"Python runner with streamable HTTP support" matching MCP servers:

Demonstrates how to create a simple MCP server with streamable HTTP transport, featuring tools, prompts, and resources.

A minimal MCP server running in a container that connects to GitHub Copilot over stateless, JSON-only Streamable HTTP, exposing echo and server_info tools.

Execute Python code via subprocess with timeout and error handling, returning stdout, stderr, and exit code.

Enables AI assistants to execute Python functions and system commands via Streamable HTTP, including bash, Python code execution, file operations, and text searching.

A TypeScript-based MCP server that implements a simple note-taking system using low-level server components and streamable HTTP. It enables users to create, store, and summarize text notes through a set of tools, resources, and specialized prompts.

Enables LLMs to make HTTP requests with OAuth2, session cookies, retry logic, and cURL command generation, while providing security features like SSRF protection and TLS enforcement.

Exposes MAID Runner validation tools (validate, snapshot, test) as MCP tools, resources, and prompts for AI agents like Claude Code and Aider, enabling seamless integration with AI development workflows.

An MCP server that exposes a sandboxed task runner protocol to any MCP client, enabling evidence-protected task execution, exit protocol reading, and autopsy reports.

Enables AI agents to run, monitor, and manage Cypress tests with features like test discovery, screenshot handling, and multi-browser support.

Enables AI assistants to work with Chapel code, including compiling, linting, and accessing educational primers.

Enables running multiple bash steps in one MCP call with per-step contains, notContains, or regex expectations, reporting process failures and expectation failures separately. Also provides async status polling, cancellation, guarded commands, file edits, grep, sqlite reads, and artifact retrieval.

JSON-driven E2E test runner for AI agents. Define browser tests as JSON action arrays and run them in parallel against a Chrome pool (browserless/chrome) with 28+ built-in actions, visual verification, network debugging, and flaky test detection.

Simple MCP Runner makes it effortless to safely expose system commands to language models via a lightweight MCP server—all configurable with a clean, minimal YAML file and zero boilerplate.

Enables AI clients to list, inspect, triage, and update support tickets via MCP tools, with a mocked dataset designed for swapping in real ticket sources later.

Enables running configurable Prompt-as-Code tasks across multiple scenarios through local Codex, with MCP tools to list scenarios, execute standard task files, and validate task definitions.

A Windows-only headless LLM task automation engine that executes natural language tasks on schedule and delivers results through configured channels, built as an MCP server with 7 tools for task management.

Enables AI harnesses to maintain a persistent memory layer backed by a local SQLite file, providing MCP tools to add, search, deprecate, and synchronize facts without deleting history.

Provides an HTTP API for Claude Code using a native MCP channel to enable stable message exchange without terminal screen-scraping. It allows users to programmatically send messages, retrieve conversation history, and stream real-time events via standard web protocols.

HTTP Inspector MCP Server enables sending arbitrary HTTP requests, viewing history via a web panel, and taking screenshots of the panel for AI penetration testing workflows.

MCP server for generating negative-space print supports for 3D models (STL/OBJ/STEP) via the negative.support API.