"Running queries in Apache Superset" matching MCP servers:

MCP server enabling AI agents to programmatically connect to and control Apache Superset instances, allowing users to manage dashboards, charts, databases, datasets, and run SQL queries through natural language interactions.

Persistent memory and pattern learning for AI coding assistants via MCP.

This read-only MCP Server allows you to connect to Apache Cassandra data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).

All In One Model Context Protocol: qdrant, google suite (gmail, calendar, ...), jira, gitlab, CLI, ...

Backend service implementing the Model Control Panel protocol that connects to Apache Doris databases, allowing users to execute SQL queries, manage metadata, and potentially leverage LLMs for tasks like natural language to SQL conversion.

Wraps Claude Code as a server using the Model Context Protocol (MCP), allowing teams to interact with Claude Code through a Slack bot interface.

Code-mode MCP server (docs_search + execute_code two-tool surface) backed by a unified capability manifest across three sandbox kernels (in-process node:vm, WASM via QuickJS / Pyodide / Wasmtime, and remote microVM via E2B / Cloudflare Sandbox). At N=30 tools the bootstrap-context cost drops to 13.6% of direct tool-use. Apache-2.0.

An MCP server that enables a supervising OpenAI Codex agent to delegate bounded implementation tasks to isolated worker threads with enforced file scopes and verification, optionally running in parallel git worktrees.

Enables analysis of bulk RNA-seq data using natural language queries, executing R and Python in a Docker container with automatic sample anonymization and privacy controls.

BeamScope gives AI coding agents access to your running BEAM application through a resilient TCP architecture that survives app restarts.

Enables running code against tests in an isolated sandbox to obtain PASS/FAIL verdicts with signed, offline-checkable certificates, and generating verified code with attached certificates after execution against derived tests.

Enables MCP clients to submit long-running jobs that are executed safely in isolated child processes with a durable SQLite queue, configurable timeouts, retries with backoff, and backpressure.

A lightweight framework for building and running Model Context Protocol (MCP) servers using FastMCP, providing tools for development, debugging, and server management.

Enables agents to interact with a running Roblox game client, execute Lua code, inspect scripts, spy on remotes, and more.

Runs AI-generated code in secure Firecracker microVMs with opt-in network policy enforcement, PII scanning, prompt injection defense, and audit logging. Exposes MCP tools for running commands, managing files, and the full sandbox lifecycle.

Enables coding assistants to access Perplexity AI for quick fact-checking and in-depth research. Provides two tools: lookup for fast documentation queries and answer for comprehensive research with recommendations.

Auto-discovers running marimo notebooks and exposes tools for reading, editing, and running cells via MCP, supporting both HTTP and VS Code backends.

Enables autonomous task execution by dynamically searching APIs, generating Python tools, and running them on-demand, with built-in web search, scraping, and file operations.

A Model Context Protocol server that enables running and managing long-running background tasks (like development servers, builds) from within Claude Desktop or other MCP-compatible clients.

An enhanced Model Context Protocol (MCP) server that allows running Claude Code in one-shot mode with permissions bypassed automatically, featuring advanced task