接入你的智能体
發布者自己的指令。不是 PlugMCP 端點。
用我們的金鑰與日誌託管一份副本。
npx -y [email protected]Claude Code 沒有本機指令的安裝連結。複製下方指令並在終端機中執行。
claude mcp add io.github.madia333-lintbase-mcp -- npx -y lintbase-mcp@0.1.3在終端機中執行。
{ "mcpServers": { "io.github.madia333-lintbase-mcp": { "command": "npx", "args": [ "-y", "[email protected]" ] } }}claude_desktop_config.json
遠端 URL 還是本機指令？ 兩種安裝方式的差異
來自發布者
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
Real-time Firestore schema context for AI coding agents. Stop hallucinating field names.
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.Because in document databases, the code lies. The real schema is whatever your live documents actually contain, and that drifts away from the code with every half-finished migration, every renamed field, and every previous AI session that wrote in a hurry. An agent inferring the schema from TypeScript interfaces writes plausible queries against a database that no longer exists. The failure is silent: empty results, undefined values, a new field variant living alongside the old one. LintBase reads the documents, not the code.
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.
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]
--max-depth <n> Firestore: tiers to recurse into subcollections
(1 = top-level only) [default: 2]
--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
Real-time Firestore schema context for AI coding agents. Stop hallucinating field names.
{ "mcpServers": { "io.github.madia333-lintbase-mcp": { "command": "npx", "args": [ "-y", "[email protected]" ] } }}工具
尚無工具清單。遠端伺服器會在首次健康檢查後取得工具清單。
常見問題
在本頁複製適用於 Cursor、Claude Desktop、Claude Code 或 VS Code 的 stdio 設定。它使用發布者的安裝方式，而不是 PlugMCP 代理伺服器。
這筆記錄未列出必要的環境變數。
Lintbase 透過 stdio 在本機執行。
上次檢查時間：2026-11-09。 Real-time Firestore schema context for AI coding agents. Stop hallucinating field names.