Camel/micasa

A modal TUI for tracking home projects, maintenance schedules, appliances, and vendor quotes.

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Camel/micasa was last pushed on Feb 19, 2026. Data as of . Signed-in members get hourly updates — create a free account.

Summary Information

Updated 29 minutes ago
Added to GitGenius on September 23rd, 2026
Created on February 19th, 2026
Open Issues & Pull Requests: 0 (+0)
GitHub issues: Disabled - open counts may still include pull requests.
Number of forks: 0
Total Stargazers: 0 (+0)
Total Subscribers: 0 (+0)

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Detailed Description

micasa is a modal terminal user interface for tracking home projects, maintenance schedules, appliances, and vendor quotes.

The tool addresses the challenge of managing household maintenance and improvement work scattered across memory, notes, and various vendor communications. It stores everything in a single SQLite file on your machine with no cloud dependency, account requirement, or subscription. The interface uses vim-style modal navigation: a browse mode for viewing data and an edit mode for making changes. Users can sort by any column, search columns with fuzzy matching, hide irrelevant fields, and follow relationships between records. The tool tracks maintenance schedules with auto-computed due dates and full service history, projects from planning through completion, vendor quotes side by side with vendor history, appliances with purchase dates and warranty status, incidents with severity and location linked to appliances and vendors, and a vendor directory with contact information and job history. Files like manuals, invoices, and photos attach directly to projects and appliances as BLOBs within the same database file, making complete backups trivial.

micasa suits homeowners who want to consolidate scattered home management data without relying on cloud services or subscriptions. It works best for people comfortable with keyboard-driven interfaces and those who prefer terminal applications. The local-first approach appeals to users concerned about data privacy or who lack reliable internet connectivity. The optional local LLM integration, powered by Ollama or OpenAI-compatible APIs, lets users query their home data in plain English; the model translates questions to SQL, executes queries, and summarizes results entirely on the user's machine. A magnitude mode replaces dollar amounts with order-of-magnitude symbols for privacy-conscious review.

Development activity shows consistent engagement with regular commits across the codebase. The project maintains comprehensive documentation covering installation, first-run setup, usage guides, and configuration reference. Pull requests receive timely review and feedback. The maintainer actively addresses issues and incorporates user suggestions into the tool's direction.