"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.

Enables agents to synthesize typed MCP tool schemas at runtime, validate Python ASTs for unsafe imports, compile sandboxed callable handlers, and hot-plug them into an active MCP runtime. It provides a zero-dependency, standard-library-only MCP server for safe just-in-time tool creation and execution.

Enables agents to dynamically generate typed MCP tool schemas, validate Python execution ASTs against unsafe imports, and hot-plug sandboxed callable handlers into an active runtime. This allows new tools to be synthesized and safely executed on demand.

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

Enables running one Codex CLI task at a time in an isolated temporary folder, returning Codex's answer and a manifest of produced files for manual review and selective copying.

Enables AI agents to drive a running Roblox Studio in real time over a single WebSocket, executing whole Luau programs, installing in-engine controllers, hot-patching scripts during live playtests, and receiving errors, assertions and other events as pushes. It also reaches Roblox Open Cloud for the open place and answers visual questions via a vision sidecar, exposing all of this through nine MCP tools.

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.

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.

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 running Python 2 IPython sessions via MCP, with tools to install dependencies, start/stop sessions, execute code, and get tab completion.

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.

Enables any LLM to drive your local Codex CLI in a sandboxed workspace, running coding tasks and generating images without needing an API key.

Gives any MCP client the same sandboxed coding-agent toolset — searching, viewing and editing files, running tests, and executing shell commands — each session in its own locked-down, network-isolated Docker container. Enables an MCP-capable assistant to diagnose and fix failing tests without touching the host machine.

Enables local agents to connect to and interact with Google Colab sessions running in the browser.

An MCP server that enables coding agents to execute and manage long-running shell commands asynchronously with capabilities for process monitoring, interaction, and lifecycle management.

Enables MCP clients to control the local Codex CLI, including running and resuming agent sessions, forking, code review, applying diffs, and generating images, with background execution for long-running tasks.

An MCP server that lets host-side Claude Cowork dispatch work into Claude Code running inside your devcontainer over stdio.

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.

Enables AI agents to execute Lua code, inspect scripts, spy on remotes, and interact with a running Roblox game client through an MCP interface.

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 AI assistants to execute designer-confirmed code and reusable capability packs inside a running Autodesk Revit instance.

Enables agents to run and manage SageMath computations through a persistent kernel over stdio, including executing code, polling long-running jobs, interrupting or resetting sessions, running files, and driving notebooks.

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.