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# Share Context Across AI Clients with Supermemory MCP

Connect compatible MCP clients to a shared memory service using OAuth. Verify spaces, explicit saves, cross-client retrieval, and correction behavior.

By Shardul Mane October 7, 2025 · 4 min read 

![Share Context Across AI Clients with Supermemory MCP](https://supermemory.ai/_astro/cover.DpsB5acE_qnROH.webp)

AI clients can share selected context when they connect to the same memory service and use the same authorized space. Model Context Protocol (MCP) supplies a way for a client to access tools and resources. The server provides persistence; the client or an additional integration determines when to save and retrieve information.

Connecting two clients does not automatically transfer their full conversations or guarantee that either client will call a memory tool. Verify the path with one explicit save and one explicit search before relying on an automatic workflow.

## What is shared, and what stays in the client?

A memory saved to a shared service can be retrieved by another authorized client. A local chat message that was never saved remains local to that chat's own storage. The model's current context window is also distinct from the server's persisted records.

Think of MCP as the access path, not the memory database. Two unrelated MCP memory servers do not share data just because they implement the same protocol. Choose the server that stores the context you want both clients to access.

## Connect using the current server configuration

Supermemory's [setup documentation](https://supermemory.ai/docs/supermemory-mcp/setup) lists the remote HTTP endpoint and OAuth authentication. In clients that use an `mcpServers` configuration object, the documented form is:

```
{
  "mcpServers": {
    "supermemory": {
      "url": "https://mcp.supermemory.ai/mcp"
    }
  }
}
```

Other clients use a connector interface instead of this JSON file. Add the same server through that client's documented remote-MCP setup and complete its OAuth flow. Use the OAuth flow for this remote-server connection.

Client support and account availability differ. Use the relevant linked setup guide for Claude, ChatGPT, Cursor, or your chosen client rather than assuming every application accepts the same file path and menu sequence. After connecting, verify the account and space in both clients.

## Verify the account and space before saving

After connecting, ask which spaces are available and which space is active. Select the intended space explicitly for the test. Repeat that check in the second client. Being signed in to the same email address in two AI products does not by itself establish access to the same Supermemory account or space.

For a team workflow, decide which information should be shared and which should stay personal. A shared project decision and an individual's private preference have different audiences. Check permissions at the memory service and client configuration layers rather than relying on a prompt that says “only use my data.”

## Run a cross-client test with a unique fact

Use a fictional note that the model cannot infer from general knowledge:

```
Save in the test project space:
The demo project's release code name is Cedar-47.
This is synthetic test data, not a production release.
```

Confirm the save result and any documented processing state. In the second client, select the same space and explicitly search for the demo project's release code name. Inspect the returned record before judging the final answer.

Then change the code name, search again, and check how the earlier record is represented. Finally, remove the test record through the supported controls and repeat retrieval. Use the same test in a different space to check that it does not appear there unintentionally.

These steps distinguish successful transport, successful persistence, correct scoping, and useful answer behavior. A convincing answer alone cannot distinguish real retrieval from a guess or context copied into the prompt.

## Automatic capture requires its own verification

A client may decide to call an exposed save or search tool. Another integration may add hooks that capture selected work. Those behaviors are different from merely connecting a server.

For a workflow you intend to automate, record which events should trigger capture, what content is included, and how failure is surfaced. Test an unsaved message as a negative case. If it appears in another client, identify the actual capture mechanism rather than attributing it to MCP in general.

The [Claude Code plugin guide](https://supermemory.ai/blog/claude-code-memory-rehab/) covers a client-specific integration with additional behavior. Keep plugin configuration separate from remote-server configuration so you can explain which component is responsible for each record.

## Troubleshoot at the failing boundary

| Symptom                                        | First check                                                 |
| ---------------------------------------------- | ----------------------------------------------------------- |
| Server will not connect                        | Client support, endpoint, and OAuth error                   |
| Connected but no tools available               | Enabled tools and granted access                            |
| Save succeeds but another client finds nothing | Account, space, processing state, and exact search evidence |
| An old answer persists                         | Retrieved version, local conversation context, and caches   |
| Unrelated project context appears              | Active space and sharing configuration                      |

Preserve the actual error and use the provider's supported authentication flow. Changing certificate checks or ignoring OAuth validation errors is not a memory fix.

For application code that needs explicit control over identity and retrieval, use the [AI SDK guide](https://supermemory.ai/blog/how-to-use-supermemory-with-ai-sdk/) or a direct API integration. For personal or team use across compatible clients, the first milestone is simpler: one saved fact, retrieved in a second client from the intended space, with a correction and deletion you can verify.

Ready to connect your clients? [Follow the Supermemory MCP setup guide](https://supermemory.ai/docs/supermemory-mcp/setup), then run the two-client test above with a fictional fact. Start with one intended space and verify the result before adding more clients.

## Other posts.

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19. [Mem0 vs Supermemory: Why Scira Switched Scira AI moved its production memory layer from Mem0 to Supermemory. This is what failed, what improved, and how the team evaluated the two systems. Case StudyOct 2, 2025 ](https://supermemory.ai/blog/why-scira-ai-switched)
20. [Never Record Again: How Montra Uses Supermemory to Rethink Video Creation Campbell Baron, the founder of Montra, has been making videos since he was twelve. By thirteen, he was already doing brand work. Today, he’s betting on a very different future for creators: a world where recording is the exception, and most videos are generated from scratch. Case StudyAug 21, 2025 ](https://supermemory.ai/blog/never-record-again-how-montra-uses-supermemory-to-rethink-video-creation)
21. [Unified Memory That Works Where You Work: Your Second Brain With Supermemory Hi everyone, I’m Dhravya, the founder of Supermemory. I want to start with a little story behind why this product means so much to me. You can also skip straight to what it is and how it works below. EngineeringJul 25, 2025 ](https://supermemory.ai/blog/unified-memory-that-works-where-you-work-your-second-brain-with-supermemory)
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27. [Architecting a memory engine inspired by the human brain Language is at the heart of intelligence, but what truly powers meaningful interaction is memory — the ability to accumulate, recall, and contextualize information over time. Large Language Models (LLMs) have mastered language, but memory remains their Achilles’ heel. EngineeringJun 5, 2025 ](https://supermemory.ai/blog/memory-engine)

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