management, but the lack of explicit resource and sampling support means it may not fully utilize all MCP features yet. Usability and setup are well-documented.

Overall Score: 7.5/10