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Pay per usage
Persistent memory for AI agents via knowledge graph. Store entities, relations, and observations that persist across sessions. MCP-compatible.
Pricing
Pay per usage
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Quadruped
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2 days ago
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You can access the Memory Mcp Server programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.
1from apify_client import ApifyClient2
3# Initialize the ApifyClient with your Apify API token4# Replace '<YOUR_API_TOKEN>' with your token.5client = ApifyClient("<YOUR_API_TOKEN>")6
7# Prepare the Actor input8run_input = {9 "entities": "[{\"name\": \"John\", \"entityType\": \"person\", \"observations\": [\"Works at Acme Corp\", \"Lives in NYC\"]}]",10 "relations": "[{\"from\": \"John\", \"to\": \"Acme Corp\", \"relationType\": \"works_at\"}]",11 "observations": "[\"New observation 1\", \"New observation 2\"]",12 "entityNames": "[\"John\", \"Acme Corp\"]",13}14
15# Run the Actor and wait for it to finish16run = client.actor("constant_quadruped/memory-mcp-server").call(run_input=run_input)17
18# Fetch and print Actor results from the run's dataset (if there are any)19print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])20for item in client.dataset(run["defaultDatasetId"]).iterate_items():21 print(item)22
23# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-startThe Apify API client for Python is the official library that allows you to use Memory Mcp Server API in Python, providing convenience functions and automatic retries on errors.
Install the apify-client
$pip install apify-clientOther API clients include: