"Information About Persistent Memory" matching MCP servers:

MCP server for Python build123d to help AIs develop and reason about 3D models and CAD

A general-purpose MCP server providing web search, persistent memory storage, and secure code execution capabilities. It enables AI agents to search the web, store and retrieve data, and run Python/JavaScript code in sandboxed environments.

NEXUS enhances AI coding agents with semantic code indexing, context engineering, change impact analysis, persistent memory, safe execution, and deterministic orchestration through 31 MCP tools.

Provides AI assistants with persistent memory of your project architecture, development history, and technical decisions, allowing them to give context-aware coding help without needing repeated explanations.

A boilerplate project for quickly developing Model Context Protocol (MCP) servers using TypeScript SDK. Includes example tools for calculations and greetings, plus system information resources.

Provides a secure, isolated JavaScript execution environment with configurable time and memory limits for safely running code from Claude.

Provides comprehensive documentation about AWS AgentCore framework to GenAI tools, enabling users to build production-ready AI agents with enterprise-grade security, observability, and scalability. Offers guidance on identity management, API integration, monitoring, code execution, memory storage, and tool integration for AI agents.

Provides Prolog logic programming integration for Claude via a Docker SWISH container, with persistent notebooks and cognitive architecture support.

Provides AI-driven development tools including file system operations, multi-language code analysis with tree-sitter, Git operations, code execution, and system information retrieval.

Enables large language models to access user geolocation information through EdgeOne Pages Functions using the Model Context Protocol.

Enables AI agents to perform low-level Windows process memory research, including process attachment, memory scanning, reading/writing, pointer chasing, remote code execution, and inline hooking via MCP tools and Lua scripting.

MCP server to provide Sketch layout information to AI coding agents like Cursor

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.

A localhost broker that allows multiple MCP clients to share a persistent xcrun mcpbridge connection to Xcode, enabling tool discovery and serialized calls.

Provides a stateful Django shell environment that allows AI assistants to execute Python code directly against Django projects. Maintains persistent session state between calls, enabling iterative exploration of models, queries, and debugging.

Provides a persistent Python REPL session as a tool for executing code, managing files, installing packages, and initializing projects via the MCP protocol.

Bridges Xcode's mcpbridge to MCP clients via SSE, maintaining a single persistent process to eliminate repeated authorization prompts.

A self-hosted MCP server providing Claude with an interactive Jupyter environment, including real kernels, persistent notebooks, and optional GPU offload to Google Colab.

Enables WebGPT to delegate durable coding-project tasks to a local Luna worker over MCP, managing sessions, tools, permissions, memory, and recovery while preserving at-most-once execution.

MCP server for Cheat Engine 7.6 that enables AI agents to perform memory scanning, reading/writing, process manipulation, debugging, and code injection via a Lua named pipe bridge.