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

Plugin folder locations:

The manifest.json

Every plugin must include a manifest.json that tells Tabularis its capabilities and the data types it supports.

{
  "id": "duckdb",
  "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

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).

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.

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 paginated results.

Params:

{
  "params": ConnectionParams,
  "query": "SELECT * FROM users",
  "page": 1,
  "page_size": 100
}

Result:

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

For the full list of methods (CRUD, DDL, views, routines, 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
        }),
        "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 manifest.json and the compiled executable there.
3. On Linux/macOS, make it executable: chmod +x myplugin
4. Open Tabularis Settings → Available Plugins and install it — no restart required.

Using a Custom Plugin Registry

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

{
  "customRegistryUrl": "https://example.com/my-registry.json"
}

The custom registry must expose a JSON file that follows the same schema as the official registry. When this key is set, both the plugin browser and the install command will use your URL instead of the default one.

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 manifest.json into a .zip file.
3. Publish a GitHub Release with the ZIP assets.
4. Open a pull request adding your entry to plugins/registry.json.