"Netflix Media Control Protocol (MCP) or Management Platform" matching MCP servers:

A local, read-only MCP server (plus CLI) over your own stock/ETF transaction log. A deterministic core computes drawdown-first risk with bootstrap confidence intervals and validates targets with walk-forward verdicts. The assistant narrates, but the number fence makes it structurally impossible for the model to produce a figure.

Connects to wetlab protocol resources such as protocols.io, enabling users to access and manage experimental protocols via natural language.

Enables AI assistants to interact with the Open Targets Platform API to search and retrieve comprehensive data about target-disease associations, drugs, genes, and drug discovery information through GraphQL queries.

A read-only MCP server for searching control science and engineering papers via OpenAlex, limited to core journals in the field.

Provides tools to research crypto trading strategies via backtesting, walk-forward validation, and paper trading, with a deflated-Sharpe overfitting check. Enables natural-language-driven analysis and interpretation of strategy performance.

Enables AI assistants to directly access quant research knowledge, including factor libraries, strategy backtesting, and research reports, through the MCP protocol.

A Python MCP server for querying grant applications and previewing or committing scoped reviewer reassignments.

Enables querying and retrieving materials data from the Materials Project via MCP tools, supporting search, lookup, comparison, and export.

Enables Claude to access and analyze your paid media campaign data, team structure, performance metrics, and reporting templates, so it can answer questions and assist with analysis directly in your workflow.

Provides AI assistants with real-time web search, reasoning, and research capabilities through Perplexity's Sonar models and Search API. Supports quick searches, deep research, advanced reasoning, and direct web search with ranked results.

An MCP server that integrates AI retrievals with NASA's Common Metadata Repository (CMR), allowing users to search NASA's catalog of Earth science datasets through natural language queries.

Access to many public datasets right from your LLM application.

Enables AI agents to resolve Japanese food names to nutrition facts per 100g based on official Japanese food composition data.

Provides read access to campaign performance data from Google Ads, Meta Ads, and TikTok Ads via live API calls, enabling AI assistants to analyze and audit advertising campaigns.

The Materials Project MCP Server is server that provides programmatic access to the Materials Project database. It enables LLMs, to search, analyze, and retrieve up to date materials science data.

A Python implementation of the Model Context Protocol (MCP) server that enables searching and extracting information from arXiv papers, designed to be extensible with additional MCP tools.

MCP server for Taiwan's agricultural wholesale market real-time price data, providing 6 tools to search products and query trade data at daily, weekly, monthly, yearly granularities, plus cross-market comparisons.

Provides AI assistants with access to Lumenore's analytics capabilities, enabling natural language queries for data insights, advanced analytics (trends, predictions, correlations, outliers), and real-time data processing with zero persistent storage.

Server for managing academic literature with structured note-taking and organization, designed for seamless interaction with Claude. Built with SQLite for simplicity and portability.

An MCP server that provides controlled read/write tools for managing local-first research memory in an Obsidian vault, enabling AI agents to maintain project context across sessions.