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Code Execution

Code execution servers. Allow LLMs to execute code in a secure environment, e.g. for coding agents.

MCP ServersBrowse all →

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    Enables AI agents to interact with the Execute.run bot API for managing Shell balances, transferring funds, and executing LLM requests. It provides tools for identity verification, transaction tracking, and performing compute tasks through the Execute.run platform.
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    The Fibery MCP server provides integration between Fibery and any LLM provider supporting the MCP protocol (e.g., Claude for Desktop), allowing you to explore Fibery Workspace Schema, query databases, create and update entities using natural language.
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    MIT
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    Enables execution of SAS code on SAS Viya compute environments with OAuth2 authentication. Allows users to run SAS programs and retrieve execution results including logs and output through the Model Context Protocol.
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    Apache 2.0
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    A Model Context Protocol server implementation that enables AI assistants to securely interact with GreptimeDB, allowing them to explore database schema, read data, and execute SQL queries through a controlled interface.
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    MIT
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    Enables deterministic verification for AI assistants by executing Python code that uses symbolic engines like SymPy and Z3 for math, logic, and code analysis.
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    Apache 2.0
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    MCP server that gives AI agents full access to ITASCA PFC - browse documentation, run simulations, capture plots, all through natural conversation. Built on the Model Context Protocol, pfc-mcp turns any MCP-compatible AI client (Claude Code, Codex CLI, Gemini CLI, OpenCode, toyoura-nagisa, etc.) into a PFC co-pilot that can look up commands, execute scripts, monitor long-running simulations.
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    MIT
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    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.
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    Apache 2.0
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    A TypeScript-based MCP server that provides full CRUD operations for Requestly rules and groups, enabling integration with VS Code and other MCP clients through a stdio interface.
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    MIT
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    Enables code agents to interact with Netlify services through the Model Context Protocol, allowing them to create, build, deploy, and manage Netlify resources using natural language prompts.
    Last updated
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    ISC
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    Backtest PineScript v6 strategies locally from your AI agent: transpiles Pine to C++ and runs it on the deterministic, TradingView-validated PineForge engine via Docker. Tools for single backtests, parameter-grid sweeps, and Binance OHLCV fetch — no API key, data never leaves your machine.
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    Provides tools to search and execute Code Ocean capsules and pipelines while managing platform data assets. It enables users to interact with Code Ocean's computational resources and scientific workflows directly through natural language interfaces.
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    This server enables natural language interaction between a user and their Kuzu databases using clients like Claude Desktop or Cursor, allowing LLMs to retrieve the database schema, execute Cypher queries, create nodes, and establish relationships in the graph database.
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    MIT
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    A Model Context Protocol server that enables automated optimization and analysis using Optuna, allowing LLMs to perform hyperparameter optimization and interactively analyze optimization results via chat interfaces.
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    MIT
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    A secure shell command execution server implementing the Model Context Protocol (MCP). This server allows remote execution of whitelisted shell commands with support for stdin input.
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    MIT
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    Allows LLMs to execute Python code in a specified Conda environment, enabling access to necessary libraries and dependencies for efficient code execution.
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    MIT

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