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Synap hosts a remote MCP server so no-code platforms can have persistent memory without running an SDK or writing any code. You connect it the way every MCP-aware tool connects to a remote server: paste an MCP Server URL and a Bearer token. Your agent then discovers Synap’s memory tools and calls them automatically.
This is the no-code surface. If you’re building with code, use an SDK or framework integration instead — you get the same memory, with more control.

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How it works

The MCP server re-fronts Synap’s existing memory operations as a small set of tools. The model decides when to call them from their descriptions alone, so you configure nothing:
  • Forward everything. Your agent forwards each conversation turn to a single “log” tool. You never decide what is “memory-worthy” — Synap’s extraction pipeline decides what to keep.
  • Recall before replying. Your agent fetches what’s already known about the person before it answers.
  • Async by design. Logging is fire-and-forget so a slow write never stalls a reply; extraction happens in the background.

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Get your connection details

1

Open the MCP page in your dashboard

In the Synap dashboard, go to MCP in the sidebar.
2

Create an agent

Describe, in plain English, what your agent does and what it should remember. Synap designs the memory architecture for you — there’s nothing to configure.
3

Copy the URL and generate a token

The page shows your MCP Server URL and lets you generate a Bearer token. The token is shown once — copy it now.Your MCP Server URL looks like:
https://synap-mcp.maximem.ai/mcp
Always use a standard Bearer token — never a custom header. Some platforms (e.g. Gumloop with Anthropic models) drop custom headers, so Bearer is the only reliable option. Your Synap API key is the Bearer token.

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Connect your platform

1

Add the credential

Settings → Credentials → Add → MCP Server. Paste your MCP Server URL, choose Bearer token, and paste your token. Connect.
2

Enable it on your agent

Add an Agent (or Ask AI) node and enable the Synap MCP credential. The memory tools appear automatically.
3

Chat

Talk to your agent. It logs each turn and recalls what’s known before replying.

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Tools

The MCP server exposes these tools. Descriptions are written so the model calls them on its own — you don’t wire anything up.
ToolWhat it does
log_exchangeForward a user (and optional assistant) turn to be remembered. Synap decides what persists.
recall_contextRecall what’s already known about the current person, for use before replying.
list_recent_memoriesList recent memories — handy for debugging or confirming memory works.
check_memory_statusCheck whether a logged exchange finished processing (extraction is asynchronous).

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Arguments

  • user_id (optional) — a stable id for the end-user. Pass it on both log_exchange and recall_context to keep each person’s memory separate.
  • customer_id (optional) — an organization id, for B2B / multi-tenant agents.
  • conversation_id (optional) — groups turns into a conversation.
  • wait_for_processing (optional, log_exchange) — when true, waits for extraction to finish and reports the outcome instead of returning immediately. Leave it off for normal turn-by-turn logging.

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Scoping memory

Who sees which memories is decided by the ids you pass — there’s nothing to configure:

One shared memory

Pass no ids. Everything is shared across the agent. Good for a single-purpose assistant.

Per end-user

Pass user_id. Each person gets their own private memory; everyone still shares the agent’s general knowledge.

Per organization

Pass customer_id for B2B agents that serve multiple customer organizations.
For a real per-user experience, map your platform’s user identifier into user_id — for example an n8n expression like {{ $json.userId }} or a Gumloop input. The same id on log_exchange and recall_context keeps each person’s memory separate.

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Prove it works

The dashboard’s MCP page includes a Test my memory button: it writes a sample memory and reads it back live, so you can confirm your token works before going live. In your platform, the same loop is the real test — tell your agent a fact, then in a new session ask what it remembers.

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Troubleshooting

Confirm the tools are listed on the credential/node. If the model still doesn’t call them, add a one-line instruction to your agent prompt: “Use your memory tools — log every user message and recall before replying.”
That’s the custom-header drop. Make sure auth is set as a Bearer token, not a custom header.
Extraction is asynchronous — wait a few seconds and try again, or use check_memory_status (or wait_for_processing) to confirm processing finished.
Re-check the URL (it ends in /mcp) and that the token is pasted exactly. Tokens are shown once — regenerate from the MCP page if you’ve lost it.