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Mission Control

With over 600 GitHub stars and a featured Show HN launch, Mission Control is the agent-first command center that replaces the chaos of manually shepherding AI agents with structured delegation, approval workflows, and autonomous execution. The Next.js 15 web UI delivers an Eisenhower priority matrix with drag-and-drop quadrants, a Kanban board tracking tasks through Not Started, In Progress, and Done columns, and a goal hierarchy with milestone progress bars — powered by shadcn/ui, Radix UI, and @dnd-kit. Six built-in agent roles — Researcher, Developer, Marketer, Business Analyst, Tester, and You — receive tasks through a token-optimized API compressing context by 92 percent to approximately 50 tokens versus 5,400 unfiltered. The autonomous daemon polls task queues on cron schedules, spawns Claude Code sessions via the official CLI, enforces concurrency limits, and auto-retries with loop detection that escalates to human decisions after three failures. Field Ops extends execution to 64 external services across 16 categories with working X, Ethereum with MetaMask signing, and Reddit adapters, protected by AES-256-GCM encrypted vault with scrypt key derivation, per-service and global spend limits, a circuit breaker, and three autonomy levels. All data lives in local JSON files with Zod validation and async-mutex locking ensuring safe concurrent writes, backed by 193 automated Vitest tests. 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.

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Mage

Backed by 8,700+ GitHub stars and designed as a modern alternative to Apache Airflow, Mage delivers the open-source data pipeline platform that combines the interactive flexibility of notebooks with production-grade orchestration in a single self-hosted environment accessible at port 6789. The modular block architecture lets data engineers compose pipelines from Python, SQL, and R code blocks with instant data previews, live execution logs, and visual debugging at each step. Over 100 prebuilt integrations connect sources and destinations including PostgreSQL, MySQL, Snowflake, BigQuery, Redshift, S3, Kafka, MongoDB, Amplitude, Salesforce, and Stripe with parallel stream synchronization for high-throughput data movement. Batch pipelines run on cron schedules or event triggers while streaming pipelines process real-time data from Kafka, Kinesis, and RabbitMQ with stream mode reducing memory usage by approximately 90 percent compared to batch processing. Native dbt integration builds, tests, and runs dbt models directly inside the pipeline editor alongside custom transformation blocks. Spark, Snowpark, and Databricks runtimes handle large-scale distributed processing. AI-assisted development generates code, fixes errors, and optimizes queries within the notebook interface. Monitoring dashboards track pipeline health with integrations to Datadog, Prometheus, New Relic, and OpenTelemetry. Terraform templates deploy production environments to AWS, GCP, or Azure with two commands, while Helm charts support Kubernetes clusters. 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.

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