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mcp-toolbox

Active·★ 16.7k·Apache-2.0·Updated 2026-10-14
★ Most Popular★ Trending

MCP Toolbox for Databases, from Google, is an open-source MCP server that connects AI agents, IDEs and applications to databases. It was originally called Gen AI Toolbox for Databases and was renamed to reflect its MCP focus. It serves two purposes: a ready-to-use MCP server with prebuilt generic tools such as `list_tables` and `execute_sql`, and a framework for defining custom, restricted tools for production agents.

It suits two audiences. Developers can connect Gemini CLI, Claude Code, Codex, Antigravity or another MCP client to a database and explore data in natural language during development. Teams building agents can define structured queries, semantic search and NL2SQL tools in a YAML configuration, so the agent only runs the operations you allow. Supported sources include Google Cloud databases (AlloyDB, BigQuery, Cloud SQL, Spanner, Firestore) and many others such as PostgreSQL, MySQL, SQL Server, Oracle, MongoDB, Redis, Elasticsearch, ClickHouse, Neo4j and Snowflake. Connection pooling, IAM authentication and OpenTelemetry are built in, and SDKs integrate it with ADK, LangChain and LlamaIndex.

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Getting started: install with Homebrew (`brew install mcp-toolbox`), Go, Docker or `npx @toolbox-sdk/server`. Use `--prebuilt=postgres` (or another database) for instant generic tools, or pass `--config tools.yaml` with your own tool definitions.

This write-up is based on the project's README and public repository data. We have not hand-tested the tool. Data as of 2026-10-10.

License
Apache-2.0
Latest release
v1.14.0 · 2026-10-08
Last commit
2026-10-08
Contributors
166
Forks
1,757
Open issues and PRs
373
First published
2024-06-07
npm package
@toolbox-sdk/server 1.14.0 · 56,185 downloads last week
PyPI package
toolbox-core 1.4.0 · 91,365 downloads last week

Source: GitHub, npm and PyPI public APIs.

#MCP Server#Database Connector#AI Agent Tooling#LLM Integration#Data Access API#Custom Tool Framework#Developer SDKs
$ Install
$ brew install mcp-toolbox
↗ Visit site★ GitHub
01

Features

01Out-of-the-Box Database Access: Prebuilt generic tools for instant data exploration from IDEs/CLIs.
02Custom Tools Framework: Robust framework to build production-ready, secure AI tools with predefined logic.
03Simplified Agent Integration: Easy integration of tools into popular AI agent frameworks like LangChain, LlamaIndex, or custom agents.
04Enhanced Security and Observability: Integrated authentication and out-of-the-box OpenTelemetry for metrics and tracing.
02

Why choose it

+Very broad database coverage, from Google Cloud services to most popular open-source and commercial databases.
+Custom tools let production agents run only predefined, structured operations.
+Connection pooling, IAM authentication and OpenTelemetry built in.
+Official Google project, Apache-2.0 licensed, with SDKs for major agent frameworks.
03

Trade-offs

!The prebuilt generic tools include `execute_sql`; connecting them to production data with a privileged account is risky, so use read-only credentials or custom tools.
!Some authentication and observability features are most convenient on Google Cloud.
!Writing good custom tools requires designing queries and parameters carefully in YAML.
05

Maintenance check

ActiveChecked: 2026-10-15
Last commit
2026-10-13
Commits, last 90 days
100+
Releases, last 90 days
9
Latest release
v1.14.0 (2026-10-08)
Open issues
389
Recent issues with at least one comment
8/13

Status rule: archived on GitHub = Archived; last commit within 90 days = Active; 91 to 365 days = Slowing; older = Stale. All figures come from the GitHub API on the date shown.

Most discussed open issues

  • #1896 Support for metdata for both sources and tools in tools.yaml and description for sources30 comments · 2025-11-07
  • #715 Proposal: Enabling MCP Toolbox for Databases as MCP Server26 comments · 2025-06-15
04

Who it fits

Pick it if
  • You work with Google Cloud databases (AlloyDB, BigQuery, Cloud SQL, Spanner, Firestore) or want one server across many other databases.
  • You are building a production agent and want it to run only predefined, structured operations defined in YAML.
  • You need connection pooling, IAM authentication or OpenTelemetry built in.
Look elsewhere if
  • You want a two-minute setup for one local database; a single-purpose server such as the MySQL one is simpler.
  • You plan to connect execute_sql to production data with a privileged account; the README's own advice is read-only credentials or custom tools.
  • You prefer not to write YAML tool definitions.
06

How it differs

vs dbhub

MCP Toolbox has the wider source list and production features (pooling, IAM, OpenTelemetry) and is an official Google project under Apache-2.0. DBHub is MIT, lighter and quicker to start for PostgreSQL, MySQL, SQL Server, MariaDB and SQLite.

vs mongodb-mcp-server

MongoDB's own server is the choice for MongoDB and Atlas specifically, with Atlas cluster and user management tools. MCP Toolbox is for breadth across many databases.

07

Compatibility

Python
SDK
Verified via docs
JavaScript/TypeScript
SDK
Verified via docs
Go
SDK
Verified via docs
Java
SDK
Verified via docs
Linux
OS
Verified via docs
macOS
OS
Verified via docs
08

Quick start

1
$ brew install mcp-toolbox
09

Use cases

↳AI-powered Data Querying: Allow AI assistants to query databases using natural language from IDEs or CLIs.
↳Automated Database Operations: Automate schema discovery, management, and database-aware code generation.
↳Building Specialized AI Tools: Develop highly secure, production-ready AI tools with custom logic for specific database interactions.
↳Integrating Database Functionality into Agent Frameworks: Incorporate database access and custom tools into AI agent development kits like LangChain or LlamaIndex.
10

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On this page
01Features02Why choose it03Trade-offs05Maintenance check04Who it fits06How it differs
  • #1327 why there are duplicate parameters descrption in the tools ?18 comments · 2025-09-04
  • #3373 feat: Add policy-based automatic PII detection and dynamic masking17 comments · 2026-06-06
  • #2290 ArangoDB16 comments · 2026-01-11

    • Issue titles are quoted from GitHub. Open the link to check whether a problem still applies to the version you use.

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    07
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    08Quick start
    09Use cases
    10Alternatives
    Stats
    GitHub Stars★ 16.7k
    Last commit1d ago
    StatusActive
    LicenseApache-2.0
    CategoryAPI Integration
    Trend (30d)
    +0.6k↑ 2.5%
    Links
    Documentation↗Discussion↗Issues↗Releases↗

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