QiVo Studio

Deterministic column-level lineage for Oracle SQL and PL/SQL: where every column comes from, what a change will hit, and what the code really does, including dynamic SQL. Nothing is guessed: what cannot be decided from the code is reported as a gap, with the reason.

This is the Explorer edition: one person, one machine, no database needed.

pip install qivo-studio
qivo serve

Then open the address it prints, usually http://127.0.0.1:8000/app. If port 8000 is busy, it uses the next free port (8001, 8002, ...) and says so. To choose a port: qivo serve --port 8080 (or set QIVO_PORT=8080).

Explore a bundled example estate, or upload your own scripts (DDL, packages, procedures, triggers, SQL*Plus scripts, a zip). Your code never leaves your machine: the app listens on this machine only, and its data (an embedded PostgreSQL) is kept in ~/.qivo.

• Oracle 12.2 to 23ai/26ai: SQL, PL/SQL, conditional compilation, SQL*Plus scripts
• Lineage through PL/SQL variables, records, collections, cursors and parameters, across units
• Dynamic SQL resolved from constants, branches, control tables and call sites
• Code tools: parser, syntax tree, names (what every identifier is), lineage, dynamic SQL
• Python 3.12 or later; Linux (x86-64, ARM), macOS (Intel, Apple silicon), Windows (x64)

Use with AI tools (MCP)

QiVo MetaGraph, the CodeBase Ontology, serves the proven facts of your code (lineage, joins, dynamic SQL, gaps, findings, glossary) to AI tools through MCP, read only. Every analysis in the app builds it, so there is nothing to prepare: let your AI tool start qivo mcp on this machine. No token and no server address are needed.

claude mcp add qivo -- qivo mcp  # Claude Code; Claude Desktop and VS Code: command "qivo", args ["mcp"]
qivo graph build <scan>          # only for a scan analysed by a version before 0.1.2 (the id is shown in the app)

Every answer names its evidence and proof level; what could not be proven is reported as a gap, never guessed. If the tool cannot find qivo, give its full path (which qivo). On QiVo Cloud and self-hosted servers, AI tools connect to <server>/mcp with a personal access token instead: https://qivo.studio/docs/mcp.

For teams and whole estates (live Oracle connections, Git, schedulers, a sandbox for probing dynamic SQL, sign-in and single sign-on), the Enterprise edition runs with Docker or Kubernetes. See https://qivo.studio.

QiVo Studio is free to use under its licence agreement; it is not open source. Questions and issues: https://github.com/qivo-studio/qivo-studio/issues