How do I install the AI Memory MCP server for Claude?

Install the AI Memory MCP server by running "pip install aimemory-mcp-server" in your terminal. Then add the server configuration to your Claude Desktop config file (claude_desktop_config.json) and restart Claude Desktop. The entire setup takes less than 5 minutes.

What tools does the Claude Desktop MCP server provide?

The Claude Desktop MCP server provides 7 tools: search_memory (full-text search), get_context (relevant snippets), list_memories (browse conversations), get_conversation (full conversation by ID), add_memory (save new notes), delete_memory (remove data), and get_stats (memory statistics and platform breakdown).

Where is the Claude Desktop MCP config file?

On macOS, the Claude Desktop config file is located at ~/Library/Application Support/Claude/claude_desktop_config.json. On Windows, it is at %APPDATA%\Claude\claude_desktop_config.json. Add your MCP server configuration to the mcpServers object in this file.

Can I use the MCP server with Claude Desktop and other AI tools at the same time?

Yes. The AI Memory MCP server works with 113+ MCP-compatible clients simultaneously. You can connect Claude Desktop, Cursor, Windsurf, Cline, and many other AI tools to the same memory server. All clients share access to the same conversation history.

Do I need Python installed to run the MCP server for Claude?

Yes, the pip-installed MCP server requires Python 3.10 or higher. However, you can also use the hosted version at aimemory.pro/api/mcp which requires no local installation at all — just add the URL to your Claude Desktop config.

MCP Server for Claude Desktop: The Complete Setup Guide

Q: Is the MCP server for Claude Desktop free?

Yes, the AI Memory MCP server for Claude Desktop is completely free and open source. You can install it via pip, and there are no API keys, subscriptions, or usage limits required. You just need to upload your conversations to aimemory.pro first.

Claude Desktop becomes exponentially more powerful when connected to an MCP server. Instead of starting every conversation from scratch, your Claude desktop MCP server gives Claude access to your entire conversation history — across every AI platform you use. Here is everything you need to know to set it up.

🔑 Key Takeaway

An MCP server for Claude Desktop lets Claude search, read, and add to your AI conversation memory using the open Model Context Protocol. Install it with pip install aimemory-mcp-server or use the hosted version — setup takes under 5 minutes.

What Is MCP and Why Does It Matter for Claude?

The Model Context Protocol (MCP) is an open standard created by Anthropic that defines how AI assistants connect to external data sources and tools. Think of it as a universal adapter — any MCP-compatible client can talk to any MCP-compatible server using the same protocol. Over 113 clients already support MCP, including Claude Desktop, Cursor, Windsurf, Cline, and more.

Before MCP, every AI tool had its own isolated memory or none at all. If you spent an hour debugging a React hydration error with ChatGPT, Claude had no idea that conversation existed. An MCP server for Claude breaks down those silos by exposing your conversation history through a standardized set of tools that Claude can call directly inside Claude Desktop.

This matters because Claude Desktop is one of the most popular MCP clients available. Anthropic built native MCP support directly into the desktop app, meaning you can connect any claude desktop MCP server without plugins, extensions, or workarounds. The configuration is a simple JSON file.

Step-by-Step Installation

There are two ways to set up an MCP server for Claude Desktop: the pip install method for a local server, or the hosted URL method if you prefer zero local setup.

Option A: Install via pip (Local Server)

Step 1: Install the package

pip install aimemory-mcp-server

Requires Python 3.10+. The package includes all dependencies.

Step 2: Upload your conversations

Visit aimemory.pro and upload your ChatGPT, Claude, DeepSeek, or other AI conversation exports. This populates the memory database that your MCP server for Claude will query.

Step 3: Start the server

aimemory-mcp-server --port 8080

The server starts on localhost:8080 by default. It uses the SSE transport protocol for real-time communication with Claude Desktop.

Option B: Use the Hosted URL (No Installation)

If you do not want to run a local server, you can use the hosted version directly. Skip the pip install entirely and just point Claude Desktop at the remote endpoint. See the config JSON below.

Claude Desktop Config JSON

Claude Desktop reads its MCP server configuration from a JSON file. Open it in any text editor:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

Windows: %APPDATA%\Claude\claude_desktop_config.json

Add one of the following configurations to your claude_desktop_config.json:

Hosted Version (Recommended)

{ "mcpServers": { "ai-memory": { "url": "https://aimemory.pro/api/mcp" } } }

Local Server (After pip install)

{ "mcpServers": { "ai-memory": { "command": "aimemory-mcp-server", "args": ["--port", "8080"] } } }

⚠️ Important

After editing the config file, you must restart Claude Desktop for the changes to take effect. The MCP server for Claude Desktop will appear in the tools panel once connected successfully.

Available Tools: 7 MCP Memory Tools

Once your claude desktop MCP server is connected, Claude gains access to these 7 tools for managing your conversation memory:

🔍 search_memory

Full-text search across all your conversations using FTS5 syntax. Supports AND, OR, NOT operators and phrase matching. Filter by platform, date range, or limit results.

Input: {query: string, platform?: string, limit?: number}

📝 get_context

Retrieve relevant context snippets for a given topic, optimized for providing Claude with conversation history. Token-budget aware — respects the max_tokens parameter to stay within context limits.

Input: {topic: string, max_tokens?: number}

📋 list_memories

List recent conversations with optional platform filtering. Browse your entire conversation history with pagination support. Great for exploring what you have discussed across AI tools.

Input: {limit?: number, platform?: string}

💬 get_conversation

Retrieve a full conversation by its ID, including every message with role, content, and timestamps. Use this when Claude needs detailed context from a specific past discussion.

Input: {conversation_id: string}

➕ add_memory

Add a new conversation or note to your memory store. Claude can save important context, decisions, or summaries for future reference. Supports tagging by platform.

Input: {title: string, content: string, platform?: string}

🗑️ delete_memory

Delete a specific conversation by ID or wipe all session data with a confirmation flag. Full data control — nothing is stored without your consent.

Input: {conversation_id?: string, confirm?: boolean}

📊 get_stats

Get memory statistics including total conversation count, per platform breakdown, storage size, and date ranges. Useful for understanding the scope of your AI memory at a glance.

Input: {'}

Use Cases for Your MCP Server for Claude

🐛 Cross-Platform Debugging

"Search my memory for the PostgreSQL connection pooling issue we solved last month." — Your MCP server for Claude Desktop finds the exact solution from a ChatGPT conversation you had weeks ago, saving you from re-debugging the same problem.

📚 Research Synthesis

"What have I learned about React Server Components across all my AI conversations?" — Claude Desktop pulls insights from ChatGPT, DeepSeek, and previous Claude discussions, synthesizing a comprehensive answer from your entire history.

🏗️ Project Continuity

"What authentication approach did we decide on for project-alpha?" — Instead of searching through Slack threads or old notes, your claude desktop MCP server retrieves the exact architecture decision from a past AI conversation.

💡 Knowledge Capture

"Save this conversation summary to my memory with tag 'onboarding-patterns'." — Claude uses the add_memory tool to store important context for future sessions, building a persistent knowledge base across all your AI interactions.

🔄 Workflow Automation

Connect your MCP server for Claude to multiple AI tools simultaneously. Use Claude Desktop for planning, Cursor for coding, and both share the same memory. Your context travels with you across every tool.

Technical Details

Protocol: JSON-RPC 2.0 over HTTPS (Streamable HTTP Transport)
Endpoint: https://aimemory.pro/api/mcp
Database: SQLite with FTS5 full-text search and WAL mode
Authentication: Session cookie (aim_session) — no API keys needed
Tools: 7 (search_memory, get_context, list_memories, get_conversation, add_memory, delete_memory, get_stats)
Python Package: aimemory-mcp-server on PyPI

Frequently Asked Questions

What is an MCP server for Claude Desktop?

An MCP server for Claude Desktop is a service that implements the Model Context Protocol, giving Claude the ability to access external tools and data. The AI Memory MCP server specifically lets Claude search, read, and manage your conversation history from every AI platform you use.

How do I install the MCP server for Claude?

Run pip install aimemory-mcp-server to install locally, then add the configuration to your claude_desktop_config.json. Alternatively, use the hosted URL https://aimemory.pro/api/mcp for zero-installation setup.

Is the MCP server for Claude Desktop free?

Yes, the AI Memory MCP server is completely free and open source. No API keys, no subscriptions, no usage limits. Upload your conversations to aimemory.pro and connect Claude Desktop — that is all you need.

Where is the Claude Desktop config file?

On macOS: ~/Library/Application Support/Claude/claude_desktop_config.json. On Windows: %APPDATA%\Claude\claude_desktop_config.json. Add your MCP server entries to the mcpServers object in this file.

Can I use the same MCP server with other AI tools?

Absolutely. The AI Memory MCP server works with 113+ MCP-compatible clients. Connect Claude Desktop, Cursor, Windsurf, Cline, and more to the same server — they all share access to your unified conversation memory.

Do I need Python installed to use the MCP server?

Only if you want to run a local server. The pip-based installation requires Python 3.10+. However, the hosted version at aimemory.pro/api/mcp requires no local installation — just add the URL to your Claude Desktop config JSON.

Get Started with Your MCP Server for Claude Desktop

Setting up an MCP server for Claude Desktop takes less than 5 minutes and transforms Claude from a stateless assistant into a persistent knowledge partner. Whether you choose the pip install aimemory-mcp-server route or the hosted URL, Claude will gain access to your full conversation history across every AI platform.

Visit aimemory.pro and upload your AI conversations
Add the MCP server configuration to your Claude Desktop config JSON
Restart Claude Desktop and start asking about your conversation history

Your AI memory is persistent, searchable, and private — powered by an open protocol that works across 113+ clients.

Read the full MCP documentation →