mcpField
M

MemoryRouter

Remote
memoryrouter.aiMemory & Knowledge

About MemoryRouter

Persistent AI memory shared across Claude, ChatGPT, coding agents and compatible MCP clients

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://mcp.memoryrouter.ai/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

Tools

10
ParameterTypeRequiredDescription
limitintegerNoMaximum number of relevant memories to return. Use a large limit such as 250 for broad 'most important things' questions over tiers [3].
querystringYesA concise natural-language description of the past context to recall.
tiersarrayNoRestrict results to these memory tiers. 3 highest-level consolidated reflections (identity, principles, what matters most), 2 reflections of specific meaningful events, 1 raw verbatim memories. Use [3] for broad 'most important' or big-picture questions, [2] or [2, 3] for specific meaningful events, [1] for exact verbatim detail when you know the wording to match; otherwise drill down from [3] with inspect_memory. Omit to search all tiers blended, the right default for specific lookups. Mixing tiers is fine. Only tiers 2 and 3 carry importance ratings.
importanceintegerNoMinimum importance threshold, 1 to 10. Only reflections (tiers 2 and 3) carry ratings, so raw memories are excluded whenever this is set. Use 8 or higher with tiers [3] for broad 'most important' questions. Leave unset for general or specific searches; a high threshold hides relevant material.

Details

The maintainer has not added details yet. Check the README in the repository.

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.