google__adk-docs/docs/integrations/synap.md

catalog_title, catalog_description, catalog_icon, catalog_tags

catalog_title	catalog_description	catalog_icon	catalog_tags
Synap	Add persistent, cross-session long-term memory to ADK agents	/integrations/assets/synap.png	data

Synap integration for ADK

Supported in ADKPython

The maximem-synap-google-adk plugin connects your ADK agent to Synap, a managed long-term memory layer for AI agents. Synap automatically extracts and structures knowledge from conversations (facts, preferences, episodes, emotions, and temporal events) and retrieves only what is semantically relevant to the current query.

Use cases

• Persistent cross-session memory: Give your ADK agents long-term memory that survives across sessions and deployments, with no manual bookkeeping.
• Multi-tenant isolation: Memory is scoped to user_id and customer_id, ensuring strict isolation in multi-user deployments.
• Semantic recall: Server-side extraction surfaces only what is relevant to the current query, keeping prompts short and tokens efficient.

Prerequisites

• A Synap account and API key
• Gemini API key (or any other model provider configured with ADK)

Installation

pip install maximem-synap-google-adk maximem-synap

Set the following environment variable:

export SYNAP_API_KEY="your-synap-api-key"

Use with agent

create_synap_tools(...) returns two FunctionTool instances, search_memory and store_memory, that the agent can call to recall and persist memories on demand.

import os

from google.adk.agents.llm_agent import Agent
from maximem_synap import MaximemSynapSDK
from synap_google_adk import create_synap_tools

sdk = MaximemSynapSDK(api_key=os.environ["SYNAP_API_KEY"])

synap_tools = create_synap_tools(
    sdk=sdk,
    user_id="alice",
    customer_id="acme_corp",
)

root_agent = Agent(
    model="gemini-flash-latest",
    name="memory_assistant",
    instruction=(
        "You are a helpful assistant with long-term memory. "
        "Use search_memory to recall what you know about the user. "
        "Use store_memory to save important new facts the user mentions."
    ),
    tools=synap_tools,
)

Run with:

adk run path/to/your_agent

Teach the agent something on the first turn (e.g. "I'm allergic to peanuts"), then ask about it on a later turn. Synap retrieves the relevant memory automatically, even across separate adk run invocations.

Available tools

Tool	Description
search_memory	Semantic search over the user's stored memories. Takes a natural-language query and returns the most relevant facts, preferences, and episodes.
store_memory	Persist an explicit fact in the user's long-term memory. The agent calls this when the user shares something worth remembering.

Resources

• Synap documentation
• ADK integration guide
• maximem-synap-google-adk on PyPI
• Open source integration package
• Synap Dashboard