Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
<p align="center"> <img src="icon.svg" width="128" height="128" alt="MemoryLens MCP"> </p>
<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>
<!-- mcp-name: io.github.MarcelRoozekrans/memorylens-mcp -->
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.McpPrerequisites
- .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)
| Platform | Architecture |
|---|---|
| Windows | x64, x86, ARM64 |
| Linux (glibc) | x64, ARM64, ARM |
| Linux (musl) | x64, ARM64 |
| macOS | x64 (Intel), ARM64 (Apple Silicon) |
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 # WindowsFind 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:
- `DOTMEMORY_PATH` environment variable — explicit path to the CLI executable
- System PATH — searches for
dotMemory.sh/dotMemory(Linux/macOS) ordotMemory.exe(Windows) - Local .NET tool manifest —
dotnet tool install dotnet-dotmemory --local - Global .NET tool —
dotnet tool install -g dotnet-dotmemory(legacy fallback)
Error Scenarios
| Error | Cause | Fix |
|---|---|---|
Platform '...' is not supported | Unsupported OS/arch | Set DOTMEMORY_PATH |
| Network/download failure | No internet / NuGet unreachable | Set DOTMEMORY_PATH or retry ensure_dotmemory |
chmod +x failed | Read-only filesystem | Set DOTMEMORY_PATH to a writable location |
dotMemory CLI not found | All discovery modes failed | Run ensure_dotmemory or set DOTMEMORY_PATH |
Available MCP Tools
| Tool | Description |
|---|---|
ensure_dotmemory | Downloads and verifies the JetBrains dotMemory CLI tool is available |
list_processes | Lists running .NET processes available for profiling |
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 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 requestsClaude will call compare_snapshots with a configurable wait period, then analyze the diff to identify objects that grew between snapshots.