"A server providing context 7" matching MCP servers:

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

Enables compatible MCP AI tools to read, write, design windows, and run programs in the E-Language IDE.

A self-hosted MCP server that enables AI coding agents to read, edit, search, and run code in local projects with human review loops and policy controls.

Allows LLMs to execute Wolfram Language code in a secure, session-based environment by providing an interface to interact with a Wolfram Mathematica kernel.

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.

An MCP server that keeps raw tool output out of the context window by sandboxing and compressing results (about 98% reduction), persisting file edits, git operations, tasks and decisions in SQLite with BM25 retrieval so the agent resumes after compaction, and enforcing routing across 17 platforms via MCP and hooks. It also encourages the model to write scripts that compute answers and log only results instead of reading large data into context.

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 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.

Context Mode is an MCP server that reduces context window waste by sandboxing data-heavy tools, tracking session state in SQLite, and promoting code-based analysis over raw data reads, achieving up to 98% context savings.

An MCP server that preserves LLM context by intercepting large data outputs and returning only concise summaries or relevant sections. It enables efficient sandboxed code execution, file processing, and documentation indexing across multiple programming languages and authenticated CLIs.

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.

Enables AI agents to write, validate, and render high-quality PostScript by providing operator lookup, vetted PSlib fragments, cited reference search, and Ghostscript-based checking.

Enables AI assistants to create and modify Google Apps Script projects, manage versions and deployments, run functions, and inspect execution history through natural language.

Enables AI assistants to read, edit, and execute Jupyter notebook files (.ipynb) with live kernel output, without requiring JupyterLab.

Gives AI assistants a genuine Borland Turbo C 3.0 toolchain via MCP, enabling compile and run of real 16-bit DOS C programs with diagnostics and classic examples.

A bridge server that provides access to an Odoo shell environment, allowing execution of Python code within an Odoo database context for model introspection and database operations.

Enables Gemini-powered multimodal analysis (video, audio, image, documents), Google search, and code execution via the API易 service. Supports Docker deployment and flexible configuration.

A professional implementation of a Model Context Protocol server that enables integration between DaVinci Resolve video editing software and AI assistants like Claude Desktop or Cursor.

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 exposes Python debugging tools backed by debugpy, providing a focused debugging surface for local scripts.

A production-grade MCP server providing a persistent Python REPL with multi-session support, sandboxing, and timeout protection, enabling LLM agents to execute Python code across multiple turns with variables that persist between calls.

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

A hub server that connects to and manages other MCP (Model Context Protocol) servers.

A Model Context Protocol server that allows Claude Desktop to manage and execute tasks in a queue-based system, supporting planning, execution, and completion phases.

A Model Context Protocol server that provides AI assistants with access to ReactBits.dev components - a collection of 135+ animated React components for creative developers.

A Model Context Protocol server that enables interaction with PostgreSQL databases for analyzing setups, debugging issues, managing schemas, migrating data, and monitoring performance.

A local Model Context Protocol server that allows LLMs to securely execute shell commands on remote Linux and Windows systems via SSH connections.

An MCP server that enables processing of massive datasets up to 10M+ tokens using a recursive language model pattern for strategic chunking and analysis. It automates sub-queries and result aggregation using free local inference via Ollama or the Claude API to handle context beyond standard prompt limits.

Enables basic arithmetic operations (addition, subtraction, multiplication, division) with 64-bit precision and matrix multiplication capabilities. Provides mathematical computation tools for AI assistants through the Model Context Protocol.