"A tool for sending emails" matching MCP servers:

MCP server that gives AI agents isolated, named Linux computers with stable IDs and lifecycle control. Supports multiple backends like Docker, Fly Machines, Modal, and E2B, with a dashboard for managing sandboxes.

Composes arbitrary MCP tools using JavaScript, enabling discovery, composition, and execution of other MCP servers through a single 'exec' tool.

Run DeepSeek as a real sub-agent inside Claude Code / Codex CLI — not just a single LLM call. DeepSeek gets its own 7-tool agent loop (Read/Write/Edit/Bash/Glob/Grep/NotebookEdit) inside a sandboxed workspace.

A Model Context Protocol (MCP) server that wraps the dbt CLI tool, enabling AI coding agents to interact with dbt projects through standardized MCP tools. Developed by Mammoth Growth.

Lets your AI find the open-source tool it needs on GitHub and install it as an MCP tool, in a sandbox, after you approve. Reads only the folders you grant; no network unless allowed.

A Model Context Protocol implementation that plays sound effects (completion, error, notification) for Cursor AI and other MCP-compatible environments, providing audio feedback for a more interactive coding experience.

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 agents to accomplish multi-step work by writing a single sandboxed JavaScript program that drives shell, filesystem, HTTP, and every tool of any configured MCP server, returning only a small summary instead of raw JSON. This collapses dozens of advertised tool schemas into one tool, cutting per-request context by roughly 26× while keeping disabled upstream servers reachable.

An MCP server for Task Trellis that provides tools for AI coding agents to manage tasks, currently featuring a simple hello_world demonstration tool.

Provides agents with real Linux VMs to run commands, manage files, expose ports, and track costs, all through an ephemeral sandbox service.

Enables Windows users to connect Antigravity CLI as an MCP subagent for coding tasks such as file reading, code execution, edits, and terminal commands, with model selection, conversation continuity, and streaming progress.

A minimal MCP server that exposes a single bash tool to execute commands inside a devcontainer, returning real output and exit codes.

A tool that enables AI assistants to conversationally scaffold, build, and publish Python MCP servers to PyPI. It automates the entire development lifecycle, including package naming, tool scaffolding, GitHub repository setup, and package publishing.

Enables Claude Code to perform programmatic tool calling by executing Python scripts that interact with multiple MCP servers in a single round-trip. This reduces latency and token consumption by keeping intermediate tool results within the local Python runtime instead of the conversation context.

Lightweight MCP server for After Effects that enables Cursor Agent to execute ExtendScript code inside AE via a single tool, similar to Blender MCP.

Gives LLM agents spatial awareness inside Autodesk Maya, enabling scene inspection and measurement, aesthetic and engineering audits, camera planning, checkpoint/rollback safety, asset import, and viewport or render previews. Agents can also execute arbitrary Python in Maya to build and verify 3D scenes against engineering rules instead of writing blind.

Remote-control Unity Editor from any AI IDE via file-based IPC — 62 tools, zero dependencies

Provides direct, unsandboxed local machine access via filesystem, Python, Node.js, and shell commands for MCP agents.

An MCP server that provides a persistent sandbox for AI coding agents to explore codebases server-side, returning only compact summaries to reduce context consumption.

Chain of Draft Server is a powerful AI-driven tool that helps developers make better decisions through systematic, iterative refinement of thoughts and designs. It integrates seamlessly with popular AI agents and provides a structured approach to reasoning, API design, architecture decisions, code r

Enables execution of TypeScript code to call MCP tools instead of direct tool calls, reducing token usage by up to 98% while orchestrating complex multi-tool workflows through secure sandboxed code execution.

Connects Claude Desktop to a running FreeCAD instance, enabling document management, part creation and editing, direct Python execution, parts library insertion, FEM analysis, and 3D view screenshots.

Bridges Claude Desktop to local Windows 10 development environments to enable repository reading, documentation searching, and isolated code execution. It provides a secure interface for running allowlisted terminal commands and scripts directly through natural language.

A proxy MCP server that wraps MCP-for-Unity, correcting transport inaccuracies and restricting tool usage for reliable Unity integration.

Orchestrates multiple MCP servers through a Deno sandbox, reducing token usage by 99.7% by processing tool calls and returning only compact results.

Agent development tool-kit

Enables interactive Python execution with a persistent IPython kernel through MCP, retaining namespace state and providing structured output logs for agent and tool integrations.

Provides a ready-to-run stdio server scaffold that agents can launch via npx without installing anything, bundled into a single file with an example tool, strict tool-schema checks, tests, and bilingual documentation. It gives developers a consistent foundation for building, validating, and shipping new MCP servers that agent-kit can execute directly.

MCP server wrapping DeepSeek's agent harness tools into minimal/standard modes, enabling persistent shell, file editing, search, job management, and more via natural language.

Guides problem-solving by breaking down complex problems into steps and recommending appropriate MCP tools for each stage, with confidence scores and rationales for tool suggestions.