Discover our curated collection of MCP servers for data science & ml. Browse 9120 servers and find the perfect MCPs for your needs.
Enables AI assistants to access and interact with real-time transport alerts from Transport for NSW.
Enables AI assistants to perform intelligent searches using the Baidu Wenxin API.
Interfaces with the Google Analytics Data API using a Model Context Protocol (MCP) server.
Connects QGIS to Claude AI, enabling prompt-assisted project creation, layer manipulation, and code execution through the Model Context Protocol (MCP).
Tracks newly created liquidity pools on Uniswap across nine blockchain networks in real-time.
Enables AI models to interact with SQLite databases by executing SQL queries and managing schemas.
Generates text differences between two strings using Python's `difflib` in Unified diff format.
Enables long-term memory storage for LLM conversations using Redis Graph as a backend.
Manages project-specific and knowledge graph-based memory for LLMs and agents.
Enables searching of vectorized Cursor IDE chat history using LanceDB and Ollama through an API service.
Fetches or generates YouTube video transcripts using AI, prioritizing official transcripts and falling back to local Whisper transcription.
Generates AI images using the Doubao Seedream 4.0 model, seamlessly integrating with Claude Code via Model Context Protocol.
Provides intelligent, persistent memory for AI assistants like Claude Code via a self-hosted Model Context Protocol (MCP) server.
Enables AI assistants to leverage local knowledge through semantic search over multi-format documents, supported by vector storage and OCR.
Enables large language models to reliably control Blender for 3D modeling tasks.
Enables AI assistants to interact with ComfyUI for generating images, video, audio, and 3D content.
Provides a Model Context Protocol server for VictoriaMetrics Anomaly Detection, enabling AI assistants to interact with its REST API.
Provides drop-in integrations, tools, and an MCP server to connect various AI agent frameworks with the Agoragentic agent-to-agent marketplace.
Establishes a universal context and memory layer for AI agents, preventing repeat mistakes by capturing feedback, generating prevention rules, and injecting relevant historical context.
Prepares users for the Claude Certified Architect exam with 390 questions, spaced repetition, and zero sycophancy.
Scroll for more results...