asyncpg

High-performance async PostgreSQL client for Python — uses PostgreSQL binary protocol directly for maximum throughput. asyncpg features: asyncpg.connect() and asyncpg.create_pool() for connection management, await conn.fetch(sql)/fetchrow()/fetchval()/execute() for queries, parameterized queries with $1 $2 placeholders, transaction support via conn.transaction(), COPY FROM/TO for bulk data, prepared statements, custom type codecs, listen/notify pub/sub, and connection pool with min_size/max_size. Significantly faster than psycopg2 for async PostgreSQL.

Evaluated Mar 06, 2026 (0d ago) v0.29.x
Homepage ↗ Repo ↗ Developer Tools python asyncpg postgresql async asyncio database high-performance
⚙ Agent Friendliness
67
/ 100
Can an agent use this?
🔒 Security
87
/ 100
Is it safe for agents?
⚡ Reliability
85
/ 100
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
--
Documentation
88
Error Messages
85
Auth Simplicity
90
Rate Limits
98

🔒 Security

TLS Enforcement
90
Auth Strength
88
Scope Granularity
85
Dep. Hygiene
90
Secret Handling
82

PostgreSQL driver. Always use parameterized queries ($1, $2) — never format SQL strings. SSL in production: await asyncpg.connect(dsn, ssl='require'). Connection URL contains credentials — use environment variables. COPY is powerful but validate source data.

⚡ Reliability

Uptime/SLA
88
Version Stability
85
Breaking Changes
82
Error Recovery
85
AF Security Reliability

Best When

High-performance async PostgreSQL access in FastAPI or asyncio applications — asyncpg is 3-5x faster than psycopg2 for async workloads.

Avoid When

ORM needed (use SQLAlchemy+asyncpg), non-PostgreSQL databases, synchronous code, or when psycopg3's sync+async flexibility is preferred.

Use Cases

  • Agent async PostgreSQL — import asyncpg; async with asyncpg.connect('postgresql://user:pass@host/db') as conn: rows = await conn.fetch('SELECT * FROM users WHERE status = $1', 'active'); for row in rows: process(dict(row)) — query; agent queries PostgreSQL with parameterized queries; row is Record with dict-like access
  • Agent connection pool — pool = await asyncpg.create_pool('postgresql://...', min_size=5, max_size=20); async with pool.acquire() as conn: result = await conn.fetchrow('SELECT * FROM items WHERE id = $1', item_id) — pooled; agent uses connection pool for concurrent FastAPI/asyncio application; acquire() checks out connection
  • Agent transaction — async with conn.transaction(): await conn.execute('INSERT INTO orders ...'); await conn.execute('UPDATE inventory ...') — atomic; agent wraps multiple operations in transaction; automatic rollback on exception; nested transactions create savepoints
  • Agent bulk COPY — import io; data = io.StringIO('1,Alice\n2,Bob\n'); await conn.copy_to_table('users', source=data, format='csv', columns=['id', 'name']) — bulk insert; agent loads large datasets into PostgreSQL; COPY is much faster than individual INSERTs; also copy_from_table for bulk export
  • Agent listen/notify — await conn.add_listener('channel', lambda conn, pid, ch, payload: handle(payload)); await conn.execute('LISTEN channel'); while True: await asyncio.sleep(1) — pub/sub; agent subscribes to PostgreSQL NOTIFY for real-time event streaming between processes

Not For

  • ORM usage — asyncpg is a low-level driver; for ORM use SQLAlchemy async with asyncpg as backend
  • MySQL/SQLite — asyncpg is PostgreSQL-specific; for MySQL use aiomysql; for SQLite use aiosqlite
  • Synchronous code — asyncpg is async-only; for sync PostgreSQL use psycopg2 or psycopg3

Interface

REST API
No
GraphQL
No
gRPC
No
MCP Server
No
SDK
Yes
Webhooks
No

Authentication

Methods: password ssl
OAuth: No Scopes: No

PostgreSQL authentication via connection URL. SSL/TLS via ssl= parameter. SCRAM-SHA-256 supported.

Pricing

Model: open_source
Free tier: Yes
Requires CC: No

asyncpg is Apache 2.0 licensed. Free for all use.

Agent Metadata

Pagination
cursor
Idempotent
Partial
Retry Guidance
Not documented

Known Gotchas

  • Placeholders use $1 $2 not %s — asyncpg uses positional $1, $2, $3 placeholders not psycopg2-style %s or %(name)s; conn.fetch('SELECT * FROM t WHERE id = $1 AND status = $2', id_val, 'active') — positional args; agent code migrating from psycopg2: replace all %s with $1, $2, etc.; named params not supported
  • fetch() returns list of Records not dicts — rows = await conn.fetch(sql) returns list of asyncpg.Record; Record is dict-like but not dict; dict(row) converts; row['column'] for access; row[0] for index access; agent code: use dict(row) to convert for JSON serialization; [dict(r) for r in rows] for list
  • Pool must be created at startup, not per request — await asyncpg.create_pool() is expensive; create once at application startup; agent FastAPI: create pool in lifespan context manager; store on app.state.pool; acquire per request with pool.acquire(); close pool at shutdown: await pool.close()
  • Transaction context manager auto-rollbacks — async with conn.transaction(): if exception raised inside, transaction auto-rolls back; no explicit rollback needed; nested: async with conn.transaction() creates savepoint; agent code: wrap database writes in transaction(); handle exceptions outside transaction block for partial success
  • Connection from pool must be used as context manager — async with pool.acquire() as conn: — context manager returns connection on exit; NOT async with pool.acquire() as conn: without release; or: conn = await pool.acquire(); try: ... finally: await pool.release(conn) — explicit release pattern; agent code: prefer async with acquire()
  • listen/notify requires dedicated connection — listeners block connection; agent code: use separate connection (not from pool) for LISTEN: conn = await asyncpg.connect(...); await conn.add_listener('channel', callback); keep connection alive; pool connections are not suitable for persistent listeners

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Scores are editorial opinions as of 2026-03-06.

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