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thepopebot is an open-source template for deploying a 24/7 autonomous AI agent using GitHub Actions as the execution environment. You interact with the agent via Telegram (or a webhook). An event handler creates a job branch, GitHub Actions spins up a Docker container that runs the “Pi” coding agent, and the agent completes the task by committing changes and opening a pull request. Optional auto-merge workflows can merge results automatically. The project emphasizes security by filtering secrets at the process level so the agent cannot access them directly, and it treats the git repository history as the agent’s auditable, reversible memory.

thepopebot

Open-source autonomous coding agent that runs on GitHub Actions, does work in Docker, commits changes, and notifies you on Telegram.

Awesome OpenClaw Use Cases is a community-curated repository that collects practical, real-world OpenClaw workflows and examples. It’s intended to help users and developers discover how people use OpenClaw to make life easier, providing inspiration and patterns that can be copied, adapted, and extended into new skills and automations. The repo acts as a living catalog of use cases rather than a standalone tool, enabling faster onboarding and idea discovery for building with OpenClaw.

Awesome OpenClaw Use Cases

awesome-openclaw-use-cases

Community list of real OpenClaw use cases and workflows to copy, adapt, and extend for personal and developer productivity.

memU is an open-source memory infrastructure for LLM applications and AI agents, designed for long-running, always-on assistants that need persistent, evolving memory. It organizes memories like a file system (categories as folders, memory items as files, cross-links as symlinks) and supports proactive behavior such as capturing user intent, predicting next steps, and injecting relevant memory into the agent’s context. memU aims to reduce token spend for continuous agents by caching insights and avoiding redundant LLM calls, and it includes companion components like a backend service (memU-server) and a web UI (memU-ui). In addition to the open-source framework, memU offers hosted APIs (Memory API / Response API) with usage-based pricing and a “start free” path.

memU

memu

Open-source agentic memory framework for 24/7 proactive AI agents with file-system memory, intention prediction, and lower token costs.

Amp is an agentic coding tool by Sourcegraph that runs in the terminal and editor extensions (including VS Code and compatible forks). It is designed for complex coding tasks such as multi-file edits, planning, and execution using multiple frontier model options. Amp includes a threads feature to save and share interactions, and offers “Amp Free” with a daily credit grant supported by sponsor ads, plus pay-as-you-go usage with no markup for individuals after the free allowance.

Agentic coding tool for terminal and editors that uses multiple frontier models, with a free $10/day grant and pay-as-you-go pricing.

Ralph is an open-source autonomous AI coding loop that repeatedly runs an AI coding tool (Amp CLI or Claude Code) until every item in a Product Requirements Document (PRD) is finished. Each iteration starts with clean context, while progress persists through git history and project files like prd.json and progress.txt. Ralph is designed to help developers ship features with minimal manual intervention by continuously planning, implementing, committing changes, and checking off PRD items in a structured loop.

Ralph

ralph

Autonomous AI coding loop that repeatedly runs Amp or Claude Code until all PRD items are completed, using git history as memory.

Mastra is an all-in-one TypeScript framework for building AI-powered applications and agents. It supports core agent patterns like tools, workflows/orchestration, RAG, memory, MCP integration, and evals, designed to go from prototype to production inside your own codebase. Mastra also offers an optional Mastra Cloud/Platform experience with a Studio for testing agents and workflows plus AI-focused observability (structured logs, tracing, and eval dashboards) and deployment integrations.

Mastra

mastra

Open-source TypeScript framework for building AI agents, workflows, RAG, memory and MCP, with optional cloud studio and observability.

PubNub MCP Server is a CLI-based Model Context Protocol (MCP) server that connects MCP-compatible AI assistants (like Cursor, VS Code, Claude Code, Codex, and others) to PubNub’s SDK documentation and PubNub account/API resources. It helps agents retrieve SDK and Chat SDK documentation across many languages, manage PubNub apps and keysets (including enabling features like persistence, files, presence, and app context), and perform real-time operations such as publish/subscribe, signals, presence, and user/channel objects. The server supports dynamic mode (keys provided per tool call) and fixed mode (publish/subscribe keys set via environment variables) and can be installed via npm or run via Docker, with authentication typically provided using a PubNub API key.

PubNub MCP Server

pubnub-mcp-server

MCP server that lets AI coding assistants access PubNub docs and manage apps/keysets, plus messaging, presence, and channel/user objects.

GLM-4.6V is a next-generation multimodal large language model series from Z.ai (Zhipu AI), designed for high-fidelity visual understanding and long-context reasoning across images, video, documents, and text. It comes in two main variants: the 106B-parameter GLM-4.6V foundation model for cloud and cluster deployment, and the lightweight GLM-4.6V-Flash (9B) optimized for local and low-latency applications. With a 128k token context window, GLM-4.6V can read large PDFs, slide decks, and multi-page mixed-media documents in a single pass. Native multimodal function calling lets it use tools directly from visual inputs, closing the loop from perception to executable actions and enabling powerful agent-style workflows. Typical use cases include visual document QA, chart and layout understanding, multimodal search and analysis, converting UI screenshots into production-ready code, and generating image-rich content. The models are released with open weights under a permissive open-source license, making them suitable for research, self-hosted deployments, and integration into production systems.

GLM-4.6V

glm-4-6v

Open-source multimodal GLM from Z.ai unifying vision, text, and tool calling for long-context reasoning, search, coding, and UI-to-code.