MemoryLens.Mcp 1.5.2

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<h1 align="center">MemoryLens MCP</h1>

<p align="center"> <a href="https://www.nuget.org/packages/MemoryLens.Mcp"><img src="https://img.shields.io/nuget/v/MemoryLens.Mcp?style=flat-square&logo=nuget&color=blue" alt="NuGet"></a> <a href="https://www.nuget.org/packages/MemoryLens.Mcp"><img src="https://img.shields.io/nuget/dt/MemoryLens.Mcp?style=flat-square&color=green" alt="NuGet Downloads"></a> <a href="https://github.com/MarcelRoozekrans/memorylens-mcp/actions"><img src="https://img.shields.io/github/actions/workflow/status/MarcelRoozekrans/memorylens-mcp/ci.yml?branch=main&style=flat-square&logo=github" alt="Build Status"></a> <a href="https://github.com/MarcelRoozekrans/memorylens-mcp/blob/main/LICENSE"><img src="https://img.shields.io/github/license/MarcelRoozekrans/memorylens-mcp?style=flat-square" alt="License"></a> </p>

<p align="center"> On-demand .NET memory profiling with concrete, AI-actionable code fix suggestions — wraps JetBrains dotMemory with a heuristic-based rule engine. </p>

<a href="https://glama.ai/mcp/servers/MarcelRoozekrans/memorylens-mcp"> <img width="380" height="200" src="https://glama.ai/mcp/servers/MarcelRoozekrans/memorylens-mcp/badge" alt="memorylens-mcp MCP server" /> </a>

Hosted deployment

A hosted deployment is available on Fronteir AI.

Quick Start

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

claude install gh:MarcelRoozekrans/memorylens-mcp

.NET Global Tool

dotnet tool install -g MemoryLens.Mcp

Prerequisites

• .NET 10 SDK or later
• JetBrains dotMemory CLI (see below for installation options)

dotMemory CLI Installation

MemoryLens MCP automatically downloads and caches the JetBrains dotMemory CLI on first use via the ensure_dotmemory tool — no manual installation required on supported platforms.

Supported Platforms (auto-download)

Cache Location

Downloaded binaries are cached at ~/.memorylens/tools/dotmemory/{version}/. Old versions are not auto-removed — delete the directory manually to free disk space.

Unsupported Platforms

Platforms not listed above (e.g. FreeBSD, Linux x86) cannot use auto-download. Set DOTMEMORY_PATH to point to an existing dotMemory CLI executable:

export DOTMEMORY_PATH="/path/to/dotMemory.sh"   # Linux/macOS
set DOTMEMORY_PATH=C:\path\to\dotMemory.exe      # Windows

Find dotMemory CLI in JetBrains Toolbox:

• Linux: ~/.local/share/JetBrains/Toolbox/apps/rider/tools/profiler/dotMemory.sh
• Windows: %LOCALAPPDATA%\JetBrains\Toolbox\apps\rider\tools\profiler\dotMemory.exe

Manual Fallback Discovery

If auto-download is unavailable, MemoryLens MCP falls back through these discovery modes in order:

1. DOTMEMORY_PATH environment variable — explicit path to the CLI executable
2. System PATH — searches for dotMemory.sh / dotMemory (Linux/macOS) or dotMemory.exe (Windows)
3. Local .NET tool manifest — dotnet tool install dotnet-dotmemory --local
4. Global .NET tool — dotnet tool install -g dotnet-dotmemory (legacy fallback)

Error Scenarios

Available MCP Tools

Built-in Rules

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 ensure_dotmemory, then snapshot with the target PID, then analyze the result 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 configurable wait period, then analyze the diff to identify objects that grew between snapshots.

License

MIT