MemoryDB Python client
superb-memory gives you the Python client, the mdb command-line tool and the
memorydb-mcp stdio server for MemoryDB — a single-binary
Go document database that also stores AI-agent memory (facts with evidence, summaries, tool
traces, hybrid BM25 + vector search).
One line to a running database
pip install superb-memory
mdb serve # fetches the server binary, starts it on 127.0.0.1:8080
mdb serve prints the connection string; every client reads it from the environment:
export MEMORYDB_URL=memorydb://TOKEN@127.0.0.1:8080
Documents
from memorydb import MemoryDB
db = MemoryDB() # reads MEMORYDB_URL
db.collections.create("customers",
fields={"email": {"type": "string", "required": True},
"age": {"type": "integer"}},
unique=["email"], indexes=["age"])
customers = db.collection("customers")
row = customers.objects.create(email="demo@example.com", age=24, idempotency_key="customer-demo-1")
customers.objects.filter(age__gte=18).order_by("-age").only("email").all()
customers.objects.increment(pk=row["id"], views=1) # atomic counter, no version needed
Django-style lookups: eq ne gt gte lt lte in contains icontains prefix iequals exists,
plus or_q, Sum/Avg/Min/Max with group_by, cursor pagination and optimistic version checks.
Agent memory
db.ingest([{"role": "user", "content": "I prefer terse answers in Hindi"}],
facts=[{"subject": "user", "predicate": "answer_style", "value": "terse Hindi",
"quote": "terse answers in Hindi", "message_index": 0, "confidence": 0.95}])
db.objects.search("terse")
Facts need an exact quote from a user message, so a stored memory always carries its evidence.
CLI and MCP
mdb health; mdb search "fridays"; mdb memory add --content "user ships on fridays"
memorydb-mcp # stdio MCP server for Claude Desktop, Qoder, IDE agents
Companion packages: memorydb-django (cache + session backends) and memorydb-langchain
(chat message history). Docs: docs/QUICKSTART.md and docs/CONNECTING.md in the repository.
Metadata
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Total release size: 28.6 kB
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