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Developers are constantly feeding context files to AI tools like Cursor, Windsurf, Copilot Workspace, and Claude Code. If your agent doesn't understand your rea
Developers are constantly feeding context files to AI tools like Cursor, Windsurf, Copilot Workspace, and Claude Code. If your agent doesn't understand your real database schema, it writes code that fails in production. LintBase acts as the bridge. It connects directly to your database, reads the ground truth of your live documents, and generates structured context optimized for AI. 🤖 Stops AI
Ground Truth for AI Coding Agents. LintBase gives AI agents real-time knowledge of your database schema, security rules, and architecture so they stop hallucinating your codebase.
npx lintbase export-context firestore --key ./service-account.json
npm version npm downloads License: MIT
Developers are constantly feeding context files to AI tools like Cursor, Windsurf, Copilot Workspace, and Claude Code. If your agent doesn't understand your real database schema, it writes code that fails in production.
LintBase acts as the bridge. It connects directly to your database, reads the ground truth of your live documents, and generates structured context optimized for AI.
lintbase check against schema snapshots.The fastest way to give your AI agent perfect database knowledge.
npx lintbase export-context firestore --key ./service-account.json
Output:
/lintbase-context/
├── database-schema.md
├── collections.md
├── security-rules.md
├── architecture.md
└── risk-report.md
Drop the lintbase-context folder into your AI's context window, or mention it in .cursorrules. Your agent will now write perfect, drift-free database queries.
Firebase Console → Project Settings → Service Accounts → Generate new private key
Save the JSON file. Never commit it to git.
LintBase acts as "Version Control for your Schema". Run the snapshot command to create a baseline:
npx lintbase snapshot firestore --key ./service-account.json
Commit .lintbase/schema.json to your repository. Then, add the check command to your CI/CD pipeline (GitHub Actions, GitLab CI):
npx lintbase check firestore --key ./service-account.json --fail-on error
If a query or deployment accidentally deletes a critical field or changes a type (e.g., string to number), your CI build will fail instantly.
npx lintbase scan firestore --key ./service-account.json
You'll see a full report in your terminal:
LintBase — Firestore Scan
─────────────────────────────────────────────
Collections scanned: 12
Documents sampled: 847
Issues found: 23 (4 errors · 11 warnings · 8 infos)
Risk score: 67 / 100 [HIGH]
ERRORS
✖ users no-auth-check Documents readable without authentication
✖ orders missing-index Query on `status` + `createdAt` has no composite index
✖ debug_logs large-collection Collection has 2.4M docs — estimated $340/mo in reads
WARNINGS
⚠ products schema-drift Field `price` found as both Number and String
⚠ sessions ttl-missing No expiry field — stale docs accumulate indefinitely
...
Track your database health over time at lintbase.com:
npx lintbase scan firestore \
--key ./service-account.json \
--save https://www.lintbase.com \
--token <your-api-token>
Get your token at lintbase.com/dashboard/settings.
npx lintbase scan firestore --key ./sa.jsonnpx lintbase scan mongodb --uri mongodb+srv://user:[email protected]/testUsing Cursor, Claude Desktop, or Windsurf? Install lintbase-mcp to give your AI agent real-time Firestore schema context — so it stops hallucinating field names.
Add to .cursor/mcp.json:
{
"mcpServers": {
"lintbase": {
"command": "npx",
"args": ["-y", "lintbase-mcp"]
}
}
}
Now when you ask your AI "add a field to users", it will check your real schema first before writing a line of code.
→ Full setup guide & tools reference
| Rule | What it detects |
|---|---|
no-auth-check |
Collections readable/writable without auth |
exposed-pii |
Email, phone, SSN fields without encryption markers |
world-readable |
Documents with overly permissive security rules |
| Rule | What it detects |
|---|---|
large-collection |
Collections with 100k+ docs and high read cost |
unbounded-query |
Queries without limit() that scan entire collections |
missing-index |
Filter combinations that fall back to full collection scans |
debug-collection |
Collections that look like temporary data that was never cleaned up |
| Rule | What it detects |
|---|---|
type-inconsistency |
Field stored as different types across documents |
missing-required-field |
Field present in 90%+ of docs but absent in some |
nullable-id |
Reference fields that are sometimes null |
| Rule | What it detects |
|---|---|
deep-nesting |
Document fields nested > 3 levels deep |
large-document |
Documents approaching the 1MB Firestore limit |
hot-document |
Single document updated by many users simultaneously |
no-pagination |
Collections without a standard pagination field |
lintbase <command> <database> [options]
Commands:
scan <database> Scan a database and print diagnostic report
export-context <database> Export schema to markdown/JSON for AI agents
snapshot <database> Generate local schema snapshot for CI comparison
check <database> Run in headless CI mode (fails on schema drift)
Options:
--key <path> Path to Firebase service account JSON
--uri <uri> MongoDB connection URI
--limit <n> Max documents to sample per collection [default: 100]
--fail-on <lvl> Fail pipeline if issues exceed severity (error, warning, info)
--save <url> Dashboard URL to save results
--token <token> API token for dashboard (from lintbase.com)
--collections Comma-separated list of collections to scan
-h, --help Show help
The CLI is free forever. The dashboard visualizes your scan results as an interactive schema map — your credentials never leave your machine.
What Pro gets you via --save:
CLI Local Tooling: 100% Free · Pro: $39/month — unlimited history, dashboards, and shared team workflow.
--limit (default 100) to prevent accidental read costs--save flag only sends the scan summary and issue list — never raw document dataMIT © Mamadou Dia
Выполни в терминале:
claude mcp add lintbase -- npx Query your database in natural language
автор: AnthropicRead-only database access with schema inspection.
автор: modelcontextprotocolInteract with Redis key-value stores.
автор: modelcontextprotocolDatabase interaction and business intelligence capabilities.
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