Academic-focused graph analysis in your AI conversations - The first and only NetworkX MCP server specialized for academic research and citation analysis. NetworkX MCP Server enables Large Language Models (like Claude) to perform sophisticated academic research and citation analysis directly within conversations. Built specifically for researchers, academics, and students who need to analyze citat
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npx mdskills install Bright-L01/networkx-mcp-serverComprehensive graph analysis server with unique academic research focus and strong documentation
1# NetworkX MCP Server23**Academic-focused graph analysis in your AI conversations** - The first and only NetworkX MCP server specialized for academic research and citation analysis.45[](https://github.com/Bright-L01/networkx-mcp-server/actions/workflows/ci.yml)6[](https://github.com/Bright-L01/networkx-mcp-server/actions/workflows/release.yml)7[](https://github.com/Bright-L01/networkx-mcp-server/actions/workflows/security.yml)8[](https://github.com/Bright-L01/networkx-mcp-server/actions/workflows/docker-build.yml)9[](https://pypi.org/project/networkx-mcp-server/)10[](https://www.python.org/downloads/)11[](https://networkx.org/)12[](https://modelcontextprotocol.io/)13[](https://opensource.org/licenses/MIT)14[](https://crossref.org/)1516## 🎓 What is this?1718NetworkX MCP Server enables Large Language Models (like Claude) to perform sophisticated **academic research and citation analysis** directly within conversations. Built specifically for researchers, academics, and students who need to analyze citation networks, calculate author impact metrics, and discover literature patterns.1920**Stop switching between VOSviewer, CitNetExplorer, and manual analysis. Start doing academic research in your AI conversations.**2122### 🎯 Key Features2324#### 🔬 Academic Research Tools2526- **Citation Network Analysis**: Build citation networks from DOIs using CrossRef API27- **Author Impact Metrics**: Calculate h-index, total citations, and academic influence28- **Literature Discovery**: Automated paper recommendations based on citation patterns29- **Collaboration Analysis**: Map co-authorship networks and identify key researchers30- **Research Trend Detection**: Analyze publication and citation trends over time3132#### 📊 Core Graph Operations3334- **20+ Graph Functions**: From basic operations to advanced algorithms like PageRank35- **BibTeX Export**: Export citation networks in academic-standard BibTeX format36- **CrossRef Integration**: Access 156+ million academic papers via DOI resolution37- **Visualization**: Generate publication-ready network visualizations38- **First of Its Kind**: The only academic-focused NetworkX MCP server3940## 🌟 Why NetworkX MCP Server for Academic Research?4142- **Built for Researchers**: Designed specifically for academic workflows and citation analysis43- **Real-time Literature Discovery**: Find related papers and collaboration opportunities instantly44- **Reproducible Research**: Python-based, version-controlled, and shareable analysis workflows45- **Academic Data Integration**: Direct access to CrossRef's 156+ million paper database46- **No Enterprise Complexity**: Focus on research, not IT infrastructure47- **Cost-Effective**: Free alternative to expensive commercial citation analysis tools4849## 📦 Installation5051```bash52pip install networkx-mcp-server53```5455## 🚀 Quick Start5657### 1. Install the server5859```bash60pip install networkx-mcp-server61```6263### 2. Configure Claude Desktop6465Add to your `claude_desktop_config.json`:6667**MacOS**: `~/Library/Application Support/Claude/claude_desktop_config.json`68**Windows**: `%APPDATA%\Claude\claude_desktop_config.json`6970```json71{72 "mcpServers": {73 "networkx": {74 "command": "python",75 "args": ["-m", "networkx_mcp"]76 }77 }78}79```8081### 3. Restart Claude Desktop8283The NetworkX tools will now be available in your conversations!8485### 🧪 Test It Works8687Ask Claude: "Create a graph called 'test', add nodes 1, 2, 3 with edges between them, then find the shortest path from 1 to 3"8889## 📊 Available Operations9091### 🔬 Academic Research Functions9293- `resolve_doi` - Resolve DOI to publication metadata using CrossRef API94- `build_citation_network` - Build citation networks from seed DOIs95- `analyze_author_impact` - Calculate h-index and impact metrics for authors96- `find_collaboration_patterns` - Analyze co-authorship networks97- `detect_research_trends` - Identify publication and citation trends over time98- `recommend_papers` - Get paper recommendations based on citation patterns99- `export_bibtex` - Export citation networks in BibTeX format100101### 📊 Core Graph Operations102103- `create_graph` - Create directed or undirected graphs104- `add_nodes` - Add nodes to your graph105- `add_edges` - Connect nodes with edges106- `get_info` - Get basic graph statistics107- `shortest_path` - Find optimal paths between nodes108109### 🔍 Analysis Operations110111- `degree_centrality` - Find the most connected nodes112- `betweenness_centrality` - Identify bridges and key connectors113- `pagerank` - Google's PageRank algorithm for node importance114- `connected_components` - Find isolated subgraphs115- `community_detection` - Discover natural groupings116117### 🎨 Visualization & I/O118119- `visualize_graph` - Create PNG visualizations with multiple layouts120- `import_csv` - Load graphs from edge lists121- `export_json` - Export graphs in standard formats122123## 🚦 Quick Start124125### Community Edition126127```bash128# Install community edition129pip install networkx-mcp-server130```131132Add to your `claude_desktop_config.json`:133134```json135{136 "mcpServers": {137 "networkx": {138 "command": "networkx-mcp",139 "args": []140 }141 }142}143```144145### Academic Research Example146147```148Human: Analyze citation patterns for the paper "Attention Is All You Need"149150Claude: I'll help you analyze citation patterns for that influential paper.151152[Resolves DOI: 10.5555/3295222.3295349]153Found paper: "Attention Is All You Need" by Vaswani et al. (2017)154Citations: 82,892 | Journal: NIPS155156[Builds citation network from seed DOI]157Built citation network with 847 nodes and 2,341 edges from 2-hop analysis158159[Analyzes author impact]160Ashish Vaswani: h-index 45, total citations 127,436161Most impactful paper: "Attention Is All You Need" (82,892 citations)162163[Finds collaboration patterns]164Key collaborators: Noam Shazeer (Google), Niki Parmar (Google)165Research cluster: Google Brain team with 47 collaborations166167[Detects research trends]168Trend: MASSIVE INCREASE in attention mechanism research post-20171692017: 12 papers → 2023: 3,847 papers (320x growth)170171[Recommends related papers]172Top recommendations based on co-citation patterns:1731. "BERT: Pre-training of Deep Bidirectional Transformers" (2018)1742. "GPT-2: Language Models are Unsupervised Multitask Learners" (2019)1753. "RoBERTa: A Robustly Optimized BERT Pretraining Approach" (2019)176177[Exports BibTeX]178Generated BibTeX file with 847 entries ready for LaTeX integration179```180181## 🎓 Academic Use Cases182183### 1. Literature Review & Meta-Analysis184185- Automatically expand citation networks from key papers186- Identify research gaps and emerging trends187- Calculate field-wide impact metrics188- Generate comprehensive BibTeX databases189190### 2. Collaboration Network Analysis191192- Map research collaborations within and across institutions193- Identify key researchers and potential collaborators194- Analyze interdisciplinary connections195- Study research community evolution196197### 3. Citation Pattern Analysis198199- Track knowledge diffusion through citation networks200- Identify influential papers and breakthrough research201- Analyze citation bias and self-citation patterns202- Study geographic and institutional citation patterns203204### 4. Research Trend Detection205206- Identify emerging research areas and hot topics207- Analyze publication volume and citation trends208- Track research lifecycle from emergence to maturity209- Predict future research directions210211### 5. Academic Impact Assessment212213- Calculate comprehensive author impact metrics214- Compare researchers across different career stages215- Analyze journal and conference impact patterns216- Study citation half-life and research longevity217218See the [demos/](demos/) folder for complete examples.219220## 📈 Performance221222- **Memory**: ~70MB (including Python, NetworkX, and visualization)223- **Graph Size**: Tested up to 10,000 nodes224- **Operations**: Most complete in milliseconds225- **Visualization**: 1-2 seconds for complex graphs226227## 🛠️ Development228229### Running from Source230231```bash232# Clone the repository233git clone https://github.com/Bright-L01/networkx-mcp-server234cd networkx-mcp-server235236# Install dependencies237pip install -e ".[dev]"238239# Run the server240python -m networkx_mcp241```242243### Running Tests244245```bash246pytest tests/working/247```248249## 📚 Documentation250251- [API Reference](docs/api.md) - Detailed operation descriptions252- [Examples](demos/) - Real-world use cases253- [Contributing](CONTRIBUTING.md) - How to contribute254255## 🤝 Contributing256257We welcome contributions! This is the first NetworkX MCP server, and there's lots of room for improvement:258259- Add more graph algorithms260- Improve visualization options261- Add graph file format support262- Optimize performance263- Write more examples264265## 📄 License266267MIT License - See [LICENSE](LICENSE) for details.268269## 🙏 Acknowledgments270271- [NetworkX](https://networkx.org/) - The amazing graph library that powers this server272- [Anthropic](https://anthropic.com/) - For creating the Model Context Protocol273- The MCP community - For inspiration and examples274275---276277**Built with ❤️ for the AI and Graph Analysis communities**278
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