Discover our curated collection of MCP servers for data science & ml. Browse 6480servers and find the perfect MCPs for your needs.
Builds a fully serverless LLM agent that dynamically manages memory and context using AWS Bedrock, Lambda-hosted MCP servers, and S3 Vectors.
Exposes a static library of Claude Code Skills to dynamic AI agents via the Model Context Protocol.
Provides comprehensive documentation and insights for AWS AgentCore to GenAI tools, enabling the development of production-ready AI agents.
Provides read-only access to local Beeper chat conversations on macOS for Model Context Protocol (MCP) clients.
Processes XLS and CSV files using a Java-based server.
Enables the deployment of a Model Context Protocol (MCP) server on Cloudflare Workers without requiring authentication.
Analyzes and sorts resumes using AI to efficiently match candidates with job descriptions.
Provides a cloud-hosted Model Context Protocol (MCP) server for Alibaba's Qwen models, optimized for Chinese language and coding AI inference on the Apify platform.
Evaluates functionality using the Claude language model.
Provides seamless access to GA4GH Task Execution Service (TES) functionality, empowering AI assistants and LLMs to manage computational tasks.
Enables Large Language Models (LLMs) to perform accurate mathematical computations by acting as an external coprocessor.
Provides a standardized interface for interacting with the SmartSuite API, enabling human-readable field names and AI-guided operations.
Enables connecting to Reckon Accounts Hosted data from LLMs like Claude Desktop for natural language querying.
Manages and queries a Pinecone vector database for similarity search, semantic search, and RAG applications.
Delivers Stoic philosophy quotes augmented with AI-driven insights to enhance understanding and developer well-being.
Provides AI assistants and applications seamless access to rigorous particle physics data from the Particle Data Group (PDG).
Efficiently search and retrieve specific code segments across multiple projects, empowering AI agents with relevant context.
Exposes Swagger/OpenAPI endpoints through the Model Context Protocol for AI agent accessibility.
Connects Large Language Models (LLMs) to live Outreach.io data via a Model Context Protocol (MCP) interface, enabling natural language queries without SQL.
Generates image assets using Google Gemini AI, offering advanced control over output format, transparency, and resizing.
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