Memorylens MCP

Name: Memorylens MCP
Author: MarcelRoozekrans

by MarcelRoozekransversion 2.1.3i★ –iRuns on your computer

Registry nameio.github.MarcelRoozekrans/memorylens-mcp

Install

Overview

Description from the maker (original English)

MCP server for .NET memory profiling — in-process heap snapshots via EventPipe with leak heuristics

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Search & AI memory

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "memorylens": {
      "command": "npx",
      "args": [
        "-y",
        "memorylens-mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add memorylens -- npx -y memorylens-mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "memorylens": {
      "command": "npx",
      "args": [
        "-y",
        "memorylens-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "memorylens": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "memorylens-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account MarcelRoozekrans, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

More stars than 0% of the other 7286 servers in this category
Published to the registry more recently than 84% of the other 7286 servers in this category
Basic checks equal to or better than 100% of the other 7286 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Memorylens MCP safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (2.1.3) reached the registry 7 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js, .NET on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated yesterday

Install

Codebase Memory

by DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Runs on your computer★ 48,148MITUpdated 21 days ago

Install

Exa

by exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated last month

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

MemoryLens MCP

On-demand .NET memory profiling with concrete, AI-actionable code fix suggestions — no profiler to install.

Hosted deployment

A hosted deployment is available on Fronteir AI.

Quick Start

npx (any MCP client)

"mcpServers": { "memorylens": { "type": "stdio", "command": "npx", "args": ["-y", "memorylens-mcp"] } } }

The npm package ships no server code — it is a launcher that installs the MemoryLens.Mcp .NET global tool at a matching version and execs it, so the .NET 10 SDK must be on `PATH`. Subsequent starts skip the install entirely and work offline.

VS Code / Visual Studio (via dnx)

Add to your MCP settings (.vscode/mcp.json or VS settings):

"servers": { "memorylens": { "type": "stdio", "command": "dnx", "args": ["MemoryLens.Mcp", "--yes"] } } }

Claude Code Plugin

/plugin install memorylens --marketplace MarcelRoozekrans/memorylens-mcp

The plugin runs the NuGet tool through dnx, so it needs the .NET 10 SDK and nothing else.

.NET Global Tool

dotnet tool install -g MemoryLens.Mcp

Docker

docker build -t memorylens-mcp .

docker run -i --rm --pid=host --cap-add=SYS_PTRACE \ -v /tmp:/tmp \ -v "$PWD:/workspace" memorylens-mcp

Profiling from a container needs ptrace and the host PID namespace, and on Docker Desktop that namespace is the Linux VM rather than your desktop — see docs/docker.md before choosing this route.

-v /tmp:/tmp is what makes list_processes return anything — the runtime's diagnostic sockets live in the temp directory — and it is also what keeps snapshots alive after --rm, since they are written to /tmp/memorylens-snapshots inside the container. -v "$PWD:/workspace" is only so .memorylens.json is picked up; nothing is written there.

Prerequisites

.NET 10 SDK, 10.0.4xx feature band (pinned in global.json)

Running a filtered subset of the tests, e.g. dotnet test --filter , will exit with code 9 and print error: 1, failed: 0. That's the test project's discovery-collapse guard (--minimum-expected-tests) firing because the filter left fewer tests than expected — it is not a test failure, and a full dotnet test run is unaffected.

How Collection Works

MemoryLens collects heap data in-process over EventPipe, the .NET runtime's built-in diagnostics channel. There is no profiler to install, no download on first use, and no external tool on PATH.

snapshot attaches to a running .NET process by pid, induces a collection, and aggregates the heap into per-type counts and sizes. Snapshots are written as small JSON files under your temp directory and referenced by a short id.

On Linux and in containers, attaching to another process's diagnostic endpoint may require matching UID or SYS_PTRACE — see docs/docker.md.

Available MCP Tools

Tool	Description
`list_processes`	Lists running .NET processes available for profiling, discovered from their diagnostic IPC endpoints
`snapshot`	Captures a single memory snapshot of a target process
`compare_snapshots`	Captures two snapshots with configurable delay and compares them
`analyze`	Runs the rule engine against a captured snapshot and returns findings
`get_rules`	Lists all available analysis rules with their metadata

Built-in Rules

ID	Severity	Category	Description
ML001	critical	leak	Event handler leak detected
ML002	critical	leak	Static collection growing unbounded
ML003	high	leak	Disposable object not disposed
ML004	high	fragmentation	Large Object Heap fragmentation
ML005	medium	retention	Object retained longer than expected
ML006	medium	allocation	Excessive allocations in hot path
ML007	medium	retention	Closure retaining unexpected references
ML008	low	allocation	Array/list resizing without capacity hint
ML009	low	pattern	Finalizer without Dispose pattern
ML010	low	pattern	String interning opportunity

Configuration

Create a .memorylens.json file in your project root to customize rule behavior:

"rules": { "ML001": { "enabled": true, "severity": "critical" }, "ML002": { "enabled": true, "severity": "critical" }, "ML003": { "enabled": true, "severity": "high" }, "ML004": { "enabled": true, "severity": "high" }, "ML005": { "enabled": true, "severity": "medium" }, "ML006": { "enabled": true, "severity": "medium" }, "ML007": { "enabled": true, "severity": "medium" }, "ML008": { "enabled": true, "severity": "low" }, "ML009": { "enabled": true, "severity": "low" }, "ML010": { "enabled": true, "severity": "low" } } }

Usage Examples

Single Snapshot

Capture a memory snapshot of a running process to inspect current memory state:

> /memorylens

Take a snapshot of my running API (PID 12345)

Claude will call snapshot with the target PID, then analyze the returned snapshot id and present findings ordered by severity.

Before/After Comparison

Detect memory growth by comparing two snapshots taken with a delay:

> /memorylens

Check if my app has a memory leak — compare before and after processing 1000 requests

Claude will call compare_snapshots with a delaySeconds value (default 10 seconds) between the two captures, then analyze the diff to identify objects that grew between snapshots.

Family

MemoryLens MCP is part of a small family of .NET projects for AI work:

AI.Sentinel: Security monitoring middleware for IChatClient: prompt injection, hallucination and PII detection with an audit trail.
Minos.NET: Typed, source-generated decision questions with calibrated answers.
Rag.NET: A modular retrieval-augmented generation pipeline on Microsoft.Extensions.AI.
Roslyn CodeLens MCP: Semantic .NET code intelligence for AI agents over MCP.

Built on ZeroAlloc

MemoryLens MCP uses these ZeroAlloc libraries, which are source generators and analyzers with no reflection at runtime:

ZeroAlloc.Analyzers

License

MIT

Memorylens MCP

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Search & AI memoryi

Common questions

Alternatives

Context7

Codebase Memory

Exa

README from the maker

Hosted deployment

Quick Start

npx (any MCP client)

VS Code / Visual Studio (via dnx)

Claude Code Plugin

.NET Global Tool

Docker

Prerequisites

How Collection Works

Available MCP Tools

Built-in Rules

Configuration

Usage Examples

Single Snapshot

Before/After Comparison

Family

Built on ZeroAlloc

License