MCP Memory Server for Claude and AI Tools
A production-ready Model Context Protocol memory server. Persistent semantic memory for Claude Desktop, Claude Code, Cursor, and every MCP client.
The Model Context Protocol is becoming the standard way AI tools connect to external capabilities. MCP servers give language models access to tools, data sources, and services through a unified protocol. PersistMemory is a managed MCP memory server that gives any MCP-compatible client persistent long-term memory. No self-hosting, no infrastructure management, no vector database configuration. Connect in 60 seconds and your AI tools gain semantic memory that persists across every session.
What Is an MCP Memory Server
The Model Context Protocol, developed by Anthropic, defines a standard interface for AI tools to communicate with external servers. An MCP server exposes a set of tools that the AI model can discover and invoke during conversations. A memory server specifically provides tools for storing and retrieving persistent information, giving the model a form of long-term memory that survives beyond the current session.
Without an MCP memory server, tools like Claude Desktop and Cursor are stateless. Each conversation starts fresh, and the model has no way to recall what you discussed yesterday, what decisions were made about your project architecture, or what coding patterns you prefer. An MCP memory server bridges this gap by providing store and search tools that the model calls naturally during conversation, just like it would use a web search or file reading tool.
The power of the MCP approach is that memory becomes a first-class capability of the model rather than a workaround bolted on by the application developer. The model decides when to store important information and when to search for relevant context, making memory management seamless and intelligent. You do not need to manually tell the model to remember things; it learns to use its memory tools as part of its natural reasoning process.
PersistMemory as Your MCP Server
PersistMemory is a fully managed MCP memory server. Unlike open-source alternatives that require you to run a local process, configure a vector database, and manage embedding models, PersistMemory runs as a hosted service. Your MCP client connects to PersistMemory's remote server through the standard MCP transport layer, and all the infrastructure, embeddings, vector search, storage, and backups are handled for you.
This managed approach has significant advantages for developers. There is no local process to keep running, no database to maintain, and no embedding models to download or update. Your memories are accessible from any device because they are stored in the cloud, not on your local machine. Switch between your laptop and desktop, and your AI tools have the same memory on both. The server is optimized for low-latency retrieval, so memory searches feel instant even with thousands of stored entries.
Setup in 60 Seconds
Connecting PersistMemory to your MCP client requires adding a single server entry to your configuration file. For Claude Desktop, edit the claude_desktop_config.json file. For Claude Code, use the CLI configuration command. The connection uses npx mcp-remote to bridge the MCP transport to PersistMemory's hosted server.
// Claude Desktop: ~/Library/Application Support/Claude/claude_desktop_config.json
// Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"persistmemory": {
"command": "npx",
"args": [
"-y",
"mcp-remote",
"https://mcp.persistmemory.com/sse"
]
}
}
}
// After saving, restart Claude Desktop.
// Claude will discover the memory tools automatically.
// Try: "Remember that our project uses PostgreSQL with Prisma"
// Later: "What database does our project use?"For Cursor, add the same server configuration through the Cursor MCP settings panel. For Claude Code, run the configuration command in your terminal. The setup is identical across all MCP clients: point the client at PersistMemory's server URL, and the memory tools become available immediately.
Available MCP Tools
PersistMemory exposes four MCP tools that the AI model can invoke during conversations. Each tool is designed for a specific memory operation, and the model learns to use them contextually based on the conversation flow.
store_memory
Saves a piece of information to persistent storage. The content is automatically embedded for semantic search. Supports optional namespace parameters for organizing memories into isolated spaces. The model calls this when it encounters information worth remembering, such as project decisions, user preferences, or important findings.
search_memory
Queries the memory store using semantic search. Returns the most relevant memories ranked by similarity to the query. The model calls this when it needs context about the current project, past decisions, or any previously stored information. Results include the memory content, similarity score, and creation timestamp.
list_memories
Returns all memories in a given namespace, paginated for large stores. Useful for reviewing what the model has stored, auditing memory contents, or displaying a memory dashboard to the user. Supports filtering by namespace and date range.
delete_memory
Removes a specific memory by ID. The model can use this to clean up outdated information, correct previously stored errors, or manage memory hygiene. Users can also request deletion of specific memories through natural language.
Works With Every MCP Client
PersistMemory implements the standard Model Context Protocol specification, making it compatible with every MCP client. Claude Desktop was the first MCP client and remains the most popular, but the ecosystem has expanded rapidly. Claude Code, Anthropic's command-line coding tool, uses MCP servers for tool access. Cursor, the AI-powered code editor, supports MCP servers for extending its capabilities. Windsurf and Cline also support MCP, meaning PersistMemory works as their memory layer too.
The cross-client compatibility means your memories are portable. Store information while using Claude Desktop for general tasks, and that same context is available when you switch to Cursor for coding. A memory stored through Claude Code on your laptop is searchable from Claude Desktop on your desktop. The memory layer is unified across all your AI tools, creating a single source of truth for your projects and preferences.
As new MCP clients emerge, they will work with PersistMemory automatically. Any tool that implements the MCP client specification can discover and use PersistMemory's memory tools without any PersistMemory-specific integration work. This future-proofs your investment in building up a memory store; the memories you create today will be accessible from AI tools that have not been built yet.
Self-Hosted vs Managed MCP Memory
Several open-source MCP memory servers exist that you can run locally. These typically use SQLite or a local vector database to store memories on your machine. While functional for personal use, self-hosted solutions come with significant trade-offs. You need to keep a local process running at all times, manage database backups yourself, and your memories are locked to a single machine. Embedding models must be downloaded and updated locally, consuming disk space and compute resources.
PersistMemory as a managed MCP server eliminates these operational concerns. The service runs in the cloud with automatic scaling, redundant storage, and global availability. Your memories are encrypted in transit and at rest. Updates to embedding models, search algorithms, and the MCP protocol are rolled out automatically without any action on your part. For teams, the managed approach also enables shared memory spaces where multiple developers can contribute to and benefit from a common knowledge store.
The choice depends on your requirements. If you need complete data locality and are comfortable managing infrastructure, a self-hosted solution works. For most developers and teams who want reliable, cross-device memory without operational overhead, PersistMemory's managed server is the pragmatic choice. You can start with the free tier and scale as your memory usage grows.
Related Resources
Connect Your MCP Client in 60 Seconds
Add PersistMemory as an MCP server and give Claude, Cursor, or any MCP client persistent memory. No infrastructure to manage. Free to start.