Mimir Memory integration for ADK¶

Supported in ADKPython

The adk-mimir-memory integration connects your ADK agent to Mimir, a persistent, cross-session memory backend. Backed by a single Rust binary with an embedded SQLite database, it requires zero cloud dependencies, and everything runs locally. Memory is encrypted at rest with AES-256-GCM, and search combines FTS5 keyword matching with dense vector retrieval.

Use cases¶

Persistent agent memory across restarts: Sessions survive process restarts, and agents recall past conversations automatically
Private, air-gapped deployments: No cloud dependency, and Mimir runs entirely on your machine with optional AES-256-GCM encryption
Hybrid search across memories: Combine keyword (FTS5/BM25) and semantic (dense vector) search to find relevant past interactions
Workspace-aware agents: Pair with Perseus for agents that know about your project files, git state, and configuration

Prerequisites¶

Python 3.10+
The mimir binary (see Installation)
google-adk>=1.0.0

Installation¶

Install the Python package:

pip install adk-mimir-memory

Then install the mimir binary: download the build for your platform from the Mimir releases page and place it on your PATH. The service looks for mimir by default, or pass mimir_binary="/absolute/path/to/mimir" to MimirMemoryService.

Use with agent¶

Create the MimirMemoryService, pass it to your Runner, and give the agent the load_memory tool so it can recall past sessions:

from adk_mimir_memory import MimirMemoryService
from google.adk.agents import Agent
from google.adk.runners import Runner
from google.adk.sessions import InMemorySessionService
from google.adk.tools import load_memory

agent = Agent(
    name="memory_assistant",
    model="gemini-flash-latest",
    instruction="You are a helpful assistant with long-term memory.",
    tools=[load_memory],
)

runner = Runner(
    agent=agent,
    app_name="mimir_app",
    session_service=InMemorySessionService(),
    memory_service=MimirMemoryService(db_path="~/.adk/mimir.db"),
)

After a session completes, call await memory_service.add_session_to_memory(session) to persist it. The agent recalls relevant memories in later sessions through the load_memory tool. See ADK memory for the full ingest-and-recall flow.

Perseus live context (optional)¶

For live workspace awareness, install the perseus extra:

pip install adk-mimir-memory[perseus]

Then use the prebuilt perseus_context_agent, which resolves @file, @search, and @memory directives at inference time:

from adk_mimir_memory.perseus_context import perseus_context_agent
from google.adk.runners import Runner
from google.adk.sessions import InMemorySessionService

# The pre-built agent ships without a model; set one before use.
perseus_context_agent.model = "gemini-flash-latest"

runner = Runner(
    agent=perseus_context_agent,
    app_name="perseus_app",
    session_service=InMemorySessionService(),
    memory_service=MimirMemoryService(db_path="~/.adk/mimir.db"),
)

Set Perseus directives via session state when creating the session (inside an async function):

session = await runner.session_service.create_session(
    app_name="perseus_app",
    user_id="user",
    state={
        "_perseus_directives": "@file AGENTS.md @file README.md @memory deployment",
        "_perseus_workspace": "/path/to/project",
    },
)

Available memory operations¶

Method	Description
`add_session_to_memory(session)`	Persist a full session's events
`add_events_to_memory(...)`	Append incremental event deltas
`add_memory(...)`	Store explicit memory entries
`search_memory(...)`	FTS5 keyword search across memories

Backend comparison¶

Backend	Dependencies	At-rest encryption	Search	Hosting
InMemoryMemoryService	None	Not persisted	Keyword	Local (ephemeral)
VertexAiMemoryBankService	Google Cloud	Google-managed (CMEK optional)	Semantic (Gemini)	Google Cloud
VertexAiRagMemoryService	Google Cloud	Google-managed (CMEK optional)	Vector similarity	Google Cloud
MimirMemoryService	`mimir` binary	Local AES-256-GCM (optional)	Hybrid (FTS5 + dense)	Local