Shares persistent AI memory across Claude, ChatGPT, coding agents, and compatible MCP clients.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.
One-click editor setup isn’t available for this listing yet — we don’t have a confirmed install command, and we’d rather show nothing than point your editor at the wrong package or host. Follow the project’s own setup instructions, linked above.
Inspect callable tools, capabilities, and parameters exposed to AI agents by MemoryRouter.
The MemoryRouter MCP server provides persistent AI memory for multiple AI environments. The listed systems include Claude, ChatGPT, coding agents, and other MCP-compatible clients. Its central use case is sharing memory across those environments so information is not limited to a single assistant or agent context.
This makes MemoryRouter relevant when a developer uses more than one AI interface and wants them to access a common memory capability. The available description does not specify whether memory is organized by user, project, workspace, conversation, or another scope, so those details should not be assumed.
MemoryRouter sits between supported AI clients and a shared persistent memory layer. The source material identifies the participating environments but does not describe the underlying storage system, synchronization model, API surface, or MCP transport. It also does not explain whether clients read, write, search, update, or delete memories through separate tools.
The practical model supported by the description is straightforward: Claude, ChatGPT, coding agents, and compatible MCP clients can use the same persistent AI memory service. The exact behavior depends on the client compatibility and configuration options, none of which are documented in the supplied material.
The MemoryRouter MCP server listing does not include a README or technical setup guide. There are no supported installation commands, package names, transport details, environment variables, authentication instructions, storage guarantees, or deployment requirements to document from the available source.
Individual MCP tools are also not named. Developers should verify which operations are exposed before building workflows that depend on searching, saving, editing, or removing memories. Likewise, compatibility with a particular MCP client cannot be confirmed solely from the general statement that compatible MCP clients are supported.
The description names Claude, ChatGPT, and coding agents as supported categories, but it does not identify exact client products, versions, or configuration examples. Treat those categories as the documented compatibility scope and consult the project for current implementation details before integrating it into production workflows.
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