MemoryLens.Mcp

MemoryLens MCP

On-demand .NET memory profiling with concrete, AI-actionable code fix suggestions — wraps JetBrains dotMemory with a heuristic-based rule engine.

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

claude install gh:MarcelRoozekrans/memorylens-mcp

.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 "$PWD:/workspace" -v memorylens-tools:/root/.memorylens 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.

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)

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      # 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:

• DOTMEMORY_PATH environment variable — explicit path to the CLI executable
• System PATH — searches for dotMemory.sh / dotMemory (Linux/macOS) or dotMemory.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. Discovers them from their diagnostic IPC endpoints, so it works before ensure_dotmemory
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 requests

Claude will call compare_snapshots with a configurable wait period, then analyze the diff to identify objects that grew between snapshots.

License

MIT