A Model Context Protocol server that extracts and analyzes Python code structures, focusing on import/export relationships between files to help LLMs understand code context.
Python Docs MCP Server gives AI coding agents local access to the official Python standard library docs. It can look up docs by Python version, return specific sections, and keep answers compact for clients like Claude Desktop, Cursor, and Codex. It runs without API keys or a hosted service.
Paybond Kit for Python is the PyPI package for tenant-bound Paybond integrations and delegated agent spend controls. It opens hosted Gateway sessions, verifies capability tokens, authorizes tool-call spend, signs intent and evidence payloads, uses Stripe Connect, Stripe ACH Direct Debit, or x402 / USDC-on-Base settlement rails, reads tenant-scoped Signal, fraud, ledger, protocol, and A2A data, and
A streamlined foundation for building Model Context Protocol servers in Python, designed to make AI-assisted development of MCP tools easier and more efficient.
An enhanced sequential thinking tool optimized for programming tasks that helps break down complex coding problems into structured, self-auditing thought steps with branching and revision capabilities.
An MCP server that gives orchestrator agents fine-grained control over interactive Claude Code sessions running inside tmux, enabling mid-session steering, interruption, and token-efficient result extraction.
Allows LLMs to execute Python code in a specified Conda environment, enabling access to necessary libraries and dependencies for efficient code execution.
MCP server for GitHub code retrieval and reuse, using SQLite+FTS5 indexing and search history to enable search-first, requirements-refined code search from GitHub repositories.
Provides sandboxed code execution for AI agents with support for Python, JavaScript, and shell commands. Includes comprehensive safety features like destructive pattern blocking, timeout protection, and restricted file access for secure production use.
Enables AI-assisted code review with bias mitigation strategies through cross-model evaluation and bias-aware prompting. Detects AI-generated code from commit authors and provides structured reviews with security, performance, and maintainability analysis.
Enables AI assistants to programmatically control Adobe Photoshop on Windows to create documents, manipulate layers, and manage image adjustments. It provides a bridge between the Model Context Protocol and the Photoshop Python API for automated graphic design workflows.
Ephemeral MicroVM-isolated code execution for AI agents. Run Python, Node, or bash — fresh hardware-isolated VM per call, hard-purged after. No state persists between calls.