Enables interactive Python execution with a persistent IPython kernel through MCP, retaining namespace state and providing structured output logs for agent and tool integrations.
A persistent Python REPL MCP server for AI agents with stateful execution, real timeouts, crash isolation, and an MCP bridge to call other tools in the project.
Provides persistent IPython shell sessions per conversation with DataFrame-centric architecture, enabling stateful data analysis, CLI tool execution, and integration of external MCP servers within the same workspace context.
Enables LLM clients to run Python code in a persistent, user-selected interpreter via MCP, with tools for data loading, summaries, regressions, diagnostics, and plotting, while keeping sessions alive between calls and isolating crashes.
Provides a persistent Jupyter kernel for executing code, inspecting variables and dataframes, and checking SQL query plans, enabling agents to work with stateful Python sessions.
MCP server giving agents a persistent IPython workbench and a brokered RLM engine for durable, stateful computation. Offers 30 tools for bounded model calls, artifacts, and receipts with host-owned authority.