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Basalt

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View Repository

Local SQL workspaces with bounded, recoverable writes for coding agents.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "basalt-2": {
      "command": "npx",
      "args": [
        "-y",
        "basalt-2"
      ]
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing AlternativesπŸ—„οΈ More in Databases

Documentation Overview

Basalt logo

Basalt

A CLI-first local SQL workspace for structured data and coding agents.

CI MIT license

Basalt is an embedded SQL database and command-line application built from scratch in Rust. It provides a small library API, an interactive shell, durable storage, snapshot-isolated transactions, crash recovery, portable structured-data workspaces, and a stdio MCP server for local AI agents. It is not a SQLite-compatible replacement or a hosted database.

Highlights

  • SQL lexer and recursive-descent parser with expressions, joins, grouping, aggregates, aliases, and transaction statements.
  • Atomic statement execution with primary-key, UNIQUE, and user-created indexes.
  • Snapshot-isolated transactions with optimistic conflict detection.
  • Checksummed page snapshots and a write-ahead log that recovers committed state after a process crash.
  • Simple query planning with table scans, equality indexes, and range indexes.
  • Interactive and scriptable CLI output in table, CSV, and JSON-lines formats.
  • Portable workspaces with versioned metadata and atomic CSV, JSON/JSONL, and SQL dump import/export.
  • Installable MCP server with typed SQL tools, bounded workspace imports and exports, engine-bounded SQL, schema resources, and recoverable agent changes.

Installation

Rust 1.88 or newer is required for a Cargo install.

bash
cargo install basalt-db --locked

The published package is named basalt-db; the installed command remains basalt. To install the current checkout instead, use cargo install --path . --locked.

Tagged releases include checksummed installers and prebuilt binaries for Linux, macOS, and Windows. See GitHub Releases for the current no-toolchain install. The latest tagged release is verified from its published installer and its checksums:

Terminal
curl --proto '=https' --tlsv1.2 -LsSf https://github.com/joshiii-xyz/basalt/releases/latest/download/basalt-db-installer.sh | sh

To run directly from a checkout:

bash
cargo run --release -- app.basalt

Quick start

Open a database and run SQL interactively:

Dockerfile
$ basalt app.basalt
basalt> CREATE TABLE users (id INTEGER PRIMARY KEY, name TEXT NOT NULL);
basalt> INSERT INTO users VALUES (1, 'Ada');
basalt> SELECT * FROM users;
id | name
---+-----
1  | Ada
1 row(s)

For a one-shot command:

Dockerfile
basalt --json --command "SELECT * FROM users ORDER BY id;" app.basalt

Use Database::in_memory() for an ephemeral database. Durable writes are appended to the WAL immediately; call checkpoint() to fold the current state into the snapshot and clear old WAL frames. A durable path is owned by one process at a time; cloned Database handles share that owner safely across threads, while a second process receives an "already open" error.

Workspaces

Use a workspace when an agent or script needs a disposable, local relational area for CSV, JSON, logs, issue exports, or fixtures:

Dockerfile
basalt init .basalt-workspace
basalt workspace import --table issues .basalt-workspace issues.csv
basalt workspace inspect --json .basalt-workspace
basalt workspace query --json .basalt-workspace "SELECT * FROM issues ORDER BY id"
basalt workspace export .basalt-workspace issues issues.jsonl

Imports are atomic, recoverable, and return a durable change_id; exports are deterministic. Add --json to workspace import/export commands when an agent or script needs a machine-readable operation report; raw exports to - remain clean data streams. Later writes can be previewed, applied by exact plan ID, inspected in history, diffed with schema and row-change counts, and undone when they are the latest change. A workspace is owned by one Basalt process while open, so stop a workspace MCP server before using that workspace from the CLI or by opening its data.basalt file directly. See docs/workspaces.md for the format and boundaries.

The reason to use Basalt for agent-owned data is the write boundary: inspect a proposed change before it is durable, apply only the exact reviewed plan, then diff or undo the latest change if needed.

bash
basalt workspace preview --json .basalt-workspace \
  "UPDATE issues SET status = 'closed' WHERE id = 42"
# Review the returned plan_id, then:
basalt workspace apply --json .basalt-workspace PLAN_ID
# Review the returned change_id, then:
basalt workspace diff --json .basalt-workspace CHANGE_ID
basalt workspace undo --json .basalt-workspace CHANGE_ID

Use SQLite or DuckDB when you need their compatibility or analytical performance. Basalt is for local structured-data work where a bounded, recoverable write matters more than replacing an existing database.

If that describes your workflow, use the early-user validation guide with a disposable, non-sensitive input and record the concrete task and blocker. Basalt does not claim adoption until developers complete this workflow against the tools they already use.

MCP server

Basalt can run as a local Model Context Protocol server over stdio. Install the binary from this checkout:

bash
cargo install --path . --locked

Then configure an MCP host with an absolute workspace path. Workspace mode is the recommended agent integration: it scopes data access and requires an explicit preview/apply lifecycle for writes.

config.json
{
  "mcpServers": {
    "basalt": {
      "command": "basalt",
      "args": [
        "mcp",
        "--workspace",
        "/absolute/path/to/project-data",
        "--init-workspace"
      ]
    }
  }
}

--init-workspace creates the configured workspace only when its path does not exist; it never replaces an existing directory or manifest. Omit it when the workspace must be provisioned separately. Add "--allow-writes" only when the host has an explicit operator approval policy for applying workspace plans and undoing changes. Direct database mode is still available with "args": ["mcp", "/absolute/path/to/app.basalt"], but it is read-only by default; execute and checkpoint require the same flag. Use "args": ["mcp", ":memory:"] for an ephemeral direct-mode session. The installed binary is preferred for host configuration; running from a checkout is also possible with cargo run --quiet -- mcp --workspace /absolute/path/to/project-data.

When a modern MCP host advertises form elicitation, Basalt returns an input_required approval request before each workspace import, apply, or undo and executes only after the host retries with an explicit approval. Legacy initialized hosts receive elicitation/create; hosts that do not advertise elicitation use the explicit --allow-writes startup policy.

The release metadata carries the visible Cargo ownership marker used by the MCP Registry listing:

  • MCP Registry ownership marker: mcp-name: io.github.joshiii-xyz/basalt
  • Published listing: io.github.joshiii-xyz/basalt

Workspace mode exposes workspace_import, workspace_inspect, workspace_preview, workspace_plan, workspace_apply, workspace_history, workspace_diff, workspace_undo, and workspace_export, alongside bounded query, list_tables, and describe_table tools. It also exposes the current schema at basalt://schema. See docs/mcp.md for the complete tool contract, configuration details, approval boundary, and troubleshooting.

CLI

Execute a SQL file:

bash
basalt --file schema-and-seed.sql app.basalt

Run commands in order on one connection, including a transaction spanning multiple commands:

bash
basalt --command "BEGIN;" --command "INSERT INTO users VALUES (2, 'Grace');" --command "COMMIT;" app.basalt

Use --file - to read SQL from stdin. Repeat --command and --file as needed; they execute in the order they appear. Table output is human-readable, CSV emits query rows, and --json emits one JSON object per statement. Run .help inside the shell for .tables, .schema, .mode, .headers, .checkpoint, .show, and .clear. Each CLI SQL action and the pending interactive buffer is limited to 16 MiB; larger scripts should be split into smaller actions or use the bounded workspace import formats.

Library usage

Dockerfile
use basalt::{Database, db::StatementResult};

let database = Database::open("example.basalt")?;
database.execute_sql(
    "CREATE TABLE users (id INTEGER PRIMARY KEY, name TEXT NOT NULL); INSERT INTO users VALUES (1, 'Ada');",
)?;
let result = database.execute_sql("SELECT * FROM users WHERE id = 1")?;
assert!(matches!(result[0], StatementResult::Select { .. }));
database.checkpoint()?;
# Ok::<(), basalt::db::DbError>(())

Use database.connect() when SQL transaction statements need to span multiple calls.

Project layout

Read the full README β†’View source on GitHub β†’

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Reviews

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Frequently Asked Questions about Basalt

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "basalt": { "command": "npx", "args": ["-y", "Basalt"] } }

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Technical Specs & Signals

CategoryπŸ—„οΈDatabases
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimeNode.js
Last updatedSep 7, 2026
Views0
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Installs0
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27Quality signal: Emerging Β· 27/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership8/20
Documentation & tools11/30
Adoption & activity1/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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