Awesome/awesome-mcp-servers
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Merge pull request #8399 from chohyerinn/main

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Add filter-mcp-server to Data Science Tools
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Frank Fiegel
2026-06-23 10:01:45 -07:00
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@@ -1318,6 +1318,7 @@ Integrations and tools designed to simplify data exploration, analysis and enhan
- [bradleylab/stella-mcp](https://github.com/bradleylab/stella-mcp) 🐍 🏠 - Create, read, validate, and save Stella system dynamics models (.stmx files in XMILE format) for scientific simulation and modeling.
- [BlackMount-ai/blackmount-nlp-mcp](https://github.com/BlackMount-ai/blackmount-nlp-mcp) [![BlackMount-ai/blackmount-nlp-mcp MCP server](https://glama.ai/mcp/servers/BlackMount-ai/blackmount-nlp-mcp/badges/score.svg)](https://glama.ai/mcp/servers/BlackMount-ai/blackmount-nlp-mcp) 🐍 🏠 🍎 🪟 🐧 - Deterministic local text analysis: sentiment, readability scoring, keyword extraction, text similarity, summarization, and language detection across 18 languages. Pure Python, zero heavy dependencies, 42 KB wheel. Install: `pip install blackmount-nlp-mcp`.
- [Bright-L01/networkx-mcp-server](https://github.com/Bright-L01/networkx-mcp-server) 🐍 🏠 - The first NetworkX integration for Model Context Protocol, enabling graph analysis and visualization directly in AI conversations. Supports 13 operations including centrality algorithms, community detection, PageRank, and graph visualization.
- [chohyerinn/filter-mcp-server](https://github.com/chohyerinn/filter-mcp-server) 🐍 🏠 - Compares approximate filter data structures (Bloom, Counting Bloom, Cuckoo, SuRF) via MCP [![filter-mcp-server MCP server](https://glama.ai/mcp/servers/chohyerinn/filter-mcp-server/badges/score.svg)](https://glama.ai/mcp/servers/chohyerinn/filter-mcp-server)
- [ChronulusAI/chronulus-mcp](https://github.com/ChronulusAI/chronulus-mcp) 🐍 ☁️ - Predict anything with Chronulus AI forecasting and prediction agents.
- [clouatre-labs/math-mcp-learning-server](https://github.com/clouatre-labs/math-mcp-learning-server) 🐍 ☁️ 🏠 🍎 🪟 🐧 - Educational MCP server for math operations, statistics, visualization, and persistent workspaces. Built with FastMCP 2.0.
- [Daichi-Kudo/llm-advisor-mcp](https://github.com/Daichi-Kudo/llm-advisor-mcp) [![Daichi-Kudo/llm-advisor-mcp MCP server](https://glama.ai/mcp/servers/Daichi-Kudo/llm-advisor-mcp/badges/score.svg)](https://glama.ai/mcp/servers/Daichi-Kudo/llm-advisor-mcp) 📇 ☁️ 🍎 🪟 🐧 - Real-time LLM/VLM model comparison with benchmarks, pricing, and personalized recommendations from 5 data sources. No API key required.