Mongrel database and systems workbench.
Query the database. Check the API. Open the shell. Inspect the container or cluster. Keep the trail in one place - across 30+ database engines, with an opt-in AI assistant and MCP tools when you want a second pair of eyes.
Real debugging crosses tool boundaries.
Queries, logs, containers, SSH sessions, and terminals are all part of the same debugging story. Mongrel brings them into a focused workspace, so you can follow the problem without constantly switching context.
The query is only the first move
Real debugging jumps from rows to logs, shells, files, containers, and clusters.
Context switching breaks momentum
Mongrel keeps the trail in one place while the work moves across systems.
Production work needs guardrails
Secrets belong in the keychain. Writes should be intentional. Exports should not leak credentials.
Start with the row. Finish with the cause.
Connect to the system, inspect the data, follow it to the service, validate the request, then make the next move.
Run the query, inspect the result, then keep going.
Browse, edit, explain, visualize, compare, migrate, back up, restore, import, export, and sync data across the engines you already run.
Built for where database work actually goes.
Mongrel covers databases, endpoints, remote hosts, files, containers, and clusters because real investigations cross those borders.
Database workbench
Relational, document, key-value, search, edge, and analytical engines, including MongoDB, PostgreSQL, Oracle, BigQuery, Snowflake, D1, Redis, and more.
AI assistant with MCP
Opt-in assistant for any OpenAI-compatible provider, Anthropic, or Google Gemini. Reviewed MCP tools, proposal-first behavior near production, keys in the OS keychain.
Deep result exploration
Paged grids, document cards, faceted filters, quick aggregations, FK drill-down, dashboards, notebooks, and inspectors.
Schema and admin tooling
Profiles, index management, relationship graphs, ER diagrams, roles, grants, logs, process lists, and health panels.
Remote operations
SSH, Mosh, Telnet, Serial, and local terminals with logging, quick commands, themes, search, triggers, and replay.
Containers and clusters
Docker/Podman lifecycle, logs, stats, file browsers, exec terminals, Kubernetes workloads, events, metrics, Helm, and CRDs.
API client included
HTTP/REST, GraphQL, WebSocket, and gRPC with environments, secret variables, OAuth, mTLS, examples, and import/export.
Connection sync workflows
Workspace grouping, session restore, connection registry, git-backed sync, review flows, conflict resolution, and audit reporting.
Safety built into the flow
Keychain storage, stripped exports, production guards, explicit write gates, and reason prompts where configured.
Bring the stack you already have.
Mongrel connects to existing databases, endpoints, remote hosts, files, containers, and clusters. It does not ask you to rebuild the shop.
Fast enough when paged. Careful enough near real data.
Production tools need boring rules: keep secrets out of files, make risky writes explicit, and leave an audit trail when it matters.
Secrets stay where they belong
Passwords and secret values live in the OS keychain, with optional master-password protection for stored secrets.
Exports do not casually leak credentials
Profiles, API bundles, and sync payloads strip credentials by default so sharing does not become a security incident.
Risky actions are explicit
High-impact writes can require gates and reason prompts, keeping speed high without turning production into a minefield.
One app for the people who own it all.
Developers
Keep code, query analysis, API checks, terminal access, and environment debugging in one loop.
Database and SQL analysts
Analyze across multiple engines, compare environments, validate migrations, and export data without client sprawl.
SRE and platform teams
Jump from query symptoms to service validation, shell actions, cluster state, and guarded incident response.
Plans for every team size
Download for free and try for 7 days - no credit card required.
Individual
For one developer or operator using Mongrel across a personal workstation and one secondary machine.
Team
For small teams that need shared access without sharing one license key across the group.
Business
For departments standardizing database, infrastructure, and request workflows across a larger group.
Educators
For classrooms, labs, and training programs that need broad access at a lower annual price.
Frequently Asked Questions
Is Mongrel just another database client?
No. A database client stops at the query. Mongrel follows the question into APIs, shells, files, containers, and Kubernetes when that is where the cause lives.
Which databases does Mongrel support?
More than 30 engines, including Oracle, SQL Server, Db2, Informix, SAP SQL Anywhere, Snowflake, PostgreSQL, MySQL/MariaDB, SQLite, MongoDB, DynamoDB, Firestore, Redis/Valkey, ClickHouse, DuckDB, and Elasticsearch/OpenSearch. Most engines ship as signed first-party database plugins, and Mongrel connects to services you already run - it does not provision databases. The Databases page lists every supported engine.
Can I use my own AI provider?
Yes. The optional AI assistant works with any OpenAI API-compatible endpoint as well as Anthropic and Google Gemini, and API keys stay in the OS keychain. A built-in MCP client lets you expose reviewed tools from your own MCP servers to the chat. The AI page covers providers, MCP, and the safety model.
Who is the $99/year plan for?
Individual developers, database/SQL analysts, sysadmins, SREs, and platform engineers who are tired of stitching together a pile of separate tools.
How do downloads and licenses work?
Checkout, license issuance, protected downloads, and subscription status are handled server-side. The portal gives customers account-bound license access, installers when releases are published, billing entry points, and database-backed support tickets.
Put the database workflow in one serious desktop.
When a database question becomes a systems question, stay with it. Mongrel keeps the path in one app.