Reaching 45,000 GitHub stars within seven months of launch, Multica is the fastest-growing open-source platform for managing AI coding agents as first-class teammates — assign an issue to Claude Code, Codex, Cursor, Copilot, Kimi, or any of 21 supported agent CLIs and it picks up the work, comments progress in real time via WebSocket, raises blockers, and hands the result back for human review before anything merges. The Go backend (Chi router, sqlc-generated type-safe queries, gorilla/websocket) connects to PostgreSQL 17 with pgvector for semantic search across workspace history, while the Next.js 16 App Router frontend delivers workspace dashboards showing per-agent token spend, execution time, daily cost charts, and runtime status across unlimited connected machines. Agent Skills provide reusable methods, reference material, and supporting files that compound across runs — a persistent knowledge layer that makes each subsequent task faster and more accurate. Squads let a leader agent select the right specialist for subtasks, creating multi-agent workflows without manual orchestration. Review gates ensure no AI-generated code ships to main without explicit human approval. Self-host via Docker Compose or Kubernetes with full Git integration across GitHub, GitLab, Gitea, and Forgejo including self-hosted instances. The CLI and REST API make every surface scriptable, and Autopilot automations trigger agent runs from events. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed with additional conditions.

Backed by Y Combinator (S24) and processing traces from thousands of AI agents in production, Laminar is the open-source observability platform that treats agent debugging as a first-class engineering discipline rather than an afterthought. Its OpenTelemetry-native SDK auto-instruments Vercel AI SDK, LangChain, OpenAI, Anthropic, Gemini, Browser Use, Stagehand, Mastra, Pydantic AI, and the OpenAI Agents SDK with a single line of code, capturing every LLM turn, tool call, and sub-agent delegation as nested spans with full input/output data and token costs. The Signals engine lets you describe failures in plain language — "agent is stuck in a loop" or "tool returned empty results" — then reads every trace and alerts via Slack when it detects a match. A built-in debugger records runs and replays them from cache so each iteration takes seconds, designed for Claude Code, Cursor, or Codex to drive the repair loop via the MCP server or CLI. Run code-first evaluations in Python or TypeScript locally or in CI/CD pipelines, build datasets from production traces, and query everything with raw SQL through custom dashboards, the in-app editor, or your coding agent. The Rust backend delivers 20x trace compression, a custom real-time streaming engine, ultra-fast full-text search, and gRPC ingestion, while ClickHouse powers columnar analytics and PostgreSQL stores application state. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.

The first open-source substrate for enterprise knowledge engineering that learns passively and governs itself. The Rust-built backend paired with PostgreSQL and pgvector delivers a bitemporal knowledge graph where every fact carries two timelines: when it held in the real world and when the system came to believe it — enabling full audit trail replay of how understanding evolved. Document ingestion handles PDF, DOCX, PPTX, XLSX, CSV, Markdown, HTML, and plain text with legacy encoding detection, while scheduled syncing pulls from web pages, RSS feeds, GitHub, Jira, Notion, WebDAV, and S3-compatible buckets. Search fuses Tantivy full-text indexing with pgvector semantic vectors using Reciprocal Rank Fusion, streaming answers with inline citations that link directly to source passages. The built-in agent harness drives agentic RAG through conversation — searching documents, walking the knowledge graph at any historical date, and querying mounted databases via Ontology2SQL which achieves state-of-the-art results on BIRD Mini-Dev benchmarks. Five ontology packs ship inside the binary (schema.org, W3C Org, PROV-O, FOAF, IOF Core) with forward-chaining reasoning for transitivity, symmetry, inverses, and relation hierarchy. Entity resolution operates in three stages: exact name matching, embedding similarity, then model-based judgment with every merge reversible. Any OpenAI-compatible endpoint works including DeepSeek, Qwen, Ollama, and vLLM for fully air-gapped deployment. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

Paste one SQL query result into a browser and get an interactive entity-relationship diagram instantly, with no installations, no credentials, and no account required. ChartDB's "Smart Query" runs a single statement in your existing database client that exports table definitions, relationships, indexes, and column types as JSON metadata, meaning the application never touches your database passwords. The canvas renders draggable entities with cardinality markers, collapsible grouping areas, and sticky notes for documentation. AI-powered DDL export generates migration scripts between dialect pairs like PostgreSQL to MySQL or SQLite to CockroachDB, analyzing your schema to produce target-specific DDL with correct type mappings and constraint translations. Import paths cover Smart Query JSON, raw DDL scripts, and DBML files from tools like dbdiagram.io. The AI layer connects to OpenAI or any compatible inference server including local vLLM instances running models like Qwen2.5-32B. Database coverage includes PostgreSQL (with Supabase and Timescale extensions), MySQL, SQL Server, MariaDB, SQLite (with Cloudflare D1), CockroachDB, ClickHouse, and Oracle. Exports to SVG with inline styles or SQL DDL in any target dialect. Ships as a React/Vite frontend behind Nginx in Docker, deployable on RepoCloud with dedicated VPS resources under the AGPL-3.0 license.

FalkorDB is the first queryable property graph database to leverage sparse adjacency matrices and linear algebra for graph traversal, replacing traditional pointer-chasing with GraphBLAS-accelerated computation. Originally the RedisGraph engine, it was relaunched as FalkorDB in 2023 and rewritten from C to Rust in 2026 for improved memory safety and performance. The database supports the OpenCypher query language with proprietary extensions, translating queries into linear algebra expressions that exploit AVX hardware acceleration. Indexing options include full-text search, vector similarity for embedding-based retrieval, and range indexing, while connectivity supports both the RESP protocol for Redis clients and the Bolt protocol for Neo4j-compatible tooling. The GraphRAG SDK enables ingestion of documents in text, PDF, and Markdown formats into knowledge graphs, with schema-guided entity extraction, hybrid retrieval combining vector and graph traversal, relationship expansion, and cited answers for LLM applications. Official client libraries cover Python, Node.js, Java, Rust, Go, PHP, and C#. Multi-tenant support handles over 10,000 concurrent graphs with zero overhead and full isolation. Docker deployment runs the falkordb/falkordb image on ports 6379 for the database server and 3000 for the built-in browser UI, with persistent volume storage and optional authentication. A production falkordb-server image excludes the browser for lighter deployments. On RepoCloud, deploy FalkorDB on a dedicated VPS with root SSH access, persistent storage for your graph data, and complete control over authentication, thread count, and memory configuration, all under the SSPLv1 license.

With over 46,000 GitHub stars, nanobot is the ultra-lightweight personal AI agent framework that delivers full agentic capabilities — tools, persistent memory, multi-agent workflows, scheduled automation, and 10+ chat channel integrations — in approximately 4,000 lines of readable Python core code. The agent loop receives messages from any connected channel, builds context from session history and long-term memory files, calls the configured LLM provider, executes requested tools, and publishes replies back to the originating channel. Supported LLM providers include OpenAI, Anthropic, Google Gemini, DeepSeek, Qwen via DashScope, Moonshot/Kimi, Ollama, vLLM for local models, and any OpenAI-compatible API through OpenRouter or LiteLLM. Chat channels connect the agent to Telegram, Discord, Slack, WhatsApp, Feishu/Lark, DingTalk, Email via IMAP/SMTP, QQ, Matrix with end-to-end encryption, Mattermost, and the built-in browser WebUI served from the published Python wheel with no separate frontend build. Built-in tools include filesystem read/write/edit, shell execution with configurable sandboxing via bubblewrap, web search and fetch with SSRF protection, MCP server integration, cron scheduling, image generation, and subagent spawning for parallel task delegation. The Dream memory system consolidates session history into persistent markdown files for long-term context retention across conversations. Deployment runs as a CLI agent, a persistent gateway server, a Docker container with Docker Compose, or an OpenAI-compatible API server. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Backed by Alibaba's AIDC team and carrying over 27,700 GitHub stars, Pixelle-Video turns a single text prompt into a publish-ready short video in approximately three minutes — handling scriptwriting, image generation, voice narration, music selection, subtitle overlay, and final MP4 export in one automated pipeline. The engine supports multiple LLM backends for script generation including GPT-4, Qwen, DeepSeek, and local Ollama deployments, while image and video creation routes through either self-hosted ComfyUI workflows, cloud-based RunningHub pipelines, or direct API connections to DashScope Wan, OpenAI, Seedream, Seedance, and Kling AI. Text-to-speech synthesis uses Edge-TTS, Index-TTS, and other mainstream engines with multi-language voice profiles. Five distinct pipelines cover Quick Create, Standard, Digital Human Avatar broadcasting, Image-to-Video transformation, and Motion Transfer from reference video. The Streamlit web UI on port 8501 provides a visual workflow builder with template selection across portrait (1080x1920), landscape (1920x1080), and square formats, while the FastAPI server on port 8000 exposes a REST API with endpoints for async video generation, task polling, content scripting, TTS and image generation, template listing, and health checks. History persistence tracks all completed generations. HTML-based visual templates support static, image-overlay, and AI-video styles with customizable prompt prefixes. The modular architecture lets operators swap any atomic capability — image model, video model, TTS engine, or VLM — by editing a workflow JSON file without touching Python code. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.

OpenPencil is the open-source design editor that reads and writes native Figma .fig files using the same Kiwi binary format — enabling bidirectional copy-paste between Figma and OpenPencil without data loss. The built-in AI assistant provides 90+ design tools through a chat interface, creating and modifying shapes, fills, strokes, auto-layout, components, variables, and boolean operations from natural language prompts, with BYOK support for Anthropic, OpenAI, Google AI, OpenRouter, Z.ai, MiniMax, and compatible endpoints. A Skia CanvasKit WASM renderer paired with Yoga WASM layout engine delivers Figma-parity rendering with flex and CSS Grid support including gap, padding, and alignment. The headless CLI inspects node trees via XPath queries, lints naming and accessibility, converts between document formats, analyzes color and typography patterns, extracts design tokens, and exports to PNG, SVG, JSX/Tailwind, and HTML. An MCP server exposes all design operations over stdio and HTTP, connecting Claude Code, Cursor, Windsurf, and Gemini CLI for AI-assisted design automation. Real-time P2P collaboration via WebRTC with Yjs CRDT synchronization requires no server and no account. The Vue SDK provides headless components for embedding the editor into custom applications. Ships as a 7 MB Tauri v2 desktop app for macOS, Windows, and Linux, or runs in any browser as a PWA. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Agentic SOC Platform compresses hours of manual security analysis into seconds by deploying specialized AI agents that autonomously triage, investigate, and enrich security alerts. The Python/Django backend processes SIEM webhooks through Redis Streams into a modular pipeline where LangGraph-orchestrated agents extract IOCs, correlate signals, and generate Cases with severity, confidence, impact, priority, and structured verdicts. The built-in SIRP provides full case management with Alerts, Artifacts, Enrichments, Tickets, and a Knowledge base that accumulates institutional memory for both human analysts and LLM agents. Native Splunk and Elasticsearch/Kibana integrations deliver unified log search through a standardized interface so agents and analysts share identical security context. The playbook engine combines traditional SOAR automation with AI-powered investigation — launching threat hunting agents, knowledge extraction, threat intelligence enrichment, and CMDB lookups from a single orchestration layer. MCP Plugin support exposes ASP capabilities to Claude Code, Codex, and OpenCode, enabling external AI agents to operate cases, search logs, query threat intelligence, and write custom modules directly. Python Modules adapt new alert sources while Playbooks orchestrate LLM analysis and automated response actions, scaling the platform with your security scenarios. Deploy via Docker Compose with all data staying inside your network. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Backed by Y Combinator and powering scraping infrastructure across 195 countries, Anakin delivers a production-grade web scraping API purpose-built for AI agents and RAG pipelines that need clean, structured data from sites that actively block conventional scrapers. The single Go binary server handles JavaScript-heavy SPAs through its Camoufox anti-detect browser service with automatic fingerprint rotation, while the HTTP-first handler chain tries lightweight extraction before escalating to full browser rendering — keeping response times under 2 seconds for static pages. The built-in React 19 dashboard provides visual scraping with live results, job tracking with status filters, domain configuration management with handler chain CRUD, and proxy performance monitoring via Thompson Sampling scoring. Structured JSON extraction leverages Gemini AI to transform raw HTML into typed schemas without manual selector maintenance. SDKs span Python, TypeScript, Go, .NET, Java, and Ruby, while the MCP server exposes all 21 tools directly to Claude, Cursor, Windsurf, and any Model Context Protocol-compatible agent. The hosted platform extends the open-source engine with AI web search returning full page content with citations, multi-source agentic research across 20+ sources per query, Wire pre-built actions covering 944 websites with 5,201 structured endpoints, persistent browser sessions for authenticated scraping, and website change monitoring with scheduled alerts. Deploy via Docker Compose with three containers or run the binary directly with optional PostgreSQL persistence. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

FreeLLMAPI collapses the chaos of 29 free LLM providers — Google AI, Cerebras, Groq, Mistral, OpenRouter, GitHub Models, Cohere, Cloudflare Workers AI, NVIDIA NIM, HuggingFace, SiliconFlow, Reka, Z.ai, and more — into a single /v1 endpoint that speaks both OpenAI and Anthropic protocols. The smart router selects the best available model for each request, automatically fails over to the next provider when rate limits hit, and tracks per-key token consumption so you never exceed a free-tier cap. Keys are stored with AES-256-GCM encryption and clients authenticate using a single unified bearer token, never exposing upstream provider credentials to downstream applications. The catalog tracks 251 model families across 358 provider/model endpoints with approximately 4 billion tokens per month of aggregate free-tier capacity, auto-refreshing from a signed manifest at freellmapi.co twice daily without requiring git pulls. Beyond chat completions, the proxy handles embedding, image generation, and audio/TTS endpoints, plus structured outputs with JSON schema forwarding, JSON healing, and format-ignore failover. An integrated MCP server at /mcp provides gateway introspection for coding agents, while the self-hosted OpenAPI reference at /v1/docs documents every route. Compatible with OpenAI SDKs, LangChain, LlamaIndex, Continue, Claude Code, and Hermes — just change base_url. Deploy via Docker, npm, or build from source. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

With over 27,000 GitHub stars and an ecosystem of 1,900+ plugins covering every major cloud provider, database, and SaaS platform, Kestra is the orchestration engine that brings Infrastructure as Code principles to workflow automation — defining complex multi-step pipelines in readable YAML that execute across any language, runtime, or infrastructure boundary. The built-in VS Code-style editor provides syntax highlighting, auto-completion, real-time validation, and an AI Copilot that generates workflow YAML from natural language descriptions. Tasks execute in Python, Node.js, Go, R, Shell, SQL, or any Docker container, with event-driven triggers listening for file arrivals on SFTP and cloud storage, messages from Kafka, Redis, Pulsar, AMQP, MQTT, NATS, AWS SQS, Google Pub/Sub, and Azure Event Hubs in real time. The topology view visualizes workflow DAGs with execution state, duration, and output artifacts for each task node. Namespaces organize workflows into isolated environments with configurable secrets, while subflows enable modular composition with inputs, outputs, and conditional branching. Retry policies, timeouts, error handlers, and automatic backfills for missed schedules ensure reliability across production workloads. Git integration pushes workflows directly to branches from the UI with CI/CD pipeline support for automated deployment. The REST API enables programmatic workflow management, execution triggering, and resource provisioning. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.

Stop hoping your AI coding assistant remembers to plan before it codes, test after it implements, and review before it ships. Archon wraps Claude Code, OpenAI Codex, and other AI agents inside structured YAML workflows that enforce the same development process every single time. Define your pipeline as a directed acyclic graph of nodes (AI tasks, shell scripts, approval gates, loops) and Archon handles the orchestration: resolving dependencies, running independent nodes in parallel, passing artifacts between steps, and isolating every run in its own git worktree so five bug fixes can proceed simultaneously without conflicts. Ship with 17 pre-built workflows covering everything from "idea to merged PR" to automated conflict resolution, or author your own by committing YAML files to your repository's .archon/workflows/ directory. The web dashboard, launched with archon serve, provides a conversation interface with real-time streaming, a visual drag-and-drop workflow builder for creating DAG pipelines, step-by-step progress monitoring for every run, and a unified sidebar aggregating conversations from CLI, Slack, Telegram, and GitHub into one view. An NLP router parses natural language requests and automatically selects the right workflow. Structured JSON output schemas let you enforce typed responses from AI nodes, with validation and auto-repair for providers that lack native schema support. Every workflow file is version-controlled, portable, and reviewable in pull requests, so your entire team runs identical processes from day one. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Puter delivers a complete cloud operating system that runs entirely in the browser — turning any device with internet access into a full-featured personal computer with desktop environment, file management, application hosting, and developer platform. The familiar desktop interface presents windows, taskbar, right-click menus, drag-and-drop, and multi-window management indistinguishable from native operating systems. The hierarchical filesystem supports file creation, uploads, sharing, permissions, and trash recovery with storage backends ranging from local SQLite for self-hosting to S3 and DynamoDB for production scale. Built-in AI integration provides access to GPT-4, Claude, and other models directly from the desktop for text generation, code assistance, and image creation. The developer platform offers a JavaScript SDK, REST APIs, cloud storage, key-value database, and serverless workers for building and hosting web applications without managing infrastructure. Sandboxed applications run in iframes with IPC communication and permission-based access to filesystem, AI, and system services. The app store enables publishing, discovering, and monetizing applications built on the Puter platform. Website hosting publishes static sites with custom domains directly from the file manager. Multi-user support provides individual accounts with authentication, resource isolation, and sharing capabilities. Deploy via Docker with a single command, Docker Compose for production, or npm for development — the one-line install script handles everything automatically on Linux, macOS, and Windows. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

With over 2,700 GitHub stars, Auto Company is the first open-source framework that runs a fully autonomous AI company 24/7 — 14 specialized agents modeled after Jeff Bezos (CEO strategy), Werner Vogels (CTO architecture), Charlie Munger (critical analysis), DHH (full-stack engineering), Kelsey Hightower (DevOps), Seth Godin (marketing), and eight more domain experts collaborate through dynamic squad formation to ideate products, write code, deploy infrastructure, and execute marketing campaigns without human intervention. The five-layer architecture separates execution, orchestration, cognition, workflow routing, and observability, while the consensus memory pattern uses a single markdown file as a relay baton between cycles — no vector databases, no Redis, no embeddings required. A bash loop invokes Claude Code or OpenAI Codex CLI every 30 seconds, each cycle selecting 2-5 agents from the 14-person pool based on task context. Over 30 reusable skills handle specialized tasks from frontend design to competitive analysis and deployment automation. Circuit breakers trigger cooldown after consecutive errors, rate-limit detection auto-sleeps on API throttling, and sandbox rollback protects against destructive changes. The Python-powered web dashboard displays real-time cycle status, cost tracking per cycle averaging under $2, and agent activity visualization, with CLI control via make start, stop, monitor, pause, and resume. Supports macOS via launchd, Windows via WSL with systemd, and native Linux deployment. The npx create-auto-co command scaffolds a new AI company in seconds. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Backed by over 21,800 GitHub stars and more than 1,000 community contributors, Airbyte has become the standard open-source data movement platform, powering ELT pipelines for organizations ranging from startups to Fortune 500 enterprises. The platform provides 600+ pre-built connectors covering PostgreSQL, MySQL, MongoDB, Snowflake, BigQuery, Redshift, S3, Salesforce, HubSpot, Stripe, Shopify, Google Analytics, and hundreds of additional APIs, databases, and SaaS applications. The no-code Connector Builder lets practitioners create new source connectors in minutes by pointing at an API documentation URL, while the Python CDK enables custom connectors with full programmatic control for complex authentication flows and pagination strategies. Airbyte's AI agent capabilities include the MCP Gateway for Model Context Protocol integration, the open-source Agent SDK compatible with pydantic-ai, LangChain, OpenAI Agents, and FastMCP, and a Context Store that lets AI agents query business data across connected systems without runtime API stitching. Change Data Capture streams incremental updates from PostgreSQL, MySQL, and SQL Server using Debezium, while dbt integration handles post-load transformations within the pipeline. Self-hosted deployment uses Kubernetes via the abctl CLI tool, which bootstraps a local kind cluster with a single command, or Helm charts for production clusters with Keycloak OIDC authentication and secrets management through AWS Secrets Manager, Google Secrets Manager, or HashiCorp Vault. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. ELv2 licensed with MIT-licensed connectors.

CPA Manager Plus is a self-hosted observability dashboard and management panel that tracks every AI request flowing through your CLI Proxy API gateway, breaking down failures, costs, and account health across providers like OpenAI, Anthropic, xAI, and Codex in one interface. When a request fails, drill into the persistent history to see status codes, affected models, latency, and redacted failure evidence without exposing raw response bodies. The cost analytics engine breaks down token consumption and estimated spend by model, provider, account, API key, project, channel, and time range while tracking input, output, reasoning, cache, and service-tier pricing semantics separately. Model prices sync automatically from models.dev with LiteLLM and OpenRouter fallbacks, and you can add local overrides for aliases or internal models. For teams running Codex or xAI accounts, the health inspector reads quota windows, reset evidence, credential state, and workspace status on a configurable schedule, routing credential failures into an action queue for review rather than letting them silently degrade throughput. Deploy the Lightweight Panel to replace your existing CPA management UI without adding another service, or run Full Mode as a single Docker container that adds the Manager Server with persistent SQLite storage for request history, historical analytics, and automated account inspections. Export or import request history as JSONL for external analysis, and back up the SQLite files alongside your encrypted management keys. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Keep is an open-source AIOps and alert management platform built with Python FastAPI and Next.js. It provides a single pane of glass for monitoring alerts from 110+ integrations, alert deduplication, correlation, enrichment, and filtering, YAML-based workflow automation similar to GitHub Actions, AI-powered correlation and summarization, and customizable dashboards for incident management. With 12,100+ GitHub stars, Y Combinator backing, and an Elastic partnership, Keep is the open-source AIOps platform that centralizes alert management across your entire monitoring stack into a single customizable dashboard. Alert deduplication identifies duplicate notifications across providers, correlation groups related alerts into incidents based on rules or AI-powered semantic analysis using pluggable LLM backends supporting OpenAI, Anthropic, and local models via Ollama, and enrichment adds context from external sources like CMDBs and databases. Workflow automation follows a GitHub Actions paradigm with declarative YAML files defining triggers, conditions, and actions that can query MySQL, update Jira tickets, send Slack messages, execute Python scripts, or call REST APIs. Authentication supports no-auth, database, Auth0, Keycloak, OAuth2 Proxy, Okta, and OneLogin. The Common Expression Language enables advanced alert querying, slicing, and rule-based grouping to reduce noise. On RepoCloud, deploy Keep on a dedicated VPS with Docker Compose, root SSH access, and complete control over your alert infrastructure, all under the MIT license.