a2db
Most database MCP servers make you run one query at a time, repeat connection details on every call, and return results double-encoded inside JSON strings. a2db fixes all of that: Pre-configured connections — define databases in .mcp.json with --register, agent queries immediately Batch queries — run multiple named queries in a single tool call
README
<p align="center"> <h1 align="center">🗄️ a2db</h1> <p align="center"> <em>Agent-to-Database</em> </p> <p align="center"> <strong>Give AI agents safe, read-only access to your databases. One call, multiple queries, clean results.</strong> </p> <p align="center"> 5 databases · batch queries · pre-configured connections · SQLGlot read-only </p> <p align="center"> <a href="https://pypi.org/project/a2db/"><img src="https://img.shields.io/pypi/v/a2db.svg" alt="PyPI"></a> <a href="https://pypi.org/project/a2db/"><img src="https://img.shields.io/pypi/pyversions/a2db.svg" alt="Python versions"></a> <a href="https://github.com/yoselabs/a2db/blob/main/LICENSE"><img src="https://img.shields.io/github/license/yoselabs/a2db.svg" alt="License"></a> <a href="https://github.com/yoselabs/a2db/actions"><img src="https://github.com/yoselabs/a2db/actions/workflows/publish.yml/badge.svg" alt="CI"></a> <a href="https://registry.modelcontextprotocol.io/servers/io.github.yoselabs/a2db"><img src="https://img.shields.io/badge/MCP-registry-blue" alt="MCP Registry"></a> </p> <p align="center"> <a href="#quick-start">Quick Start</a> · <a href="#mcp-tools">MCP Tools</a> · <a href="#security">Security</a> · <a href="#comparison">Comparison</a> · <a href="#setup-by-environment">Setup</a> </p> </p>
Agent: "Show me active users and their recent orders"
↓
a2db execute → 2 queries, 1 call, structured results
↓
Agent: "Got it — 847 active users, avg order $42.50"
Why a2db?
Most database MCP servers make you run one query at a time, repeat connection details on every call, and return results double-encoded inside JSON strings. a2db fixes all of that:
- Pre-configured connections — define databases in
.mcp.jsonwith--register, agent queries immediately - Batch queries — run multiple named queries in a single tool call
- Default connection — set connection once, use it across all queries in a batch
- Clean output — structured JSON envelope with compact TSV data and per-query timing (see why TSV?)
- Read-only enforced — SQLGlot AST parsing blocks all write operations
- All drivers bundled —
pip install a2dband you're done - Secrets stay in env —
${DB_PASSWORD}in DSNs, expanded only at connection time
Supported Databases
| Database | Driver | Async |
|---|---|---|
| PostgreSQL | asyncpg | native |
| SQLite | aiosqlite | native |
| MySQL / MariaDB | mysql-connector-python | wrapped |
| Oracle | oracledb | wrapped |
| SQL Server | pymssql | wrapped |
Quick Start
pip install a2db
As an MCP Server (recommended)
Claude Code (with pre-configured connection):
claude mcp add -s user a2db -- a2db-mcp \
--register myapp/prod/main 'postgresql://user:${DB_PASSWORD}@host/mydb'
Claude Code (minimal — agent calls login on demand):
claude mcp add -s user a2db -- a2db-mcp
Claude Desktop / Cursor / any MCP client (.mcp.json):
{
"mcpServers": {
"a2db": {
"command": "uvx",
"args": [
"a2db-mcp",
"--register", "myapp/prod/main", "postgresql://user:${DB_PASSWORD}@host/mydb"
],
"env": {
"DB_PASSWORD": "your-password-here"
}
}
}
}
Multiple databases:
{
"args": [
"a2db-mcp",
"--register", "myapp/prod/main", "postgresql://user:${DB_PASSWORD}@host/maindb",
"--register", "myapp/prod/analytics", "postgresql://user:${DB_PASSWORD}@host/analytics"
]
}
--register pre-registers connections at server startup — the agent can query immediately. Passwords use ${ENV_VAR} syntax and are expanded at connection time, never stored in plaintext.
As a CLI
# Save a connection (validates immediately)
a2db login -p myapp -e prod -d main 'postgresql://user:${DB_PASSWORD}@localhost/mydb'
# Query
a2db query -p myapp -e prod -d main "SELECT * FROM users LIMIT 10"
# JSON output
a2db query -p myapp -e prod -d main -f json "SELECT * FROM users LIMIT 10"
# Explore schema
a2db schema -p myapp -e prod -d main tables
a2db schema -p myapp -e prod -d main columns -t users
# List / remove connections
a2db connections
a2db logout -p myapp -e prod -d main
MCP Tools
| Tool | Description |
|---|---|
login |
Save a connection — validates by connecting first |
logout |
Remove a saved connection |
list_connections |
List connections (no secrets exposed) |
execute |
Run named batch queries with pagination |
search_objects |
Explore schema — tables, columns, with detail levels |
execute — the core tool
Named dict with default connection (preferred):
{
"connection": {"project": "myapp", "env": "prod", "db": "main"},
"queries": {
"active_users": {"sql": "SELECT id, name FROM users WHERE active = true"},
"recent_orders": {"sql": "SELECT id, total FROM orders ORDER BY created_at DESC LIMIT 5"}
}
}
List format (auto-named q1, q2, ...):
{
"connection": {"project": "myapp", "env": "prod", "db": "main"},
"queries": [
{"sql": "SELECT COUNT(*) AS cnt FROM users"},
{"sql": "SELECT AVG(total) AS avg_order FROM orders"}
]
}
Response (TSV format — default):
{
"active_users": {
"data": "id\tname\n1\tAlice\n2\tBob\n3\tCharlie",
"rows": 3,
"truncated": false,
"time_ms": 12
},
"recent_orders": {
"data": "id\ttotal\n501\t129.00\n500\t49.99",
"rows": 2,
"truncated": false,
"time_ms": 8
}
}
No ::text casts needed — integers, floats, timestamps, arrays, NULLs all work natively.
Error context
When a query fails with a column error, a2db enriches the message:
column "nme" does not exist
Did you mean: name?
Available columns: id (integer), name (text), email (text), active (integer)
Why TSV?
LLM context windows are expensive. JSON row data is verbose — every row repeats every column name, adds braces, commas, and quotes. TSV is a flat grid: one header row, then just values separated by tabs.
For a 100-row, 5-column result set, TSV typically uses 40-60% fewer tokens than JSON row format. The structured JSON envelope still gives you metadata (row count, truncation status) — only the row payload is TSV.
Set format="json" if you need full structured output with column names on every row.
Security
Read-Only Enforcement
Every query is parsed by SQLGlot before execution:
- Blocked: INSERT, UPDATE, DELETE, DROP, TRUNCATE, ALTER, CREATE, GRANT, REVOKE
- Bypass-resistant: multi-statement attacks and comment-wrapped writes are caught at the AST level, not just keyword matching
- Allowed: SELECT, UNION, EXPLAIN, SHOW, DESCRIBE, PRAGMA
This is defense-in-depth — you should also use a read-only database user, but a2db won't let writes through even if the user has write permissions.
Write support is implemented in the core but not yet exposed via MCP. Planned: per-connection write permissions, explicitly enabled by the human operator — not the agent. See TODO.md.
Credential Storage
Connections are saved in ~/.config/a2db/connections/ as TOML files.
${DB_PASSWORD}syntax — environment variable references are stored literally and expanded only at connection time. Secrets stay in your environment, not on disk.- No secrets in list output —
list_connectionsshows project/env/db and database type, never DSNs or passwords - Connection files are local to your machine and outside any repository
Deployment Scope
a2db currently runs as a local stdio MCP server. It inherits environment variables from the process that launches it (your shell, Claude Code, Docker). This is the standard model for local MCP servers — the same approach used by DBHub, Google Toolbox, and others.
Planned: remote HTTP transport with OAuth 2.1 per the MCP spec. For now, if running in Docker, inject secrets via environment variables at container runtime.
Comparison
| Feature | a2db | DBHub | Google Toolbox | PGMCP | Supabase MCP |
|---|---|---|---|---|---|
| Databases | 5 (PG, SQLite, MySQL, Oracle, MSSQL) | 5 (PG, MySQL, MSSQL, MariaDB, SQLite) | 40+ (cloud + OSS) | PG only | PG (Supabase) |
| Batch queries | Named dict + list | Semicolon-separated | No | No | No |
| Default connection | Set once, use for all | Per-query | N/A | Single DB | Single project |
| Read-only | SQLGlot AST (enforced) | Keyword check (config) | Hint/annotation | Read-only tx + regex | Config flag |
| Write support | Planned (per-connection) | Config flag | Via tool definition | No | Config flag |
| Output | JSON + TSV data | Structured text | MCP protocol | Table / JSON / CSV | JSON |
| Schema discovery | 3 detail levels | Dedicated tool | Prebuilt tools | Via NL-to-SQL | Dedicated tools |
| Pre-configured | --register in MCP config |
Config file | YAML config | Env var | Cloud-managed |
| Credentials | ${ENV_VAR} in DSN |
DSN strings | Env vars + GCP IAM | Env var | OAuth 2.1 |
| Drivers bundled | All included | All included | Varies | Built-in | Managed |
| CLI | Yes | No | Yes | Yes | No |
| Error context | Column suggestions + types | No | No | No | No |
| License | Apache 2.0 | MIT | Apache 2.0 | Apache 2.0 | Apache 2.0 |
When to use what:
- a2db — multi-DB batch queries with clean output, agent-first design, fast setup
- DBHub — custom tools via TOML config, web workbench UI
- Google Toolbox — GCP ecosystem, IAM integration, 40+ sources
- PGMCP — natural-language-to-SQL for PostgreSQL (requires OpenAI key)
- Supabase MCP — full Supabase platform management (edge functions, branching, storage)
Setup by Environment
Local (macOS / Linux)
pip install a2db
# CLI
a2db login -p myapp -e dev -d main 'postgresql://user:pass@localhost/mydb'
# Or add as MCP server (see Quick Start)
Docker
FROM python:3.12-slim
RUN pip install a2db
CMD ["a2db-mcp", "--register", "myapp/prod/main", "postgresql://user:${DB_PASSWORD}@host/mydb"]
docker run -e DB_PASSWORD=secret -i my-a2db-image
Secrets are injected as environment variables at runtime — never baked into the image.
CI / Automation
pip install a2db
# Pre-configured — no login needed
a2db-mcp --register myapp/ci/main "postgresql://ci_user:${CI_DB_PASSWORD}@db-host/mydb"
# Or use CLI directly
a2db login -p myapp -e ci -d main "postgresql://ci_user:${CI_DB_PASSWORD}@db-host/mydb"
a2db query -p myapp -e ci -d main "SELECT COUNT(*) FROM migrations"
Development
make bootstrap # Install deps + hooks
make check # Lint + test + security (full gate)
make test # Tests with coverage (90% minimum)
make lint # Lint only (never modifies files)
make fix # Auto-fix + lint
License
Apache 2.0
<p align="center"> <sub>🗄️ Agent-first database access since 2025.</sub> </p> <p align="center"> <sub>Built by <a href="https://github.com/iorlas">Denis Tomilin</a></sub> </p>
<!-- mcp-name: io.github.yoselabs/a2db -->
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。