
In Memoria
@pi22by7
About In Memoria
Persistent codebase intelligence that gives agents memory across sessions.
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"in-memoria": {
"command": "npx",
"args": [
"in-memoria",
"server"
]
}
}
}Tools
No tools detected
Fetch the live tool list by running this server in a temporary sandbox using the button above.
Overview
What is In Memoria?
In Memoria is an MCP (Model Context Protocol) server that gives AI coding assistants persistent memory across sessions by learning from your codebase's patterns, architecture, conventions, and decisions.
How to use In Memoria?
Install the npm package in-memoria and configure it as an MCP server for your AI coding assistant (e.g., Claude, Copilot, Cursor). Once configured, the server automatically learns from your codebase and provides context to the AI during sessions.
Key features of In Memoria
- Persists codebase knowledge across AI sessions
- Learns patterns, architecture, conventions, and decisions
- Integrates via the Model Context Protocol (MCP)
- Reduces token waste by avoiding re-analysis
- Eliminates repetitive explanations to AI assistants
Use cases of In Memoria
- Maintain architectural decisions across multiple coding sessions
- Provide instant context on naming conventions and code style
- Prevent AI from suggesting rejected patterns or decisions
- Speed up onboarding of AI assistants to large codebases
FAQ from In Memoria
What problem does In Memoria solve?
Every AI coding session starts from scratch, forcing users to repeatedly explain conventions, architecture, and decisions. In Memoria eliminates this "session amnesia" by remembering across sessions.
How does In Memoria work?
It acts as an MCP server that learns from your actual codebase—patterns, architecture, conventions, and decisions—and stores them persistently so AI assistants can query that knowledge on demand.
Which AI coding assistants does In Memoria support?
In Memoria works with any AI assistant that supports the Model Context Protocol, such as Claude, GitHub Copilot, and Cursor.
What are the runtime dependencies for In Memoria?
In Memoria is a Node.js package available on npm. You need a Node.js runtime and an MCP-compatible AI coding assistant host.
What kind of knowledge does In Memoria learn?
It learns patterns, architecture, conventions, and decisions from your codebase, including what works, what was rejected, and why—so the AI doesn't repeat mistakes.
Frequently asked questions
What problem does In Memoria solve?
Every AI coding session starts from scratch, forcing users to repeatedly explain conventions, architecture, and decisions. In Memoria eliminates this "session amnesia" by remembering across sessions.
How does In Memoria work?
It acts as an MCP server that learns from your actual codebase—patterns, architecture, conventions, and decisions—and stores them persistently so AI assistants can query that knowledge on demand.
Which AI coding assistants does In Memoria support?
In Memoria works with any AI assistant that supports the Model Context Protocol, such as Claude, GitHub Copilot, and Cursor.
What are the runtime dependencies for In Memoria?
In Memoria is a Node.js package available on npm. You need a Node.js runtime and an MCP-compatible AI coding assistant host.
What kind of knowledge does In Memoria learn?
It learns patterns, architecture, conventions, and decisions from your codebase, including what works, what was rejected, and why—so the AI doesn't repeat mistakes.
Basic information
More Other MCP servers
🪟 Windows-MCP
CursorTouchMCP Server for Computer Use in Windows

Sequential Thinking
modelcontextprotocolModel Context Protocol Servers
AutoBrowser MCP
autobrowser-aiBrowser MCP is a Model Context Provider (MCP) server that allows AI applications to control your browser
Unity MCP ✨
justinpbarnettUnity MCP acts as a bridge between AI assistants and your Unity Editor. Give your LLM tools to manage assets, control scenes, edit scripts, and automate tasks within Unity.
Production-ready MCP integrations for AI applications
Klavis-AIKlavis AI: MCP integration platforms that let AI agents use tools reliably at any scale
Comments