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705,235 tools. Updated 2026-10-26 13:21

"A tool for running code in a REPL-like environment" matching MCP tools:

  • Run one command in a running container and return stdout, stderr, and exit code. Ideal for one-off tasks; no TTY or stdin.
    Apache 2.0
    Destructive
  • Run commands inside a running Docker container with configurable user, working directory, environment, TTY, and detach options. Returns exit code and output for straightforward automation.
    MIT
  • Execute a command in a durable cloud environment to get its exit code and output, resuming a paused environment. Pass argv as a list; set cwd, env, or timeout as needed.
    MIT
    Destructive
  • Sets up a new Translation Hosting environment in SimpleLocalize for organizing and publishing translations. Provide a unique key, name, and color to create the environment.
    Apache 2.0

Matching MCP Servers

  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables AI agents to call tools through a security gateway that intercepts requests, enforces deterministic policy and risk checks, blocks or escalates high-risk actions for human approval, and keeps tool credentials and audit logs protected.
    1
    MIT

Matching MCP Connectors

  • Indicative UK skip hire prices by town, council skip permit rules and skip size recommendations.

  • AI agents hire a human to observe, log or film on site. Typed results, feasibility before payment.

  • Execute Python code in a sandboxed environment with JAX and model fitting libraries, using export() to return results. Use for running generated or custom model fitting code.
    MIT
  • Evaluate Julia code in a persistent REPL session. State is preserved across calls, reducing startup costs and keeping variables alive.
    MIT
  • Run Python code synchronously inside the running YADE process to query or modify simulation state in real time, including during active simulations.
    MIT
  • Reports the running Electron app's environment: runtime versions, app name and paths, packaged and code-signature status, active transport, and capability matrix. Target a specific session by passing sessionId.
    MIT
  • Execute Python code directly in an Odoo environment to access models, modify data, and perform database operations with persistent state between calls.
    MIT
  • Execute Python code within a project's virtual environment to access its installed dependencies. Each call runs in a fresh interpreter subprocess, ensuring isolation.
    MIT
  • Run Python code in a persistent REPL that retains variables and imports across calls, supports top-level await, and calls MCP tools for batch automation.
    MIT
  • Generate a Solana wallet locally for staking. Create keypair in your environment, fund, then stake with walletAddress and secretKey in one call.
    MIT
  • Execute shell commands within a REPL environment, returning structured output with exit code and stdout. Supports stdin piping, timeout, and custom environment variables.
    MIT
  • Boot a stopped environment and wait until SSH responds. Does nothing if already running; errors if the environment is missing.
    Apache 2.0
  • Execute shell, REPL, or bootloader commands and automatically wait for the prompt, returning structured results with output, exit code, and timeout.
    MIT
  • Start a persistent session for code execution. Python/Node gain stateful REPL preserving variables and imports; other languages receive a persistent workspace directory. Returns session ID.
    Apache 2.0
  • Stop a running session by terminating its REPL worker and deleting its workspace, with an option to keep saved snapshots.
    Apache 2.0
    Destructive