{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"database-client","slug":"database-client","name":"Database Client","type":"extension","url":"https://marketplace.visualstudio.com/items?itemName=cweijan.vscode-database-client2","page_url":"https://unfragile.ai/database-client","categories":["data-analysis"],"tags":[],"pricing":{"model":"freemium","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"database-client__cap_0","uri":"capability://tool.use.integration.multi.database.connection.management.with.persistent.credential.storage","name":"multi-database connection management with persistent credential storage","description":"Manages connections to 10+ database systems (MySQL, PostgreSQL, SQLite, MongoDB, Redis, ClickHouse, Kafka, Snowflake, ElasticSearch, SQL Server) through a unified sidebar explorer panel. Stores connection credentials locally within VS Code's extension storage, supporting SSH tunneling for remote database access. Each connection maintains separate session state and schema cache, allowing developers to switch between databases without reconnecting.","intents":["I need to connect to multiple databases from different projects without leaving VS Code","I want to securely store database credentials and reuse them across sessions","I need to access a remote database through an SSH tunnel from my development environment"],"best_for":["full-stack developers managing multiple database backends","DevOps engineers monitoring production databases","teams using heterogeneous database stacks (MySQL + MongoDB + Redis)"],"limitations":["Credentials stored in VS Code extension storage — not encrypted at rest, relies on OS-level security","No built-in credential rotation or expiration management","SSH tunneling adds connection latency; no connection pooling for high-throughput scenarios","Schema cache becomes stale if database modified externally; requires manual refresh button click"],"requires":["VS Code 1.50+ (minimum version not officially specified)","Valid credentials for target database (username/password or connection string)","For SSH: ssh2 library support (included in extension)","Network access to database host or SSH jump server"],"input_types":["connection string","hostname/port/username/password","SSH key or password for tunneling"],"output_types":["active database connection session","schema metadata (tables, columns, indexes)"],"categories":["tool-use-integration","database-management"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"database-client__cap_1","uri":"capability://data.processing.analysis.inline.sql.query.execution.with.keyboard.shortcuts.and.result.viewing","name":"inline sql query execution with keyboard shortcuts and result viewing","description":"Executes SQL queries directly from a dedicated SQL editor window bound to a specific database connection. Supports two execution modes: (1) run selected text or current cursor line via Ctrl+Enter, (2) run entire editor buffer via Ctrl+Shift+Enter. Results render in a tabular format with pagination, sorting, and inline cell editing. Query execution happens synchronously with result streaming to the editor, and execution time is tracked.","intents":["I want to write and test SQL queries without switching to a separate database client","I need to quickly execute a single SQL statement from my current cursor position","I want to see query results in a table format and edit data directly in the results view"],"best_for":["backend developers iterating on SQL queries during development","data analysts exploring datasets without leaving their editor","QA engineers running ad-hoc test queries against staging databases"],"limitations":["No query plan visualization or EXPLAIN analysis built-in","Result pagination is manual; no automatic streaming for large result sets","Inline cell editing in results view may not support all data types (BLOBs, complex JSON)","No transaction management UI — all queries execute in autocommit mode by default","Query timeout not configurable per query; uses database server defaults"],"requires":["Active database connection established in sidebar","SQL editor tab open and bound to a database connection","Keyboard support for Ctrl+Enter and Ctrl+Shift+Enter shortcuts"],"input_types":["SQL text (SELECT, INSERT, UPDATE, DELETE, DDL statements)"],"output_types":["tabular result set with rows and columns","execution time metadata","error messages with line numbers"],"categories":["data-processing-analysis","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"database-client__cap_10","uri":"capability://tool.use.integration.ssh.tunneling.for.remote.database.access","name":"ssh tunneling for remote database access","description":"Establishes SSH tunnels to remote database servers, enabling secure access to databases behind firewalls or on private networks. SSH connection parameters (host, port, username, key/password) are configured per database connection. The extension uses the ssh2 library to establish tunnels and forwards local ports to remote database ports. Tunnels persist for the duration of the VS Code session.","intents":["I need to access a production database on a private network through a bastion host","I want to securely connect to a remote database without exposing it to the internet","I need to debug a production issue by querying the database through an SSH tunnel"],"best_for":["DevOps engineers accessing production databases securely","developers debugging issues on staging/production databases","teams with strict network security policies requiring SSH tunneling"],"limitations":["SSH tunnel latency adds 50-200ms per query due to port forwarding overhead","No connection pooling through tunnel — each query opens a new tunnel connection","SSH key authentication requires key file to be readable by VS Code process — potential security risk","Tunnel disconnection is not automatically detected — stale connections may cause query timeouts","No support for SSH agent forwarding or multi-hop tunneling"],"requires":["SSH access to bastion/jump host","SSH key or password for authentication","Network connectivity to SSH host","ssh2 library (included in extension)"],"input_types":["SSH host, port, username","SSH key file path or password","remote database host and port"],"output_types":["established SSH tunnel","local port forwarding to remote database"],"categories":["tool-use-integration","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"database-client__cap_11","uri":"capability://safety.moderation.telemetry.collection.with.opt.out.control","name":"telemetry collection with opt-out control","description":"Collects anonymous usage data (queries executed, tables accessed, features used) and sends it to the Database Client telemetry server. Telemetry is enabled by default but can be disabled via the `database-client.telemetry.usesOnlineServices` setting. Telemetry respects VS Code's global telemetry settings. No personally identifiable information is collected.","intents":["I want to help improve the extension by sharing usage data","I need to disable telemetry for compliance or privacy reasons","I want to verify that no sensitive data is being collected"],"best_for":["extension developers understanding feature usage patterns","enterprises with strict data privacy policies","users concerned about data collection"],"limitations":["Telemetry data collection is not transparent — specific data points collected are not documented","Opt-out requires manual configuration — telemetry is enabled by default","No granular control over which data points are collected","Telemetry server endpoint and data retention policy are not publicly documented"],"requires":["Network connectivity to telemetry server","VS Code 1.50+ with telemetry support"],"input_types":["extension usage (queries, tables accessed, features used)"],"output_types":["anonymous telemetry data sent to server"],"categories":["safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"database-client__cap_2","uri":"capability://code.generation.editing.sql.autocomplete.and.snippet.generation.with.database.schema.awareness","name":"sql autocomplete and snippet generation with database schema awareness","description":"Provides IntelliSense-style autocomplete for SQL keywords, table names, and column names by parsing the connected database's schema metadata. Includes pre-built SQL snippets for common patterns (SELECT, INSERT, UPDATE, DELETE, JOIN) that expand with placeholder syntax. Autocomplete triggers on typing and filters suggestions based on context (e.g., column suggestions after SELECT, table suggestions after FROM).","intents":["I want autocomplete suggestions for table and column names from my database schema","I need to quickly generate boilerplate SQL for common operations like INSERT or JOIN","I want to avoid typos in column names by using autocomplete instead of manual typing"],"best_for":["developers new to a codebase learning database schema through autocomplete","teams with large schemas (100+ tables) where manual table/column lookup is tedious","SQL developers working across multiple databases with different naming conventions"],"limitations":["Autocomplete suggestions depend on cached schema metadata; stale if database modified externally without refresh","No context-aware suggestion ranking — all matching tables/columns listed equally, no frequency-based sorting","Snippets are static templates; no dynamic parameter binding or validation","No support for database-specific functions or syntax (e.g., PostgreSQL window functions, MySQL JSON operators) — only standard SQL","Autocomplete latency increases with schema size (100+ tables may cause 200-500ms delays)"],"requires":["Active database connection with schema metadata cached","SQL editor tab open","VS Code's IntelliSense provider API support"],"input_types":["partial SQL text (e.g., 'SEL' for SELECT, 'tab' for table name)"],"output_types":["autocomplete suggestion list with table/column names","expanded SQL snippet with placeholders"],"categories":["code-generation-editing","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"database-client__cap_3","uri":"capability://data.processing.analysis.table.data.viewing.and.inline.editing.with.search.filtering","name":"table data viewing and inline editing with search filtering","description":"Displays table data in a paginated grid view with sortable columns and inline cell editing. Clicking a table name in the sidebar opens a dedicated view showing all rows with column headers. Supports full-text search across table rows (filters displayed rows in real-time), and allows direct editing of cell values by clicking and typing. Changes are committed to the database immediately (no transaction staging). Pagination controls allow navigation through large tables without loading entire dataset into memory.","intents":["I want to browse and search table data without writing SELECT queries","I need to quickly edit a few rows in a table without using UPDATE statements","I want to see all columns and rows in a table with sorting and filtering"],"best_for":["database administrators performing quick data corrections","developers debugging data issues in development/staging databases","non-technical stakeholders viewing database contents without SQL knowledge"],"limitations":["Inline editing commits changes immediately with no undo/rollback — risky for production data","Search is full-text only; no advanced filtering by column type or range queries","Pagination is manual; no automatic loading of next page when scrolling to bottom","Large tables (1M+ rows) may cause UI lag when loading first page","No support for editing BLOB, JSON, or complex data types inline — requires external tools","No bulk edit operations — must edit cells one at a time"],"requires":["Active database connection","Table selected in sidebar explorer","Read+Write permissions on target table (for editing)"],"input_types":["table name selection from sidebar"],"output_types":["paginated grid view with rows and columns","search results filtered by keyword","updated database rows after inline edits"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"database-client__cap_4","uri":"capability://memory.knowledge.database.schema.visualization.and.navigation.with.hierarchical.explorer","name":"database schema visualization and navigation with hierarchical explorer","description":"Displays database structure as a hierarchical tree in the sidebar explorer, showing databases → tables → columns → indexes. Each node is clickable to open corresponding views (table data, column details). The explorer caches schema metadata locally to avoid repeated database queries. Supports collapsing/expanding nodes to navigate large schemas. Right-click context menus on tables provide quick actions (view data, backup, import, generate mock data).","intents":["I want to understand the structure of a database I'm unfamiliar with","I need to quickly navigate to a specific table without remembering its exact name","I want to see all columns and their types for a table at a glance"],"best_for":["developers onboarding to new projects with unfamiliar database schemas","database architects documenting schema structure","teams with large schemas (100+ tables) requiring visual navigation"],"limitations":["Schema cache is static — does not reflect real-time changes made by other users or external tools","No schema search/filter — must manually expand nodes to find tables in large databases","No schema diff or version history — cannot compare schema changes over time","Hierarchical view may be slow to render for databases with 1000+ tables","No support for viewing constraints, triggers, or stored procedures in the explorer"],"requires":["Active database connection","Schema metadata loaded and cached"],"input_types":["database connection selection"],"output_types":["hierarchical tree view of schema structure","column type information","table metadata (row count, size)"],"categories":["memory-knowledge","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"database-client__cap_5","uri":"capability://code.generation.editing.sql.formatting.and.syntax.validation","name":"sql formatting and syntax validation","description":"Automatically formats SQL code in the editor using the sql-formatter library, supporting indentation, keyword capitalization, and line breaks. Triggered via command palette or keyboard shortcut. Validates SQL syntax against the target database's dialect (MySQL, PostgreSQL, etc.) and highlights errors inline in the editor. Syntax validation runs on save or on-demand and provides error messages with line numbers.","intents":["I want to auto-format messy SQL to match team style guidelines","I need to catch SQL syntax errors before executing queries","I want consistent SQL formatting across my team without manual review"],"best_for":["teams with SQL style guides enforcing consistent formatting","developers catching syntax errors early in the development cycle","large SQL files that are difficult to read without formatting"],"limitations":["Formatting is opinionated — may not match all team style preferences; limited customization options","Syntax validation is basic — does not check semantic errors (e.g., referencing non-existent columns)","Database-specific syntax (e.g., PostgreSQL CTEs, MySQL JSON functions) may not format correctly","Formatting changes are applied immediately without preview or undo option","No support for formatting stored procedures or complex multi-statement scripts"],"requires":["SQL editor tab open","sql-formatter library (included in extension)"],"input_types":["SQL text in editor"],"output_types":["formatted SQL with consistent indentation and spacing","syntax error highlights with line numbers"],"categories":["code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"database-client__cap_6","uri":"capability://memory.knowledge.query.history.tracking.and.reuse","name":"query history tracking and reuse","description":"Maintains a history of all executed SQL queries within the current session and across sessions (persisted to extension storage). Clicking the history button in the SQL editor opens a list of recent queries sorted by execution time. Selecting a query from history inserts it into the current editor or opens it in a new tab. History entries include execution timestamp, execution time, and result row count.","intents":["I want to re-run a query I executed earlier without retyping it","I need to see which queries I've run and how long they took","I want to compare performance of similar queries by reviewing execution times"],"best_for":["developers iterating on query optimization","analysts running recurring queries across multiple sessions","teams auditing which queries were executed and when"],"limitations":["History is stored in VS Code extension storage — limited to ~10MB per extension, may be pruned for old entries","No search or filtering within history — must scroll through list to find queries","History is per-user per-machine — not shared across team members","No query tagging or categorization — all queries in a flat list","Execution time tracking is client-side only — does not include database server processing time"],"requires":["SQL editor with executed queries","VS Code extension storage available"],"input_types":["executed SQL queries"],"output_types":["history list with query text, timestamp, execution time","query text inserted into editor on selection"],"categories":["memory-knowledge","search-retrieval"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"database-client__cap_7","uri":"capability://automation.workflow.database.backup.and.export.with.native.tool.integration","name":"database backup and export with native tool integration","description":"Exports database contents to backup files (SQL dumps, CSV, JSON) via right-click context menu on tables or databases. Supports two modes: (1) native extension backup using database client libraries (unstable, not recommended), (2) integration with native tools (mysql_dump for MySQL, pg_dump for PostgreSQL) if available in system PATH. Export format and compression options are configurable. Backup files are saved to user-selected directory.","intents":["I want to create a backup of a database before making schema changes","I need to export table data to CSV or JSON for analysis in another tool","I want to automate database backups without leaving VS Code"],"best_for":["developers backing up development databases before risky operations","DBAs performing manual backups of non-critical databases","data analysts exporting subsets of data for external processing"],"limitations":["Native extension backup is unstable and not recommended for production use — use mysql_dump or pg_dump instead","No scheduling or automation — backups must be triggered manually","No incremental backups — each backup is a full export","Large databases (>1GB) may cause UI freezing during export","No backup verification or integrity checking","Requires mysql_dump/pg_dump to be installed and in system PATH for reliable backups"],"requires":["Active database connection with backup permissions","Write access to target directory for backup files","For MySQL: mysql_dump in system PATH (recommended)","For PostgreSQL: pg_dump in system PATH (recommended)"],"input_types":["database or table selection from sidebar"],"output_types":["SQL dump file (.sql)","CSV export file (.csv)","JSON export file (.json)"],"categories":["automation-workflow","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"database-client__cap_8","uri":"capability://data.processing.analysis.data.import.from.files.with.format.detection","name":"data import from files with format detection","description":"Imports data from external files (SQL, CSV, JSON) into tables via right-click context menu. Detects file format automatically and parses accordingly. For SQL files, executes statements directly. For CSV/JSON, maps columns to table schema and inserts rows. Supports batch import of multiple files. Progress indicator shows import status and row count.","intents":["I want to populate a development database with test data from a CSV file","I need to restore a database from a SQL dump file","I want to import data from an external source (API export, spreadsheet) into my database"],"best_for":["developers setting up test databases with seed data","data engineers loading external datasets into databases","teams migrating data between database systems"],"limitations":["No data validation or type checking before import — invalid data may cause import failures","CSV import assumes first row is header — no support for headerless CSVs","Large files (>100MB) may cause memory issues or UI freezing","No transaction support — partial imports may leave database in inconsistent state on failure","Column mapping is automatic; no manual mapping UI for mismatched schemas","No duplicate detection or conflict resolution — may insert duplicate rows"],"requires":["Active database connection with insert permissions","Import file in supported format (SQL, CSV, JSON)","Table schema must exist before import"],"input_types":["SQL file (.sql)","CSV file (.csv)","JSON file (.json)"],"output_types":["imported rows in target table","import status and row count"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"database-client__cap_9","uri":"capability://data.processing.analysis.mock.data.generation.for.testing","name":"mock data generation for testing","description":"Generates synthetic test data for tables via right-click context menu. Supports multiple data types (strings, numbers, dates, emails, phone numbers) with configurable patterns and ranges. Generated data is inserted directly into the table. Allows specifying row count and seed value for reproducible data generation.","intents":["I want to populate a development database with realistic test data without manual entry","I need to generate large datasets for performance testing","I want reproducible test data by using a fixed seed value"],"best_for":["developers testing application features with realistic data volumes","QA engineers generating test datasets for performance testing","teams needing repeatable test data across multiple test runs"],"limitations":["Mock data generation patterns are limited — no support for custom generators or complex relationships","No foreign key constraint awareness — may generate invalid references to other tables","Large row counts (1M+) may cause database performance issues or UI freezing","Generated data is random (except with seed) — may not reflect real-world data distributions","No support for generating data that matches specific business rules or validation constraints"],"requires":["Active database connection with insert permissions","Table schema must exist with defined columns"],"input_types":["table selection from sidebar","row count parameter","optional seed value for reproducibility"],"output_types":["generated rows inserted into table","generation status and row count"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"database-client__headline","uri":"capability://data.processing.analysis.universal.database.client.for.vs.code","name":"universal database client for vs code","description":"A versatile database client extension for Visual Studio Code that supports MySQL, PostgreSQL, SQLite, MongoDB, and Redis, featuring a query editor with autocomplete, table viewer, and schema visualization, making database management seamless within the IDE.","intents":["best database client for VS Code","database management tool for developers","VS Code extension for SQL editing","universal database client for multiple databases","database query editor with autocomplete"],"best_for":["developers using VS Code","teams managing multiple database types"],"limitations":["may have access limitations based on VS Code sandboxing"],"requires":["Visual Studio Code"],"input_types":["SQL queries","database connection details"],"output_types":["query results","table views"],"categories":["data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":57,"verified":false,"data_access_risk":"high","permissions":["VS Code 1.50+ (minimum version not officially specified)","Valid credentials for target database (username/password or connection string)","For SSH: ssh2 library support (included in extension)","Network access to database host or SSH jump server","Active database connection established in sidebar","SQL editor tab open and bound to a database connection","Keyboard support for Ctrl+Enter and Ctrl+Shift+Enter shortcuts","SSH access to bastion/jump host","SSH key or password for authentication","Network connectivity to SSH host"],"failure_modes":["Credentials stored in VS Code extension storage — not encrypted at rest, relies on OS-level security","No built-in credential rotation or expiration management","SSH tunneling adds connection latency; no connection pooling for high-throughput scenarios","Schema cache becomes stale if database modified externally; requires manual refresh button click","No query plan visualization or EXPLAIN analysis built-in","Result pagination is manual; no automatic streaming for large result sets","Inline cell editing in results view may not support all data types (BLOBs, complex JSON)","No transaction management UI — all queries execute in autocommit mode by default","Query timeout not configurable per query; uses database server defaults","SSH tunnel latency adds 50-200ms per query due to port forwarding overhead","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.7,"quality":0.9,"ecosystem":0.15000000000000002,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:21.548Z","last_scraped_at":null,"last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=database-client","compare_url":"https://unfragile.ai/compare?artifact=database-client"}},"signature":"CfJ9vDTzBy/nv1xjg0W84JHx1iaCUlNHmLdd8oKLQ5E1dOH74LzHPvG3+YxXSsPttwU38Tui9y0tr8FcGgIRCg==","signedAt":"2026-06-21T16:37:23.005Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/database-client","artifact":"https://unfragile.ai/database-client","verify":"https://unfragile.ai/api/v1/verify?slug=database-client","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}