Data Science & ML MCP 서버

Jupyter

Enables interaction with Jupyter notebooks running in a local JupyterLab environment using the Model Context Protocol (MCP).

Lindorm

Facilitates interaction with Alibaba Cloud's Lindorm multi-model NoSQL database through a suite of tools for data retrieval and management.

Binance

Enables large language models to access real-time and historical Bitcoin market data from Binance.

Gemini

Integrates Google's Gemini model with Claude using the Model Context Protocol (MCP).

Indian Stocks

Exposes Indian stock market data through a local Model Context Protocol (MCP) server.

Instagram by CData

Enables querying of live Instagram data from Large Language Models (LLMs) like Claude Desktop via a Model Context Protocol (MCP) interface.

DataHarpoon

Query raw data files and MCP-generated results using natural language or SQL.

Agentic Long-Term Memory

Empower AI chatbots with sophisticated long-term memory, comprehensive Notion workspace integration, and standardized tool communication via Model Context Protocol.

Crypto Stocks

Provides an MCP server to track real-time and historical data for major crypto-related stocks, aiding AI agents in investment analysis.

PolyNeural AI

Empowers AI agents with persistent memory by integrating with the PolyNeural.ai knowledge graph platform.

Liturgical Calendar

Exposes the Liturgical Calendar API as a structured toolset, enabling AI agents to interact with Catholic liturgical data.

Excel

Enables AI assistants to create, read, modify, and format Excel (.xlsx) spreadsheets using Python's openpyxl library, without requiring Microsoft Excel.

Nabu Nisaba

Enhances LLM agent capabilities with semantic code search, structural code views, and an intelligent workspace TUI for efficient context management.

Claude Context Enhanced

Provides enhanced semantic code search and deep context for AI coding agents with improved stability, faster synchronization, and reliable data persistence.

Google Maps

Connects AI agents to Google Maps Platform APIs for real-world location intelligence, directions, geocoding, and road network data.

BaseQL

Empowers AI agents with the context and tools to query Base chain data via Coinbase Developer Platform's SQL API using natural language.

jOOQ Documentation

Enables AI models to access and query jOOQ documentation, including SQL examples and best practices.

Lenny RAG

Provides hierarchical Retrieval-Augmented Generation (RAG) over Lenny Rachitsky podcast transcripts, enabling efficient retrieval of insights and examples.

YDRAG

Implements a Retrieval-Augmented Generation (RAG) system using local embedding generation via llama.cpp and DuckDB for vector storage.

Codeix

Provides fast semantic code search for AI agents, enabling them to find symbols, references, and callers across any codebase.