Your personal AI runtime, local-first. Patchwork OS gives any AI model a consistent set of tools, YAML recipes, a delegation policy with approval queue, and a durable trace memory — all on your machine, all under your policy.

x64dbg-MCP Server is a native MCP (Model Context Protocol) plugin for x64dbg that exposes the debugger's full functionality over HTTP. Connect any MCP-compatible AI assistant and control x64dbg programmatically: set breakpoints, step through code, read memory, dump registers, and more. Built with Zig — zero dependencies, single-binary output, cros

Unlimited memory for OpenClaw

Deploy files, sites, and Dockerfile apps to live URLs + private drives for agent memory.

🚀 Apache RocketMQ built in Rust 🦀 — faster, safer, and more memory-efficient. Powering high-performance messaging for the AI era, with AI Agent, MCP, and AI-SRE capabilities.

Documentation memory for AI coding agents—route project knowledge, reduce repeated context loading, and validate living Markdown docs.

Open-source self-improving QA agent for software teams. A test harness with memory. Write tests in natural language for web and mobile. agent-qa learns from every run, adapts to UI changes, and catches regressions before you ship.

🔥 Java enterprise application development framework for full scenario: Restrained, Efficient, Open, Ecologicalll!!! 700% higher concurrency 50% memory savings Startup is 10 times faster. Packing 90% smaller; Compatible with java8 ~ java26; Supports LTS. (Replaceable spring)

Project memory and workflows for Claude Code and Codex. Keep stories, plans, handovers, and review evidence in your repo. Resume across sessions and follow progress in the Mac app.

Enables AI assistants to read and write a local-first SQLite memory vault from inside a chat — orienting on inherited context, searching and fetching past decisions and notes, wandering linked memories, and recording new ones on demand. All data stays on the user's machine, shared across local and cloud tools via MCP.

Provides AI coding tools with one local SQLite memory and rules store they can read over MCP, REST or the CLI, so facts, sessions and goals persist across sessions and shared rules are written into each tool's own instruction file. Runs entirely on your machine with no account, telemetry or network calls by default.

Enables multiple DSH plugin/session agents to share trust-labeled Markdown memory and query on-demand cross-plugin digests, with write access isolated per channel so untrusted third-party content cannot become instructions.

Free, open-source memory for Claude Code. Your own database, no cloud, no subscription.

Agentic intelligence framework for Claude Code and Antigravity: slash commands, subagents, skills, hooks, governance, memory, and cost-aware model routing for AI-driven development.

Stores what AI agents learn — thoughts, decisions, session events and repo facts — in PostgreSQL with pgvector and serves it back through versioned MCP tools with hybrid vector-plus-full-text retrieval and budgeted context packs. Enables multiple agents to share one scoped, role-isolated long-term memory, with deliberate promotion of distilled candidates into durable memories.

Provides a shared, repo-local memory that lets coding agents recall relevant decisions, conventions, gotchas, and open threads, save new entries, coordinate file claims, and cache file summaries across tools and sessions.

Enables AI IDEs and assistants to perform AST analysis, map dependency graphs and call chains, run semantic code search, and optionally sync cloud-backed memory — all locally so source code never leaves the machine.

Enables AI agents to debug Commodore software in a locally running VICE emulator through its text remote monitor, inspecting registers, memory and screens, disassembling code, setting breakpoints and watchpoints, controlling execution, and working with disk images, snapshots and exported graphics. Runs locally over stdio and includes safety guidance for state-changing operations.

Enables AI agents to run Meta (Facebook and Instagram) advertising: pull spend, CPA, ROAS and breakdown reports, audit account health, build and boost campaigns, ad sets and ads, and pause or adjust budgets, all starting paused until the user approves going live. Also supports brand memory, change logs and an optional daily spend cap.

Enables an LLM to orchestrate multiple downstream MCP tools inside one isolated sandbox in a single turn, filtering intermediate results in memory and returning only the final output to cut context tokens.

Enables AI agents to store and retrieve persistent memory across sessions and machines, and to pay any x402 API while keeping a signed, offline-verifiable ledger of purchases and spending.

Mounts a headless, low-memory browser for agents with a text-first tool interface, enabling navigation, semantic tree/markdown extraction, structured-data scraping, screenshots, form interaction, and session capture. Reads and interactions are returned as semantic trees, markdown, or CSS-selector JSON rather than pixels, which is cheaper for a model to reason over.

Core interfaces and reference storage adapters for the ggui MCP server — UiGenerator, GguiSessionStore, BlueprintProvider, AuthAdapter, plus in-memory and SQLite implementations. The pluggable seam layer @ggui-ai/mcp-server is built on.

Team-aware memory: intent, decisions, real-time conflicts for AI coding assistants.