Mako

io.github.mako-aiPublished by GitHub account mako-aiv1.0.0Updated Oct 24, 2026

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

VerifiedStreamable HTTPWeb executableDatabasesDeveloper ToolsData & Analytics

Overview

AI-generated overview

Mako is a remote, OAuth-protected MCP endpoint for its AI-native SQL client, letting an assistant explore databases, validate SQL, and build and publish data…

What you can do
  • Explore connected databases and inspect schemas across PostgreSQL, MongoDB, BigQuery, ClickHouse, MySQL, Redshift, Cloud SQL, Cloudflare D1 and KV
  • Generate, validate and run SQL queries from natural-language questions, with versioned console snapshots
  • Build and publish live React data apps wired to query results through credential-free bindings
  • Work with dbt Core transforms: projects, jobs, run history and lineage
  • Sync external SaaS data (Stripe, PostHog, Close.com, Calendly, GraphQL, REST and others) into the workspace warehouse
When to use it
Useful when your data lives in Mako and you want an assistant to query it in plain English, check SQL before running it, or scaffold and publish data apps and dbt transforms without switching to the Mako web console.
Requirements
A remote MCP endpoint at app.mako.ai reached over streamable HTTP, with OAuth sign-in to a Mako workspace. Databases or data connectors must already be configured in that workspace. No local package, environment variables or headers are declared.
Before you install
The server acts inside your Mako workspace with your OAuth identity, so it can run queries against connected databases and create or publish apps and transforms. Query results and app data are materialized in Mako's backend artifact store, and synced connectors pull third-party SaaS data into that warehouse. Review what it writes before publishing.

Installation

In SourceWeft

  1. Open Mako in the dashboard and add it to a workspace.
  2. Connect the required credentials. They are stored privately and never shown on public pages.
  3. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/io.github.mako-ai%2Fmako/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config. The client completes OAuth sign-in on first connect.

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

README

[Mako Logo] 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.

[Mako App Interface]

🚀 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.

[AI-powered console]

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

[dbt Transforms IDE]

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

[React Apps live preview]

🔌 Integrations

Databases

IntegrationStatusDescription
PostgreSQL✅ LiveConnect to PostgreSQL for relational data queries
MongoDB✅ LiveConnect to MongoDB for flexible document-based data
BigQuery✅ LiveAnalyze large datasets with Google BigQuery
ClickHouse✅ LiveFast OLAP queries on ClickHouse
MySQL✅ LiveQuery MySQL databases with natural language
Redshift✅ LiveQuery Amazon Redshift data warehouses
Cloud SQL✅ LiveConnect to Google Cloud SQL (Postgres)
Cloudflare D1✅ LiveQuery Cloudflare D1 SQLite databases
Cloudflare KV✅ LiveBrowse and query Cloudflare Workers KV

Data Connectors

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

IntegrationStatusDescription
Stripe✅ LiveTrack payments, subscriptions, and billing data
PostHog✅ LiveAnalyze product analytics and user behavior
Close.com✅ LiveSync CRM data (leads, opportunities, activities)
Claap✅ LiveSync recordings and workspace data
Calendly✅ LiveSync events, invitees, and event types
GraphQL✅ LiveQuery any GraphQL API with custom endpoints
REST✅ LiveQuery any REST API with custom endpoints
BigQuery✅ LiveSync 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
env
DASHBOARD_ARTIFACT_STORE=filesystem
# Optional shared settingsDASHBOARD_ARTIFACT_PREFIX=dashboardsDASHBOARD_ARTIFACT_DIR=/absolute/path/to/artifacts  # filesystem only
Google Cloud Storage
env
DASHBOARD_ARTIFACT_STORE=gcsGCS_DASHBOARD_BUCKET=your-bucket-nameDASHBOARD_ARTIFACT_PREFIX=dashboard-artifacts/prod

See the docs for full GCS/S3 provisioning instructions.

🛠️ Quick Start

  1. Clone & Install

    bash
    git clone https://github.com/mako-ai/mako.gitcd makopnpm install

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

    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://<user>:<password>@<cluster>.mongodb.net/devENCRYPTION_KEY=your_32_character_hex_key_for_encryptionWEB_API_PORT=8080BASE_URL=http://localhost:8080CLIENT_URL=http://localhost:5173

  3. Start Services

    bash
    # 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

  4. 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

CommandDescription
pnpm run devStart API, frontend, and Inngest dev server
pnpm run app:dev:scanStart the frontend with React Scan and render debug logging
pnpm run migrateRun database migrations
pnpm run docker:upStart the local notebook Python kernel (run notebook code cells)
pnpm run testRun test suite
pnpm run buildBuild all packages
pnpm run docs:devStart 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:

bash
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

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

Source: README.md at commit e36e3e0

Tools

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Version history

1
  1. v1.0.0LatestSep 16, 2026

Score

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