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Basalt

by joshiii-xyzversion 0.1.6i★ –iRuns on your computer
Registry nameio.github.joshiii-xyz/basalt

Install

Overview

Description from the maker (original English)

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

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Developer tools

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

The maker has not listed install details in the registry. See the maker’s README below.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account joshiii-xyz, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Developer toolsi

  • More stars than 0% of the other 4924 servers in this category
  • Published to the registry more recently than 39% of the other 4924 servers in this category
  • Basic checks equal to or better than 100% of the other 4924 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Basalt safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.6) reached the registry 2 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Rust on your computer.

What can I use instead?

In the same category: GitHub, Desktop Commander, Cloudflare MCP

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

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

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.

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:

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

To run directly from a checkout:

cargo run --release -- app.basalt

Quick start

Open a database and run SQL interactively:

$ 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:

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:

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.

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:

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.

{

"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:

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:

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

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

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

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

PathPurpose
src/sql/Lexer, parser, AST, and SQL dialect
src/engine.rsStatement execution and query semantics
src/planner.rsAccess-path selection
src/db.rs, src/database.rsTables, constraints, transactions, and API
src/storage.rs, src/wal.rsSnapshots, checksums, and recovery
src/cli.rsInteractive and scripted command-line frontend
src/workspace.rsLocal workspace lifecycle and data interchange
src/mcp.rsStdio MCP server, agent tools, and schema resource
server.jsonMCP Registry release metadata
docs/sql.mdSupported SQL dialect and transaction semantics
docs/benchmark-results.mdRecorded workflow benchmark snapshot
docs/compatibility.mdFile-format boundary and differential-test policy
docs/production-readiness.mdTechnical release contract, limits, and evidence
docs/early-user-validation.mdFive-minute switching test and feedback template
docs/fuzzing.mdParser and persistence fuzzing instructions
docs/mcp.mdMCP installation, configuration, and tool contract
docs/workspaces.mdWorkspace layout and import/export contract
tests/Integration and crash-recovery coverage
benches/In-process engine throughput benchmark
scripts/benchmark_workspace.pyReproducible workflow comparison harness
scripts/differential_sql.pySupported-subset SQLite differential checks
scripts/mcp-smoke.pyInstalled-binary writable MCP smoke test
scripts/verify-release-artifacts.pyRelease archive checksum and contents check
scripts/verify-registry-metadata.pyMCP Registry package/version consistency check
scripts/release-check.shPackaged-crate and release preflight
scripts/smoke-test.shInstalled-binary CLI and read-only MCP smoke test
fuzz/Optional libFuzzer parser and snapshot targets

Development

cargo fmt --all -- --check

cargo check --all-targets --locked cargo clippy --all-targets --all-features --locked -- -D warnings cargo test --all-targets --locked RUSTDOCFLAGS="-D warnings" cargo doc --no-deps --locked cargo bench --bench throughput cargo package --locked cargo build --release --locked cargo audit python3 scripts/benchmark_workspace.py --basalt target/release/basalt

For the complete Unix release preflight, use:

bash scripts/release-check.sh

It installs the exact packaged crate into a temporary prefix and runs the installed-binary smoke journey. It also runs cargo audit and dist plan when those tools are available.

See CONTRIBUTING.md for contribution guidelines and CHANGELOG.md for proje

Only the beginning is shown; read the rest in the repo

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