AI & Memory MCP Server

In Memoria

Name: In Memoria
Author: pi22by7

Persistent intelligence infrastructure for agentic development that gives AI coding assistants cumulative memory and pattern learning. Hybrid TypeScript/Rust implementation with local-first storage using SQLite + SurrealDB for semantic analysis and incremental codebase understanding.

Scan found nothing by pi22by7160MITRustIntermediatestdio

View on GitHub Install Guide

Install

No auto-install command available for this server.

Check the GitHub repository for setup instructions

Safety Report

86% Scan found nothing

Scanned 5 months ago

6 passed 1 warnings

Security

Authentication

details

Authentication detected: env_api_key, connection_string

Pass

CORS Policy

details

stdio transport — CORS not applicable

N/A

Rate Limiting

details

Rate limiting detected: rate_limit_middleware, throttle

Pass

Known CVEs

details

No known CVEs in dependencies

Pass

Code Quality

Dependency Audit

details

No known vulnerable dependencies detected

Pass

Dangerous Patterns

details

No dangerous code patterns detected

Pass

License

details

License: MIT

Pass

Community

Maintenance Status

details

Last commit 8 months ago

Warning

Learn about our security methodology →

Frequently Asked Questions

What is In Memoria?

Is In Memoria safe to use?

We cannot tell you that, and nobody scanning at this scale can. What we did in March 2026 was shallow-clone In Memoria and run five keyword searches over its source: auth identifiers, CORS configuration, rate-limit identifiers, the dependency manifest against a hardcoded list of 18 known-vulnerable packages, and unguarded eval/exec calls. None of them matched. A text search cannot follow a variable, judge intent, or tell you what a server does once it is running, so "nothing matched" is not "safe". What the scan does and does not cover is written out at /mcp/security.

What are alternatives to In Memoria?

Similar MCP servers include Context7, Cognee, Hindsight. Each serves a similar purpose but may differ in features, language, and compatibility.