Firestore, browsable at last.
REST-backed document browsing and editing with SQL-like and JSON query workflows, cursor pagination, schema analysis, and emulator endpoint support.
REST API · emulator support · service accounts
The query plan Mongrel would build for your query.
Click any step below to see document reads, latency, and what Mongrel would suggest. Same inspector you get inside the workbench.
// Collection Scan · orders
The query originally failed with FAILED_PRECONDITION: 'The query requires an index.' Estimated single-field fallback: 12,483 document reads.
// orders · project prod-app-e2f1 · POST :runQuery { "structuredQuery": { "from": [{ "collectionId": "orders" }], "where": { "compositeFilter": { "op": "AND", "filters": [ { "fieldPath": "status", "op": "EQUAL", "value": "paid" }, { "fieldPath": "createdAt", "op": "GREATER_THAN", "value": "2026-06-01T00:00:00Z" } ] } }, "orderBy": [{ "fieldPath": "createdAt", "direction": "DESCENDING" }], "limit": 20 } } // 1,840ms · FAILED_PRECONDITION: "The query requires an index." // ✓ Fix: composite index written to firestore.indexes.json { "indexes": [{ "collectionGroup": "orders", "queryScope": "COLLECTION", "fields": [ { "fieldPath": "status", "order": "ASCENDING" }, { "fieldPath": "createdAt", "order": "DESCENDING" } ] }] }
What Mongrel ships for Firestore.
Document browser
Collections, subcollections, and documents in a tree. Edit fields in place with correct Firestore value types.
JSON query editor
Write structured queries as native JSON with autocomplete. Inspect the raw REST request and response side by side.
SQL-like queries
A familiar SELECT-style surface over collections and collection groups, translated to structured queries under the hood.
Query inspector
Per-query document reads and latency. Index-required errors come back as a proposed composite index, ready to deploy.
Cursor pagination
Page large collections with startAfter cursors. Forward and backward paging without pulling the whole collection.
Schema analysis
Sample documents per collection to infer field types and coverage, and flag inconsistent document shapes.
Emulator support
Point Mongrel at a local Firestore emulator endpoint. Same workbench against localhost or production projects.
Service accounts
Connect with service-account JSON keys or application default credentials. Keys are stored in the OS keychain.
Import, export, copy
NDJSON and CSV. Copy documents between projects, or between Firestore and any other engine — schema-aware.