"Historical Data for SOXL" matching MCP servers:

A Windows-optimized server providing universal data analytics for JSON and CSV files through over 32 tools including schema discovery and interactive visualizations. It is specifically designed for seamless integration with Claude Desktop on Windows.

Enables Codex to consult Claude Code for a second opinion through a local stdio MCP server, exposing the ask_claude tool for text-only reviews and recommendations using existing Claude Code authentication. Codex can request findings and tradeoff analysis without allowing Claude to edit files or run commands.

A fully autonomous patent data marketplace for AI agents, providing highly structured JSON datasets with strategic insights. Supports instant M2M transactions via ROSE on the Oasis Network.

Enables AI assistants to generate realistic, synthetic test data on demand, including valid PESELs, NIPs, addresses, and more across 27 EU countries, through two tools: list_generators and generate.

Integrates Google's Gemini AI models into Claude Code and other MCP clients to provide second opinions, code comparisons, and token counting. It supports streaming responses and multi-turn conversations directly within your existing AI development workflow.

Use Codex as a subagent inside Claude Code: async dispatch into a long-lived codex app-server, results pushed back into the Claude session automatically, steer/interrupt mid-task, and Codex's built-in code review.

A basic MCP server setup guide demonstrating how to configure and run Python-based MCP servers with integration examples for Bright Data web scraping and Apify Actors for product data collection.

A Model Context Protocol server that extracts embedded data (such as i18n translations or key/value configurations) from TypeScript/JavaScript source code into structured JSON configuration files.

Odds are, most of what you want to build is already open source. Tell your AI agent what you're making, and it finds it: which repos to use as they are, which to adapt, and what's left for you to write. Every repo it names is real, licensed for your use or flagged, and checked live.

Enables agents to explore a database safely and read-only through three tools — list_tables, describe_table, and run_query — served over stdio. Queries are guarded by lexical validation, a capped LIMIT, a read-only SQLite connection, and an authorizer with a timeout.

Provides AI agents with data validation, transformation, and normalization capabilities, including JSON schema validation, CSV processing, data normalization, text cleaning, and dataset merging.

Lets AI agents and developers inspect and query local MySQL, Redis, and MongoDB instances over STDIO or authenticated loopback HTTP, with read-only defaults and allowlisted non-production writes that require explicit opt-in. Production connections always reject writes, and database-enforced read-only accounts are recommended.

Provides Large Language Models with real-time access to the latest documentation for Python libraries like Langchain, LlamaIndex, and OpenAI, enabling accurate and up-to-date code suggestions.

An MCP server for interacting with SQL Server databases that enables schema inspection, record counting, and paginated data retrieval. It provides tools to explore table structures and fetch specific records while enforcing safety limits on data volume.

Provides tools for interacting with SQL Server databases, enabling users to retrieve paginated table data, inspect schemas, and count records. It features enforced pagination and secure configuration options to manage database operations efficiently through natural language.

Enables secure access to Oracle databases with fine-grained access control, supporting multiple databases simultaneously with configurable access modes (readonly/readwrite/full) and table-level permissions for safe query execution and data management.

An MCP server that allows AI models to create data visualizations using Vega-Lite syntax by providing tools to save data tables and generate visualizations from them.

A TypeScript-based server to interact with ArangoDB using the Model Context Protocol, enabling database operations and integration with tools like Claude and VSCode extensions for streamlined data management.

Enables loading and statistical analysis of .xlsx and .csv files with visualization capabilities using matplotlib and plotly to generate various graphs and charts.

A sovereign, high-speed, local-first Big Data Ingestion, Filtering, and Analytical Pipeline Orchestrator.