mcp
VerifiedPersistent memory for AI assistants across clients.
What is the mcp MCP server?
This server enables consistent memory across different AI platforms by storing information persistently. Users save context or facts once and retrieve them later regardless of the client used.
It supports seamless recall for ongoing conversations or tasks without needing to re-enter data in each session.
Install & connect
Add this to your MCP client config. Pick your client below and copy.
{
"mcpServers": {
"mcp": {
"url": "https://api.butlerbrain.ai/mcp"
}
}
}Example prompts
Once connected, try asking your AI client:
Security & permissions
Requires streamable-http access to a remote or local server endpoint. No API keys or secrets are documented; it touches stored memory data.
What you can do with mcp
Cross-client memory
Save project details in one AI and recall them in another.
Conversation continuity
Maintain context across multiple sessions and platforms.
Shared knowledge base
Store facts or preferences accessible by any MCP-compatible assistant.
How to use mcp
- 1Configure the server with streamable-http transport.
- 2Connect your MCP client to the server endpoint.
- 3Use save commands to store memory entries.
- 4Query the server from any supported client to recall data.
- 5Verify persistence across different AI platforms.
mcp: pros & cons
Pros
- +Works across multiple AI clients without duplication
- +Simple persistent storage model
- +No need to re-enter context repeatedly
Cons
- –No tools or parameters documented in available info
- –Limited details on data management or security
- –Depends on HTTP connectivity for access
Frequently asked questions
It provides persistent memory that can be shared across AI assistants.
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