A Python-based framework that connects LLMs to executable Python code via MCP User Defined Functions, allowing data scientists to extend models. Directly relevant as a framework for building extensible MCP servers.
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MCP server for running Python code in a secure sandbox environment via MCP tool calls, tailored for LLM and coding agents.
A Python-based MCP server for querying OpenAI models directly from Claude or other clients using the Model Context Protocol.
MCP servers providing a secure, sandboxed environment for executing Kali Linux security tools like nmap, objdump, and wireshark for network analysis and vulnerability scanning.
Implements CEDARScript, a SQL-like language, as an MCP server for code manipulation, showcasing the adaptability of MCP servers for language and code-based tasks.
A command line MCP Server offering secure execution and customizable security policies. Directly relevant to MCP server implementations for command line environments.
A sandboxed MCP server enabling secure, multi-language code execution with resource limits and network restrictions. Direct example of an MCP server providing isolated code execution environments.
Fused MCP is a Python-based framework designed to connect Large Language Models (LLMs), such as Claude, to executable Python code via MCP (Model Code Proxy) User Defined Functions (UDFs). It allows data scientists to extend and enhance models by enabling LLMs to make HTTP requests and interact with APIs and executable Python functions. The framework facilitates building and running extensible MCP servers on local machines, enabling seamless integration between LLMs and custom code.
uv for package management).No pricing information is provided; the repository appears to be open-source and free to use.
code-execution, python, llm-integration, mcp
code-execution-automation-mcp-servers