OpenClaw Dashboard is a beautiful, zero-dependency command center for OpenClaw AI agents. It provides a single local page that collects gateway health, costs, cron status, active sessions, sub-agent runs, model usage, and git log in one place, refreshed automatically without login or external dependencies. It aims to offer an at-a-glance overview layer for users to monitor the health of their OpenClaw setup and make informed decisions quickly without the need to search through log files or run CLI commands.

Nanocoder is a versatile code editor designed for beginners and experienced programmers alike. It provides a user-friendly interface with features such as syntax highlighting, code completion, and error checking. With Nanocoder, you can easily write and debug code in various programming languages, making it an ideal tool for learning, practicing, and developing software projects. Whether you are a student, hobbyist, or professional developer, Nanocoder offers a seamless coding experience to boost your productivity and creativity.

AI Counsel is a true deliberative consensus MCP server where AI models engage in actual debate, refine positions across multiple rounds, and converge with voting and confidence levels. It features two modes (quick and conference), mixed adapters (CLI tools and HTTP services), auto-convergence, structured voting, semantic grouping, model-controlled stopping, evidence-based deliberation, local model support, data privacy, context injection, semantic search, fault tolerance, and full transcripts. Users can run local and cloud models to deliberate on various questions, ground decisions in reality by querying code and files, and query past decisions for analysis. The tool is designed for critical technical decisions requiring multi-model deliberation and consensus building.

Tokscale is a high-performance CLI tool and visualization dashboard for tracking token usage and costs across multiple AI coding agents. It helps monitor and analyze token consumption from various AI coding tools, providing real-time pricing calculations using LiteLLM's pricing data. Inspired by the Kardashev scale, Tokscale measures token consumption as users scale the ranks of AI-augmented development. It offers interactive TUI mode, multi-platform support, real-time pricing, detailed breakdowns, web visualization, flexible filtering, and social platform features.

Claude Code Bridge (ccb) is a new multi-model collaboration tool that enables effective collaboration among multiple AI models in a split-pane CLI environment. It offers features like visual and controllable interface, persistent context maintenance, token savings, and native workflow integration. The tool allows users to unleash the full power of CLI by avoiding model bias, cognitive blind spots, and context limitations. It provides a new WYSIWYG solution for multi-model collaboration, making it easier to control and visualize multiple AI models simultaneously.

Code Puppy is an AI-powered code generation agent designed to understand programming tasks, generate high-quality code, and explain its reasoning. It supports multi-language code generation, interactive CLI, and detailed code explanations. The tool requires Python 3.9+ and API keys for various models like GPT, Google's Gemini, Cerebras, and Claude. It also integrates with MCP servers for advanced features like code search and documentation lookups. Users can create custom JSON agents for specialized tasks and access a variety of tools for file management, code execution, and reasoning sharing.

OpenMemory is a cognitive memory engine for AI agents, providing real long-term memory capabilities beyond simple embeddings. It is self-hosted and supports Python + Node SDKs, with integrations for various tools like LangChain, CrewAI, AutoGen, and more. Users can ingest data from sources like GitHub, Notion, Google Drive, and others directly into memory. OpenMemory offers explainable traces for recalled information and supports multi-sector memory, temporal reasoning, decay engine, waypoint graph, and more. It aims to provide a true memory system rather than just a vector database with marketing copy, enabling users to build agents, copilots, journaling systems, and coding assistants that can remember and reason effectively.

Alphora is a full-stack framework for building production AI agents, providing agent orchestration, prompt engineering, tool execution, memory management, streaming, and deployment with an async-first, OpenAI-compatible design. It offers features like agent derivation, reasoning-action loop, async streaming, visual debugger, OpenAI compatibility, multimodal support, tool system with zero-config tools and type safety, prompt engine with dynamic prompts, memory and storage management, sandbox for secure execution, deployment as API, and more. Alphora allows users to build sophisticated AI agents easily and efficiently.

AgentField is an open-source control plane designed for autonomous AI agents, providing infrastructure for agents to make decisions beyond chatbots. It offers features like scaling infrastructure, routing & discovery, async execution, durable state, observability, trust infrastructure with cryptographic identity, verifiable credentials, and policy enforcement. Users can write agents in Python, Go, TypeScript, or interact via REST APIs. The tool enables the creation of AI backends that reason autonomously within defined boundaries, offering predictability and flexibility. AgentField aims to bridge the gap between AI frameworks and production-ready infrastructure for AI agents.

AutoMem is a production-grade long-term memory system for AI assistants, achieving 90.53% accuracy on the LoCoMo benchmark. It combines FalkorDB (Graph) and Qdrant (Vectors) storage systems to store, recall, connect, learn, and perform with memories. AutoMem enables AI assistants to remember, connect, and evolve their understanding over time, similar to human long-term memory. It implements techniques from peer-reviewed memory research and offers features like multi-hop bridge discovery, knowledge graphs that evolve, 9-component hybrid scoring, memory consolidation cycles, background intelligence, 11 relationship types, and more. AutoMem is benchmark-proven, research-validated, and production-ready, with features like sub-100ms recall, concurrent writes, automatic retries, health monitoring, dual storage redundancy, and automated backups.

ZeroClaw is a fast, small, and fully autonomous AI assistant infrastructure built with Rust. It features a lean runtime, cost-efficient deployment, fast cold starts, and a portable architecture. It is secure by design, fully swappable, and supports OpenAI-compatible provider support. The tool is designed for low-cost boards and small cloud instances, with a memory footprint of less than 5MB. It is suitable for tasks like deploying AI assistants, swapping providers/channels/tools, and pluggable everything.

A powerful Go framework for building intelligent agent systems with large language models (LLMs), hierarchical planners, memory, telemetry, and a rich tool ecosystem. tRPC-Agent-Go enables the creation of autonomous or semi-autonomous agents that reason, call tools, collaborate with sub-agents, and maintain long-term state. The framework provides detailed documentation, examples, and tools for accelerating the development of AI applications.

Dexto is a lightweight runtime for creating and running AI agents that turn natural language into real-world actions. It serves as the missing intelligence layer for building AI applications, standalone chatbots, or as the reasoning engine inside larger products. Dexto features a powerful CLI and Web UI for running AI agents, supports multiple interfaces, allows hot-swapping of LLMs from various providers, connects to remote tool servers via the Model Context Protocol, is config-driven with version-controlled YAML, offers production-ready core features, extensibility for custom services, and enables multi-agent collaboration via MCP and A2A.

CTINexus is a framework that leverages optimized in-context learning of large language models to automatically extract cyber threat intelligence from unstructured text and construct cybersecurity knowledge graphs. It processes threat intelligence reports to extract cybersecurity entities, identify relationships between security concepts, and construct knowledge graphs with interactive visualizations. The framework requires minimal configuration, with no extensive training data or parameter tuning needed.

LLMLight is a novel framework that employs Large Language Models (LLMs) as decision-making agents for Traffic Signal Control (TSC). The framework leverages the advanced generalization capabilities of LLMs to engage in a reasoning and decision-making process akin to human intuition for effective traffic control. LLMLight has been demonstrated to be remarkably effective, generalizable, and interpretable against various transportation-based and RL-based baselines on nine real-world and synthetic datasets.

OpenClaw Dashboard is a beautiful, zero-dependency command center for OpenClaw AI agents. It provides a single local page that collects gateway health, costs, cron status, active sessions, sub-agent runs, model usage, and git log in one place, refreshed automatically without login or external dependencies. It aims to offer an at-a-glance overview layer for users to monitor the health of their OpenClaw setup and make informed decisions quickly without the need to search through log files or run CLI commands.

Sweep is an AI junior developer that turns bugs and feature requests into code changes. It automatically handles developer experience improvements like adding type hints and improving test coverage.

The Teams AI Library is a software development kit (SDK) that helps developers create bots that can interact with Teams and Microsoft 365 applications. It is built on top of the Bot Framework SDK and simplifies the process of developing bots that interact with Teams' artificial intelligence capabilities. The SDK is available for JavaScript/TypeScript, .NET, and Python.

This guide is dedicated to Large Language Models (LLMs) that you can run on your home computer. It assumes your PC is a lower-end, non-gaming setup.

Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.

Chatbot UI is an open-source AI chat app that allows users to create and deploy their own AI chatbots. It is easy to use and can be customized to fit any need. Chatbot UI is perfect for businesses, developers, and anyone who wants to create a chatbot.

BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students

uAgents is a Python library developed by Fetch.ai that allows for the creation of autonomous AI agents. These agents can perform various tasks on a schedule or take action on various events. uAgents are easy to create and manage, and they are connected to a fast-growing network of other uAgents. They are also secure, with cryptographically secured messages and wallets.

Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.