MongrelDB Viewer

A desktop Signal Deck for MongrelDB.
Inspect schemas and indexes, browse rows, run SQL, build dense ANN search, chat through an OpenAI-compatible model, and expose the open database over MCP.

MongrelDB Viewer is free and open source. Use it as a local vector database GUI or expose the open database through its local vector database MCP server.

What it does

MongrelDB Viewer has two connection modes:

Capability	Direct folder	mongreldb-server
Open style	Embedded, exclusive filesystem lock	Multi-client HTTP
Browse schema and rows	Yes	Yes
Run SQL, DDL, and DML	Yes	Yes, when the server permits it
Show foreign-key graph	Yes	Not exposed by the current server adapter
Native retrieve_text provenance	Yes	No, SQL ANN fallback
Install, backfill, or rebuild ANN from the UI	Yes	No
Run REINDEX	Yes	Sent as server SQL
Agent and in-app MCP	Yes	Yes
Catalog credentials and encryption passphrase	Yes	Server auth only

Direct mode uses mongreldb-core and mongreldb-query in the application process. Server mode uses mongreldb-client against a running daemon. See connection modes before opening production data.

Gallery

Screenshots use the bundled six-table demo database.

Deck	Schema map

Table browser	SQL workbench

Vector search	Agent chat

MCP bridge	About

Install

Download a package, when attached, from GitHub Releases. If no package matches your platform, build from source:

git clone https://github.com/visorcraft/MongrelDB-Viewer.git
cd MongrelDB-Viewer
npm ci
npm run tauri build

Source builds need Rust 1.88+, Node.js 22+, and the native libraries required by Tauri 2. Bundles are written below src-tauri/target/release/bundle/.

See installation and builds for platform prerequisites, development mode, Linux display behavior, upgrades, and model downloads.

Five-minute tour

npm ci
npm run tauri dev

Then:

1. Leave Direct folder selected.
2. Choose an empty directory.
3. Click Create demo DB.
4. Open Deck, Stars, Table, and SQL.
5. In ANN, search hybrid retrieval across indexes.

Demo creation writes six tables, foreign keys, representative secondary indexes, a 384-dimensional embedding column, and dense HNSW ANN. The first run may download all-MiniLM-L6-v2. If the download is unavailable, demo creation can fall back to zero vectors; use Re-embed from text column after the model becomes available.

The demo button hides after its first successful use. Reopen the demo through Recent or Direct folder on later launches. The complete walkthrough and schema are in first launch and demo.

Product surfaces

Surface	Purpose
Deck	Connection metadata, table and row totals, index capabilities, live insights, and schema-derived SQL recipes
Stars	Pan and zoom graph of database, tables, columns, indexes, and Direct-mode foreign keys
Table	Column types and flags, embedding source, index options, row samples, and REINDEX
SQL	MongrelDB/DataFusion workbench with recipes, in-memory history, result grid, and CSV copy
ANN	Direct-mode ANN install/rebuild/backfill and table-scoped semantic search
Agent	OpenAI Chat Completions-compatible tool loop over the current database
MCP	Local HTTP JSON-RPC server or separate stdio process with the same tool surface
About	Product metadata, complete license texts, dependency credits, and runtime notices

The Viewer recognizes all six public MongrelDB secondary-index families: Bitmap, LearnedRange/PGM, FM, ANN, Sparse, and MinHash.

Safety before use

• SQL, Agent, and MCP tools are not read-only. They can run DDL, DML, REINDEX, and ANN installation without a per-statement confirmation dialog.
• Direct mode owns an exclusive database lock. Disconnect before another exclusive process opens the root, and disconnect before filesystem backups.
• The in-app MCP endpoint has no authentication. The UI binds it to 127.0.0.1; any local process that can reach the port can invoke its tools.
• Clicking Save in Agent stores the base URL and model in WebView localStorage. The API key remains in process memory and is cleared on exit.
• Prompts and tool results sent to a remote chat endpoint can contain database data.

Read the security policy and operations guide for the full trust model and local-data inventory.

Documentation

Start here:

• Documentation index
• Installation and builds
• First launch and demo
• Direct and server connections

Use the application:

• Deck
• Schema map
• Table browser and maintenance
• SQL workbench
• Vector search and ANN
• Agent chat
• MCP bridge
• About, licenses, and credits

Operate and extend it:

• Configuration, local data, and troubleshooting
• Architecture and internal interfaces
• Contributing
• Security

Architecture at a glance

React + TypeScript
       |
       | Tauri invoke
       v
Rust command layer
       |
       +-- Direct: mongreldb-core + mongreldb-query
       |
       +-- Server: mongreldb-client + HTTP
       |
       +-- Embeddings: fastembed MiniLM
       |
       +-- Shared tools: Agent chat + MCP HTTP/stdio

The active connection and embedding hub are shared by SQL, Agent, and in-app MCP. Stdio MCP is a separate process and must open its own Direct or Server connection. See architecture for lifetimes, data flows, trust boundaries, source layout, and extension points.

Development gate

npm ci
npm run build
cargo fmt --manifest-path src-tauri/Cargo.toml --check
cargo clippy --manifest-path src-tauri/Cargo.toml --all-targets --all-features -- -D warnings
cargo test --manifest-path src-tauri/Cargo.toml

Dependency changes also require:

scripts/regen-credits.sh

Full workflow: CONTRIBUTING.md.

Support and policy

• Bugs and feature requests: GitHub Issues
• Vulnerabilities: use private reporting described in SECURITY.md
• MongrelDB engine questions: visorcraft/MongrelDB

Related tools

• Mongrel — Commercial multi-system workbench with native MongrelDB support.
• MongrelDB Viewer — Free, open-source MongrelDB GUI and MCP server.

License

MongrelDB Viewer is available under MIT OR Apache-2.0. See LICENSE-MIT and LICENSE-APACHE.