Plugin System & Custom Drivers

While Tabularis supports major relational databases natively via Rust, the ecosystem of data stores is vast. The Plugin System allows anyone to add support for external databases (like DuckDB, ClickHouse, or Redis) using any programming language.

For the complete protocol reference, see plugins/PLUGIN_GUIDE.md in the repository.

Architecture: JSON-RPC over STDIO

Tabularis avoids dynamic linking (.so or .dll files) for plugins, which can cause version conflicts and security issues. Instead, plugins are standalone executables — a binary or a script — that run as child processes.

When a user opens a connection using a plugin driver, Tabularis:

1. Spawns the plugin executable as a child process.
2. Sends JSON-RPC 2.0 request objects to the plugin's stdin, one per line.
3. Reads JSON-RPC 2.0 response objects from the plugin's stdout, one per line.
4. Reuses the same process instance for the entire session.

Any output written to stderr is captured by Tabularis and shown in the log viewer — safe to use for debugging without breaking the protocol.

Directory Structure

A plugin is distributed as a .zip file. When extracted into the Tabularis plugins folder, it must follow this layout:

plugins/
└── duckdb/
    ├── .tabularium          (or legacy manifest.json)
    └── duckdb-plugin        (or duckdb-plugin.exe on Windows)

Plugin folder locations:

The Manifest (.tabularium)

Every plugin ships one manifest that tells Tabularis its capabilities and the data types it supports. Its canonical name is .tabularium — one file at the plugin root that serves both the host (loading the driver) and the Tabularium registry (listing it). The host still reads a legacy manifest.json as a fallback, where id and a display name remain valid; in a .tabularium, name is the lowercase slug and identifies the plugin. The full field reference with all constraints lives at docs.tabularium.wiki/manifest.

{
  "$schema": "https://registry.tabularis.dev/manifest.schema.json?kind=driver",
  "name": "duckdb",
  "version": "1.0.0",
  "description": "DuckDB file-based analytical database",
  "default_port": null,
  "executable": "duckdb-plugin",
  "capabilities": {
    "schemas": false,
    "views": true,
    "routines": false,
    "file_based": true,
    "identifier_quote": "\"",
    "alter_primary_key": false
  },
  "data_types": [
    { "name": "INTEGER",  "category": "numeric", "requires_length": false, "requires_precision": false },
    { "name": "VARCHAR",  "category": "string",  "requires_length": true,  "requires_precision": false },
    { "name": "BOOLEAN",  "category": "other",   "requires_length": false, "requires_precision": false },
    { "name": "TIMESTAMP","category": "date",    "requires_length": false, "requires_precision": false }
  ]
}

Capabilities

Data Type Categories

Type Mappings

The optional type_mappings manifest field declares how generic inferred type names map to driver-native types. It is used during paste/import, where Tabularis infers column types from the data (e.g. detects a date column as DATETIME) and needs the driver-native equivalent. The mapping is static in the manifest and resolved by the host — no RPC round-trip.

{
  "type_mappings": {
    "DATETIME": "TIMESTAMP",
    "JSON": "JSONB"
  }
}

Keys are uppercase generic type names; the lookup is case-insensitive. Types without a mapping (or an omitted type_mappings) pass through unchanged.

Plugin Settings

Plugins can declare custom configuration fields in their manifest. Tabularis renders these fields in Settings → gear icon next to the plugin. Users fill them in, the values are persisted in config.json, and Tabularis delivers them to the plugin at startup.

Declaring settings in the manifest

Add an optional settings array to your manifest:

{
  "name": "my-plugin",
  "settings": [
    {
      "key": "api_key",
      "label": "API Key",
      "type": "string",
      "required": true,
      "description": "Your API key for authentication."
    },
    {
      "key": "region",
      "label": "Region",
      "type": "select",
      "options": ["us-east-1", "eu-west-1"],
      "default": "us-east-1"
    },
    {
      "key": "max_connections",
      "label": "Max Connections",
      "type": "number",
      "default": 10
    },
    {
      "key": "ssl",
      "label": "Enable SSL",
      "type": "boolean",
      "default": true
    }
  ]
}

Supported setting types: "string", "boolean", "number", "select".

The initialize call

After spawning the plugin process, Tabularis immediately sends an initialize JSON-RPC call with the user's saved settings:

{
  "jsonrpc": "2.0",
  "method": "initialize",
  "params": { "settings": { "api_key": "abc", "region": "eu-west-1" } },
  "id": 1
}

Returning an error from initialize is safe — Tabularis ignores it silently. Plugins that do not implement initialize are completely unaffected.

Plugin settings are stored under the top-level plugins key in config.json, keyed by plugin ID.

For the full developer reference (field schema, code examples in Rust and Python), see the Plugin Guide.

Protocol Specification

Your plugin runs a continuous read loop on stdin. For each line received, parse the JSON-RPC request, execute the operation, and write a JSON-RPC response to stdout followed by \n.

Request format

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "get_tables",
  "params": {
    "params": {
      "driver": "duckdb",
      "host": null,
      "port": null,
      "database": "/path/to/my.duckdb",
      "username": null,
      "password": null,
      "ssl_mode": null
    },
    "schema": null
  }
}

The params.params object (a ConnectionParams) contains the values the user entered in the connection form. Additional fields at the top level of params are method-specific (e.g. schema, table, query).

Optional AI schema context

External drivers automatically participate in AI Query Assist when they implement the standard get_tables, get_columns, and get_foreign_keys metadata methods. The host limits the selected tables and builds the final system prompt, so plugins do not need to know which AI provider the user configured.

Drivers with an efficient batch metadata API can additionally implement get_ai_schema_context:

{
  "jsonrpc": "2.0",
  "id": 12,
  "method": "get_ai_schema_context",
  "params": {
    "params": { "driver": "my-driver", "database": "app" },
    "schema": "public",
    "max_tables": 20
  }
}

Return a result shaped as { "tables": [{ "name", "columns", "foreign_keys" }], "total_table_count": 42 }. Respect max_tables while reporting the pre-limit count in total_table_count. If the method is not implemented, return -32601; Tabularis automatically falls back to the standard metadata calls, keeping existing plugins compatible.

Successful response

{
  "jsonrpc": "2.0",
  "id": 1,
  "result": [
    { "name": "users", "schema": "main", "comment": null }
  ]
}

Error response

{
  "jsonrpc": "2.0",
  "id": 1,
  "error": {
    "code": -32603,
    "message": "Database file not found."
  }
}

Standard error codes:

Required Methods

Your plugin must implement at minimum the following methods. For unimplemented optional methods, return an empty array [] or a -32601 error.

test_connection

Verify that a connection can be established.

Params: { "params": ConnectionParams }

Result: { "success": true } or an error response.

ping (optional)

Lightweight health check called periodically on active connections. Tabularis pings every active connection at a configurable interval (default: 30 seconds). After 2 consecutive failures, the connection is automatically disconnected and the user is notified.

Params: { "params": ConnectionParams }

Result: null on success, or an error response if the connection is dead.

If not implemented, Tabularis falls back to test_connection. Implementing ping is recommended when your plugin can do a cheaper liveness check than a full connection test.

get_databases

List available databases.

Params: { "params": ConnectionParams }

Result: ["db1", "db2"]

get_tables

List tables in a schema/database.

Params: { "params": ConnectionParams, "schema": string | null }

Result:

[{ "name": "users", "schema": "main", "comment": null }]

get_columns

Get column metadata for a table.

Params: { "params": ConnectionParams, "schema": string | null, "table": string }

Result:

[
  {
    "name": "id",
    "data_type": "INTEGER",
    "is_nullable": false,
    "column_default": null,
    "is_primary_key": true,
    "is_auto_increment": true,
    "comment": null
  }
]

execute_query

Execute a SQL query and return results.

Params:

{
  "params": ConnectionParams,
  "query": "SELECT * FROM users",
  "limit": 100,
  "page": 1,
  "schema": null
}

Result:

{
  "columns": ["id", "name"],
  "rows": [[1, "Alice"]],
  "total_count": 1,
  "execution_time_ms": 5
}

Materialized Views (optional)

Declare materialized_views: true in capabilities to enable the UI. If the plugin returns -32601 (method not found), the host falls back to empty results for get_materialized_views and get_materialized_view_columns; get_materialized_view_definition and refresh_materialized_view surface a "not supported by this driver" error instead.

BLOB Operations (optional)

If the plugin returns -32601, the host shows "BLOB export/preview not supported".

• save_blob_to_file — params { "params", "table", "col_name", "pk_map", "schema", "file_path" }. The plugin queries the binary value via the PK map and writes the raw bytes to file_path itself (it runs on the same machine as the host). Returns null on success.
• fetch_blob_as_data_url — params { "params", "table", "col_name", "pk_map", "schema" }. Returns the value in the BLOB wire format "BLOB:<size_bytes>:<mime_type>:<base64_data>" for preview in the row editor.

For the full list of methods (CRUD, DDL, views, routines, triggers, batch/ER diagram methods), see the complete plugin guide.

Minimal Skeleton (Rust)

use std::io::{self, BufRead, Write};
use serde_json::{json, Value};

fn main() {
    let stdin = io::stdin();
    let mut stdout = io::stdout();

    for line in stdin.lock().lines() {
        let line = line.unwrap();
        if line.trim().is_empty() { continue; }

        let req: Value = match serde_json::from_str(&line) {
            Ok(v) => v,
            Err(_) => continue,
        };

        let id = req["id"].clone();
        let method = req["method"].as_str().unwrap_or("");
        let params = &req["params"];
        let response = dispatch(method, params, id);

        let mut res_str = serde_json::to_string(&response).unwrap();
        res_str.push('\n');
        stdout.write_all(res_str.as_bytes()).unwrap();
        stdout.flush().unwrap();
    }
}

fn dispatch(method: &str, _params: &Value, id: Value) -> Value {
    match method {
        "test_connection" => json!({
            "jsonrpc": "2.0", "result": { "success": true }, "id": id
        }),
        // Optional: lightweight health check (called periodically).
        // If omitted, Tabularis falls back to test_connection.
        "ping" => json!({
            "jsonrpc": "2.0", "result": null, "id": id
        }),
        "get_databases" => json!({
            "jsonrpc": "2.0", "result": ["my_database"], "id": id
        }),
        "get_tables" => json!({
            "jsonrpc": "2.0",
            "result": [{ "name": "example", "schema": null, "comment": null }],
            "id": id
        }),
        "execute_query" => json!({
            "jsonrpc": "2.0",
            "result": {
                "columns": ["id"], "rows": [[1]],
                "total_count": 1, "execution_time_ms": 1
            },
            "id": id
        }),
        _ => json!({
            "jsonrpc": "2.0",
            "error": { "code": -32601, "message": format!("Method '{}' not implemented", method) },
            "id": id
        }),
    }
}

Testing Your Plugin

You can test your plugin directly from the shell before installing it in Tabularis:

echo '{"jsonrpc":"2.0","method":"test_connection","params":{"params":{"driver":"duckdb","database":"/tmp/test.duckdb","host":null,"port":null,"username":null,"password":null,"ssl_mode":null}},"id":1}' \
  | ./duckdb-plugin

You should see a valid JSON-RPC response on stdout.

Installing Locally

1. Create the plugin directory inside the Tabularis plugins folder:

   ~/.local/share/tabularis/plugins/myplugin/   (Linux)
   

2. Place your .tabularium (or legacy manifest.json) and the compiled executable there.
3. On Linux/macOS, make it executable: chmod +x myplugin
4. Open Tabularis and refresh the plugins list if needed. A locally installed plugin can be loaded directly from the plugins directory.

The Hosted Registry and the Connection Catalogue

Since v0.16.0, plugin discovery runs through the hosted Tabularium registry at registry.tabularis.dev instead of a static JSON file:

• The connection catalogue. Creating a new connection starts from a searchable catalogue that merges built-in drivers with registry plugins into one grid, with paradigm facets for filtering. Drivers your platform can't run are badged and dimmed. Picking an uninstalled driver install-gates it — you can install the plugin inline and continue straight to the connection form.
• Deep-link installs. Links of the form tabularis://install/<slug> open the app with a version-aware confirmation: Install for a new plugin, Update when a newer version exists, or an already-installed notice. An optional ?version= pins a specific release.
• Version picking and updates. Catalogue cards let you install a specific released version, and the Installed tab shows an Update button when a newer compatible release exists for your platform and app version.
• Backwards compatibility. The legacy static registry.json is still merged into the catalogue (the hosted API wins on conflicting ids), so plugins that haven't migrated remain visible and installable, and older app versions keep working unchanged.

@tabularis/create-plugin scaffolds the .tabularium manifest directly and ships a migrate command that converts an existing legacy manifest.json plugin (and, with --ci, regenerates a registry-ready release workflow).

Using a Custom Plugin Registry

By default, Tabularis fetches the plugin list from the official Tabularium registry. You can point the app to a different registry (e.g., a self-hosted or company-internal Tabularium instance) by setting customRegistryUrl in your config.json:

{
  "customRegistryUrl": "https://registry.example.com/api/manifest"
}

When this key is set, both the in-app plugin browser and the install command use your registry instead of the default one. A plain static JSON file following the legacy registry schema also still works.

UI Extensions (Phase 2)

Starting with v0.9.13, plugins can inject custom React components into the Tabularis UI through a slot-based extension system. This allows plugins to add buttons, fields, previews, and menu items directly into the interface without modifying host code.

How It Works

The system has three layers:

1. SlotAnchor — Host components placed at predefined insertion points that determine WHERE extensions render.
2. PluginSlotRegistry — A React context that stores registered contributions and determines WHAT gets rendered.
3. Plugin Modules — JavaScript/TypeScript code that registers components during plugin activation.

Available Slots

Ten insertion points are available:

Declaring UI Extensions in the Manifest

Add an optional ui_extensions array to your manifest:

{
  "name": "postgis-toolkit",
  "version": "1.0.0",
  "ui_extensions": [
    {
      "slot": "row-editor-sidebar.field.after",
      "module": "./ui/GeometryPreview.tsx",
      "order": 50
    },
    {
      "slot": "data-grid.toolbar.actions",
      "module": "./ui/MapViewButton.tsx",
      "order": 80
    }
  ]
}

Plugin API

Slot components can import hooks from @tabularis/plugin-api:

Error Isolation

Each slot contribution is wrapped in a SlotErrorBoundary. A crashing plugin component displays a compact error message without affecting the host application or other plugins.

Backward Compatibility

The ui_extensions field is optional. Plugins without it continue to work identically. The slot anchors render nothing when no contributions are registered — zero overhead.

Built-in Example: JSON Viewer

Tabularis ships with a built-in JSON Viewer plugin that demonstrates the slot system. It renders a formatted, collapsible JSON tree with syntax highlighting for JSON/JSONB columns in the row editor.

Slots used: row-editor-sidebar.field.after, row-edit-modal.field.after

Features:

• Auto-detects JSON columns by name (contains "json") or by parsing the value
• Syntax-highlighted tokens: strings (green), numbers (blue), booleans (yellow), null (red), keys (purple)
• Collapsible objects and arrays with auto-expand for the first 2 depth levels
• Copy-to-clipboard button for the formatted JSON

Source code: src/plugins/examples/json-viewer/

For the full specification, see the Plugin UI Extensions Spec.

Publishing to the Registry

To make your plugin available in the official in-app plugin browser:

1. Build release binaries for all target platforms.
2. Package each binary with your manifest into a .zip file, and keep a .tabularium registry manifest in your repo. The release workflow scaffolded by @tabularis/create-plugin (or regenerated via create-plugin migrate --ci) does this for you.
3. Publish a GitHub Release with the ZIP assets — and attach .tabularium as a standalone asset; the registry resolves your metadata from the release assets (GitHub renames the dotfile to default.tabularium, which the registry also accepts).
4. Submit your plugin at registry.tabularis.dev/submit — ownership is verified via OAuth against your linked repository, and CI can pre-validate your manifest via POST /api/manifest/validate. The registry's plugin development page documents every .tabularium field, derived live from the registry's schema.

What the registry validates (the top three submit failures):

• name must match ^[a-z][a-z0-9-]*$ — it becomes your registry slug, pinned at first submit.
• version is semver without a leading v and must equal the release tag stripped of any v prefix.
• A manifest that fails schema validation (e.g. a description over 280 chars) is rejected with HTTP 422 — no silent fallback.

The legacy path — a pull request against plugins/registry.json — still works during the transition; legacy entries are merged into the hosted catalogue automatically. New plugins should submit to the registry directly.