whodb

iple windows - SQL formatter and extended autocomplete - SSH support (still testing this one) - ER diagram generation - EXPLAIN plan generation - Mock data generation - Simple table data audit functionality - Read-only mode - Streaming AI chat - CLI profiles - Different theme support - JSON, NDJSON, CSV outputs Disclaimer: a lot of the CLI code was AI-generated (mostly Claude Code). I point it to existing repos using the same libraries as reference, which helps since I don't have deep CLI development experience. If you want to install it, there are several ways: (1) curl -fsSL https://raw.githubusercontent.com/clidey/whodb/main/cli/inst... | bash (2) brew install whodb-cli (3) npm install -g @clidey/whodb-cli (4) docker pull clidey/whodb-cli:latest (5) Grab the executables from our latest Github release If you want to add it to CC: (1) claude mcp add whodb -- npx -y @clidey/whodb-cli mcp serve (2) or you can configure it with database credentials via an env variable profile: claude mcp add whodb -e WHODB_POSTGRES='[{"alias":"dev","host":"localhost","user":"user","password":"pass","database":"mydb","port":"5432"}]' -- whodb-cli mcp serve It should work with Codex as such: codex mcp add whodb -- whodb-cli mcp serve Happy to hear your thoughts on how you might use this, or what additions you might find interesting. Thanks for reading!

is, ClickHouse, Elasticsearch Performance: * Startup: <300ms * Query execution: ~50–200ms overhead vs raw SQL (mostly rendering) * Binary size: ~50MB (OS/arch dependent) Tradeoffs: 1. Optimized for interactive exploration, not bulk operations. Pagination exists but very large tables can be painful. 2. TUI complexity: Bubble Tea is powerful but harder to debug than a simple CLI. Errors are shown with copy-pasteable GitHub issue text. 3. AI requires setup: Ollama locally or env vars (WHODB_OPENAI_API_KEY, WHODB_ANTHROPIC_API_KEY). 4. Keyboard shortcuts may not feel intuitive to everyone—feedback welcome. Known limitations: 1. Syntax highlighting is basic and sometimes wrong. 2. Large result sets can feel sluggish when scrolling, even with pagination. 3. Connections are file-based (~/.whodb-cli/config.yaml). Passwords/secrets are stored in the system keyring. This tool was built primarily for ourselves as software developers. It’s not meant for heavy analytics or DBA-style power tooling, but we plan to keep improving it and make it more enterprise-ready. CLI README with usage examples: [https://github.com/clidey/whodb/blob/main/cli/README.md](https://github.com/clidey/whodb/blob/main/cli/README.md) Open questions: 1. Is the MCP server actually useful to others? 2. Is a simple yes/no AI consent sufficient, or is there a better/compliant approach? 3. Is tab-based view switching intuitive, or would vim-style :commands be better? 4. How should this fit into existing workflows instead of feeling “extra”? Try it: npm i -g @clidey/whodb-cli whodb-cli Supports macOS, Windows, and Linux (arm64/x64, plus armv7 without AI). We’ll add Homebrew and go install support. Binaries are also attached to releases: https://github.com/clidey/whodb/releases/tag/0.89.0

back. Today we want to open it up to the public with a release of the generation service! * Try it out! * Go to https://docucod.com/oss and put your repository URL there. Once generated, the link will be visible. You can also put the prefix url in front of the repo url: https://docucod.com/docs/<repo-url> (example: https://docucod.com/docs/https://github.com/clidey/whodb) Please note this will work only for public repos up to 100MB. How it works: Docucod analyzes the codebase, parses files, comments, types, examples, and the readme, then builds a static documentation site you can browse immediately — no config, no setup. It tries to surface useful context automatically so you don’t have to read the code line by line to figure out what’s going on. There is diagram generation with Mermaid, and we are working on generating images and later videos! The publishing is done with our own static site builder called Dory ([https://github.com/clidey/dory](https://github.com/clidey/dory)). It handles parsing, structure extraction, and HTML generation. Dory has been built with handling AI-generated MDX in mind, which is an interesting hurdle to overcome. We're still fleshing it out, so PRs and feedback are very welcome. What’s next: Right now we support public GitHub repos (private support coming). We’re also working on features like code search across the docs, customized responses based on the user's query, better navigation, theme customization, and integration with CI pipelines. If you check it out, I’d really appreciate your feedback — both the good and the bad. Does it solve a real problem for you? What’s confusing, missing, or just not helpful? Thanks!

e’d appreciate hearing your feedback. GitHub: https://github.com/clidey/whodb

ySQL, SQLite3 MongoDB, Redis, and other SQL and NoSQL support coming soon! * Completely Open Source: WhoDB is entirely open source, so you can get started right away and contribute to its growth. You can run WhoDB with a single Docker command: docker run -it -p 8080:8080 clidey/whodb WhoDB is in active development and thus some things will be rough around the edges. We have docs at https://github.com/clidey/whodb/blob/main/docs/docs.md and welcome any suggestions! If you find any issues, please report them here, on Github, or contact us at support@clidey.com. https://github.com/clidey/whodb