Mako

Name: Mako
Author: mako-ai

by mako-aiversion 1.0.0i★ –iRuns in the cloud

Registry nameio.github.mako-ai/mako

Install

Overview

Description from the maker (original English)

Explore your databases, validate SQL, and build & publish data apps in your Mako workspace.

PopNx MCP’s three pillars

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

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

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 in the cloud
Transport: Streamable HTTP
Category: Databases & datasets

Install

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

Before you install

Basic checks: 1 of 1 passed
Runs on the maker’s server: what you ask it goes through their server.
The registry lists no key to fill in.

You need

Runs in the cloudNothing to install; it connects over the internet

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Works in Claude on the web, desktop and mobile:

Open Settings → Connectors
Press Add custom connector
Paste the address below and press Add
If it asks you to sign in, sign in with the maker

https://app.mako.ai/api/mcp

Run this in your terminal

claude mcp add --transport http mako https://app.mako.ai/api/mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "mako": {
      "url": "https://app.mako.ai/api/mcp"
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "mako": {
      "type": "http",
      "url": "https://app.mako.ai/api/mcp"
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

ChatGPT connects only to servers on the internet:

Open ChatGPT on the web → Settings → Connectors (Apps)
Press Create or Add (some plans need Developer mode under Advanced first)
Paste the address below, give it a name and save
If it asks you to sign in, sign in with the maker

https://app.mako.ai/api/mcp

Menu names can differ slightly by plan and over time.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

We have not read this server’s tool list yet; we check endpoints in rotation.

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 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account mako-ai, 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 checked yet
Endpoint responds
Not checked yet; we check endpoints in rotation
… Not checked yet
Sign-in with OAuth
Not checked yet; we check endpoints in rotation
… Not checked yet
No hidden instructions in tool descriptions
Not checked yet; we read the tool list when we check the endpoint

Compared with others in Databases & datasetsi

More stars than 0% of the other 1137 servers in this category
Published to the registry more recently than 25% of the other 1137 servers in this category
Basic checks equal to or better than 100% of the other 1137 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 Mako 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 in the maker’s cloud. Connect over the internet with nothing to install, but what you send passes through the maker’s servers.

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.0.0) 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. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.

What can I use instead?

In the same category: Supabase, MongoDB MCP Server, Elasticsearch MCP Server

Alternatives

Servers in the same category from other makers, sorted by stars.

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

Supabase

by supabase

Supabase’s official server lets AI create tables, query data and review project settings in your Supabase database.

Computer or cloud★ 2,993Apache-2.0Updated yesterday

Install

MongoDB MCP Server

by mongodb-js

MongoDB Model Context Protocol Server

Runs on your computer★ 1,157Apache-2.0Updated 3 days ago

Install

Elasticsearch MCP Server

by cr7258

MCP server for interacting with Elasticsearch

Runs on your computer★ 315Apache-2.0Updated 14 months ago

Install

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.

Mako

The AI-native SQL Client.

The Cursor for Data. Connect to any database, query with AI, and build live data apps -- all from your browser.

Stop wrestling with complex SQL and slow, bloated database tools. Write queries in plain English, get instant results, and turn them into live React apps with scheduled data refresh.

🚀 Why Mako?

A modern SQL client built for the AI era, replacing slow desktop tools with a fast, collaborative, AI-powered experience.

✨ AI Query Generation: Write queries in natural language. Our schema-aware AI generates optimized SQL instantly.
_Replaces: DataGrip, DBeaver, Postico_
🧱 dbt Transforms: Build, run, and schedule dbt Core projects in-app -- file IDE, jobs, run history, lineage, and GitHub sync.
_Replaces: dbt Cloud_
⚛️ React Apps: Ask the agent to build live React apps wired to your data through secure, credential-free bindings -- scheduled Parquet materialization, queried with DuckDB in the browser.
_Replaces: Metabase, Looker, Lovable, v0, internal-tool builders_
🕓 Version History: Every console save is an immutable snapshot, and apps live in git -- browse and restore either.
_Replaces: Lost SQL files, manual backups_
🖥️ Mako Desktop: Native app that bundles a local agent so localhost databases work out of the box.
_Replaces: SSH tunnels and bastion hops for local DBs_
👥 Team Collaboration: Share connections, version-control queries, and work together in real-time.
_Replaces: Passing credentials around, lost SQL files_
⚡ Blazing Fast: No Java or Electron bloat. Opens instantly in your browser and runs smooth.
_Replaces: Slow desktop database tools_

📸 Screenshots

AI-powered console — ask in plain English, get a verified query and live results.

Transforms (dbt) — build, run, and schedule dbt Core projects with a file IDE, jobs, run history, and lineage.

Apps — build live React apps wired to your data, rendered in a sandboxed preview.

🔌 Integrations

Databases

Integration	Status	Description
PostgreSQL	✅ Live	Connect to PostgreSQL for relational data queries
MongoDB	✅ Live	Connect to MongoDB for flexible document-based data
BigQuery	✅ Live	Analyze large datasets with Google BigQuery
ClickHouse	✅ Live	Fast OLAP queries on ClickHouse
MySQL	✅ Live	Query MySQL databases with natural language
Redshift	✅ Live	Query Amazon Redshift data warehouses
Cloud SQL	✅ Live	Connect to Google Cloud SQL (Postgres)
Cloudflare D1	✅ Live	Query Cloudflare D1 SQLite databases
Cloudflare KV	✅ Live	Browse and query Cloudflare Workers KV

Data Connectors

Sync external SaaS data into Mako's data warehouse for querying and apps.

Integration	Status	Description
Stripe	✅ Live	Track payments, subscriptions, and billing data
PostHog	✅ Live	Analyze product analytics and user behavior
Close.com	✅ Live	Sync CRM data (leads, opportunities, activities)
Claap	✅ Live	Sync recordings and workspace data
Calendly	✅ Live	Sync events, invitees, and event types
GraphQL	✅ Live	Query any GraphQL API with custom endpoints
REST	✅ Live	Query any REST API with custom endpoints
BigQuery	✅ Live	Sync BigQuery datasets into the warehouse

🏗️ Architecture

┌─────────────────────────────────────────────────────────┐

│ Frontend (React + Vite) │ │ ┌──────────┐ ┌──────────────┐ ┌─────────────────────┐ │ │ │ Console │ │ Apps │ │ AI Chat (Vercel │ │ │ │ (Monaco) │ │ (React + │ │ AI SDK) │ │ │ │ │ │ DuckDB) │ │ │ │ │ └──────────┘ └──────────────┘ └─────────────────────┘ │ │ ▲ ▲ ▲ │ │ │ Parquet/Arrow │ │ │ │ via OPFS cache │ │ └───────────┼──────────┼──────────────────┼──────────────┘ │ │ │ ┌───────────┼──────────┼──────────────────┼──────────────┐ │ API (Hono + Node.js) │ │ ┌──────────────────────────────────────────────────┐ │ │ │ Unified Agent (expertise modes: Query / │ │ │ │ Sync Flow / React App / Transforms / │ │ │ │ Explore, switched via enable_mode) │ │ │ └──────────────────────────────────────────────────┘ │ │ ┌──────────────┐ ┌───────────────┐ ┌──────────────┐ │ │ │ DB Drivers │ │ Connectors │ │ App binding │ │ │ │ (9 drivers) │ │ (8 sources) │ │ engine │ │ │ │ │ │ │ │ (DuckDB │ │ │ │ │ │ │ │ + Parquet) │ │ │ └──────────────┘ └───────────────┘ └──────────────┘ │ │ ▲ │ │ ┌─────┴──────┐ │ │ │ Inngest │ (scheduled refresh, │ │ │ │ incremental sync) │ │ └────────────┘ │ └────────────────────────────────────────────────────────┘ │ │ ┌──────┴──────┐ ┌─────┴──────────┐ │ MongoDB │ │ User DBs │ │ (metadata, │ │ (PG, BQ, CH, │ │ warehouse)│ │ MySQL, etc.) │ └─────────────┘ └────────────────┘

Key technology choices:

DuckDB (both server-side via @duckdb/node-api and browser-side via @duckdb/duckdb-wasm): powers Parquet artifact generation for app bindings and in-browser SQL over them
Apache Arrow / Parquet: server materializes query results into Parquet, served to browser as Arrow IPC for zero-copy rendering
Inngest: event-driven job queues for scheduled app binding refresh and incremental data sync
Hono: lightweight, fast HTTP framework for the API
Monaco Editor: VS Code's editor for the SQL console
Vercel AI SDK: multi-provider LLM abstraction (OpenAI, Anthropic, Google)

📦 Artifact Storage

App data bindings (and app deployments, dbt outputs, and chat attachments) are materialized into an artifact store on the backend. The configuration names below predate apps -- they come from the since-removed dashboards feature -- and are kept so existing deployments keep working. Three storage backends:

filesystem -- default; stores files on local disk
gcs -- Google Cloud Storage
s3 -- S3-compatible bucket

DASHBOARD_ARTIFACT_STORE=filesystem

Optional shared settings

DASHBOARD_ARTIFACT_PREFIX=dashboards DASHBOARD_ARTIFACT_DIR=/absolute/path/to/artifacts # filesystem only

Google Cloud Storage

DASHBOARD_ARTIFACT_STORE=gcs

GCS_DASHBOARD_BUCKET=your-bucket-name DASHBOARD_ARTIFACT_PREFIX=dashboard-artifacts/prod

See the docs for full GCS/S3 provisioning instructions.

🛠️ Quick Start

Clone & Install

   git clone https://github.com/mako-ai/mako.git

cd mako pnpm install

Configure Environment Copy .env.example (if available) or create .env:

   # Local development connects to the shared `dev` database, an Atlas DB that is

refreshed nightly from production. Grab the `dev` connection string from the

team vault. (`staging` backs non-migration PR previews; never point local at

`production`.)

DATABASE_URL=mongodb+srv:// : @ .mongodb.net/dev ENCRYPTION_KEY=your_32_character_hex_key_for_encryption WEB_API_PORT=8080 BASE_URL=http://localhost:8080 CLIENT_URL=http://localhost:5173

Start Services

   # Start the local notebook Python kernel so notebook `code` cells run

locally. Requires the KERNEL_* vars from .env.example in your .env.

(The dev database is hosted MongoDB Atlas, set via DATABASE_URL.)

pnpm run docker:up

Start the full stack (API + App + Inngest)

pnpm run dev

Analyze

Open http://localhost:5173 to access the app.
Add a Data Source (e.g., Stripe or Close.com).
Use the chat interface to ask questions about your data.

🌐 IP Whitelisting

If your database requires IP whitelisting, add the following static IP to your allowlist:

34.79.190.46

This IP is used by Mako's cloud service for all outbound database connections.

💻 Development Commands

Command	Description
`pnpm run dev`	Start API, frontend, and Inngest dev server
`pnpm run app:dev:scan`	Start the frontend with React Scan and render debug logging
`pnpm run migrate`	Run database migrations
`pnpm run docker:up`	Start the local notebook Python kernel (run notebook code cells)
`pnpm run test`	Run test suite
`pnpm run build`	Build all packages
`pnpm run docs:dev`	Start documentation site locally

🔎 React Performance Profiling

Use React Scan when working on render churn, streaming chat responsiveness, Monaco console performance, or explorer/result table interactions:

pnpm run app:dev:scan

This enables the React Scan Vite plugin via VITE_REACT_SCAN=true and turns on Mako's render-debug logs via VITE_RENDER_DEBUG=true. React Scan highlights components that re-render in the browser, while render-debug logs summarize why hot components such as Chat, ResourceTree, Console, and ResultsTable changed.

Keep React Scan off during normal development. The plugin and debug hooks are gated behind env flags so regular pnpm run app:dev runs without profiling overlays or extra debug logging.

🤝 Community & Support

Documentation: docs.mako.ai
GitHub: mako-ai/mako
Website: mako.ai

Built with ❤️ by the Mako Team. Open Source and self-hostable.

Mako

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Databases & datasetsi

Common questions

Alternatives

Supabase

MongoDB MCP Server

Elasticsearch MCP Server

README from the maker

🚀 Why Mako?

📸 Screenshots

🔌 Integrations

Databases

Data Connectors

🏗️ Architecture

📦 Artifact Storage

Optional shared settings

Google Cloud Storage

🛠️ Quick Start

refreshed nightly from production. Grab the dev connection string from the

team vault. (staging backs non-migration PR previews; never point local at

production.)

locally. Requires the KERNEL_* vars from .env.example in your .env.

(The dev database is hosted MongoDB Atlas, set via DATABASE_URL.)

Start the full stack (API + App + Inngest)

🌐 IP Whitelisting

💻 Development Commands

🔎 React Performance Profiling

🤝 Community & Support

refreshed nightly from production. Grab the `dev` connection string from the

team vault. (`staging` backs non-migration PR previews; never point local at

`production`.)