memorydetective

Diagnose iOS retain cycles and performance regressions from your chat window. No Xcode required.

Highlights

• CLI-driven leak hunting. Read .memgraph files captured by Xcode (or by memorydetective itself on simulators), find ROOT CYCLEs, classify them against known SwiftUI/Combine patterns, and get a one-liner fix hint. All from a script or a chat.
• MCP-native. Plugs into Claude Code, Claude Desktop, Cursor, Cline, and any other MCP client. The agent drives the full investigate → classify → suggest-fix loop without you opening Instruments.
• Honest about its limits. No mocked outputs, no over-promises. Hangs analysis works clean from xctrace; sample-level Time Profile is parsed when xctrace symbolicates the trace and returns a structured workaround notice when it can't (the underlying xctrace SIGSEGV on heavy unsymbolicated traces is an Apple-side limitation we surface explicitly). Memory Graph capture works on Mac apps and iOS simulator; physical iOS devices still need Xcode.

What's new in v1.7 (2026-05-03): catalog grew from 33 to 34 cycle patterns (swiftdata.modelcontext-actor-cycle for the SwiftData @Actor pattern), every classification now carries a fixTemplate field with concrete Swift before/after snippets the agent can adapt directly, and a new compareTracesByPattern tool does for .trace bundles what verifyFix does for memgraphs. PASS/PARTIAL/FAIL verdicts on hangs / animation-hitches / app-launch regressions. 27 → 28 MCP tools.

Also in v1.6 (same day): catalog 27 → 33, MCP Resources + Prompts surface, and the original staticAnalysisHint field. Full notes in CHANGELOG.

Quickstart

npm install -g memorydetective

Add to your MCP client config (Claude Code shown):

// ~/.claude/settings.json
{
  "mcpServers": {
    "memorydetective": { "command": "memorydetective" }
  }
}

Or use it directly from the command line:

memorydetective analyze   ~/Desktop/myapp.memgraph
memorydetective classify  ~/Desktop/myapp.memgraph

→ See Examples for chat-driven flows · API for the full tool reference · Configure for Claude Desktop / Cursor / Cline · USAGE.md for the full walkthrough including how fixes flow from diagnosis to your codebase.

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Examples

Realistic chat snippets. The agent calls the MCP tools listed in API.

Diagnose a leak from a memgraph

You: I just exported a memory graph at ~/Desktop/example.memgraph. Something's leaking after I close a detail screen. What is it?

Claude: (calls analyzeMemgraph → classifyCycle) Found 4 ROOT CYCLE blocks across 60,436 leaks. The dominant one matches swiftui.tag-index-projection with high confidence. A closure attached via .tag() on a photo carousel ForEach is capturing self strongly through _viewModel.wrappedValue, which keeps DetailViewModel and the navigation coordinator alive after dismissal.

Suggested fix: replace [weak self] capture in the tap handler with a static helper, or weak-capture the view-model via [weak coord = self.coordinator]. Want me to find the exact file?

Verify a fix actually worked

You: I shipped the fix. Compare ~/Desktop/before.memgraph to ~/Desktop/after.memgraph and tell me whether DetailViewModel count dropped.

Claude: (calls diffMemgraphs → countAlive) DetailViewModel: 12 → 0 (delta -12). The swiftui.tag-index-projection cycle is gone. Total leak count fell from 60,436 to 55,576 (−4,860). Three other ROOT CYCLEs persist. They're SwiftUI internals, not your code.

Find the slow path on a real device

You: Profile DemoApp on my iPhone for 90 seconds and tell me where the hangs are.

Claude: (calls listTraceDevices → recordTimeProfile → analyzeHangs) Recorded ~/Desktop/run.trace (90s, attached to DemoApp on iPhone 17 Pro Max). Found 23 user-visible hangs (>500 ms each), longest 1.16 s, average 769 ms. Severe load. All on the main thread. Sample-level hotspots aren't symbolicated yet; open the trace in Instruments for that step (analyzeTimeProfile returns a structured workaround notice when xctrace can't symbolicate. See CHANGELOG known limits).

End-to-end: leak → file → fix suggestion

The full loop, from artifact to code edit. Combines memory-graph analysis with Swift source-bridging.

You: Tem um leak. Memgraph em ~/Desktop/example-leaks.memgraph. The cycle points at DetailViewModel. Find where it lives in the project ~/Development/myapp/ and suggest a fix.

Claude: (calls analyzeMemgraph → classifyCycle → reachableFromCycle) Found 4 ROOT CYCLE blocks. The dominant one matches swiftui.tag-index-projection with high confidence. reachableFromCycle confirms 4 DetailViewModel instances pinning ~1100 NSURLSessionConfigurations each. The VM is the culprit, the network stack is collateral.

(calls swiftSearchPattern to locate .tag( + onImageSliderTap patterns in ~/Development/myapp/Sources/) 1 match in MyApp/Views/MediaCarousel.swift:142.

(calls swiftGetSymbolDefinition({ symbolName: "DetailViewModel", projectRoot: "...", candidatePaths: ["MyApp/ViewModels/"] })) Declared at MyApp/ViewModels/DetailViewModel.swift:18. class DetailViewModel: ObservableObject.

(calls swiftFindSymbolReferences to scope the blast radius. 7 callsites)

Suggested fix at MediaCarousel.swift:142:

// before
.tag(index)
.onImageSliderTap { index in
    self.viewModel.handlePhotoTap(at: index)
}

// after. Static helper + weak captures
.tag(index)
.onImageSliderTap { [weak vm = _viewModel.wrappedValue,
                     weak coord = self.coordinator] index in
    Self.handlePhotoTap(index: index, viewModel: vm, coordinator: coord)
}

Want me to apply this and verify with a fresh .memgraph?

---

What it saves you

The pitch in one sentence: memorydetective turns a 50–500 MB binary memgraph (or a 200 KB leaks(1) text dump) into a 2–5 KB structured summary your AI agent can actually reason about. That changes the economics of using an LLM for iOS perf investigation.

Tokens (when paired with an AI agent like Claude / Cursor / Cline)

A real-world retain-cycle investigation, run twice. Once with memorydetective, once with the agent reading the raw leaks(1) output directly:

Step	Without MCP (agent reads raw output)	With memorydetective
Load leaks text dump (~280 KB)	~70,000 input tokens	n/a
analyzeMemgraph summary	n/a	~750 input tokens
classifyCycle + fix hint	agent re-reasons over the dump per follow-up (3–4 extra turns)	1 turn, structured patternId + fixHint
findRetainers / reachableFromCycle	agent re-scans the dump	~500 tokens, scoped query
Net per investigation	~85,000 tokens, ~6 turns	~3,000 tokens, ~2 turns

Translates to roughly $0.40–$1.20 per investigation depending on the model (Claude Opus / Sonnet / Haiku). Compounds linearly with file size and investigation depth.

Developer time

The same investigation, measured by the developer:

Step	Without MCP	With memorydetective
Capture memgraph + run leaks	5 min	5 min (same)
Read & interpret leaks text dump	15–30 min (skim 200 KB of repetitive frames)	30 sec (read 3 KB summary)
Identify the responsible pattern	10–20 min (recognize the cycle shape from experience)	instant (classifier returns patternId + fix hint)
Locate the suspect type in source	10–15 min (grep + manual navigation)	30 sec (swiftGetSymbolDefinition returns file:line)
Find every callsite to gauge fix blast radius	5–10 min (Xcode / grep)	10 sec (swiftFindSymbolReferences)
Net wall-clock	45–80 min	~10 min

Numbers are rounded from a single anonymized real investigation (a SwiftUI retain cycle over a tagged ForEach that pinned ~28 MB of network-stack state). Your mileage will vary with cycle complexity and codebase size.

When the win is marginal

Be honest about where this doesn't help much:

• Tiny memgraphs (a single cycle, < 50 KB raw): MCP overhead is roughly token-neutral vs. Raw read. The dev-time win still holds (no manual cycle parsing) but the token win shrinks.
• One-shot symbol lookups without a leak attached: just use grep, you don't need this.
• First-time investigations on a new codebase: the agent still needs orientation turns regardless of MCP. The compounding wins kick in on the second and later investigations once the agent has cached the project's shape.

The win compounds with (a) file size, (b) investigation depth (multi-turn), and (c) how many leaks you investigate per quarter. For a single dev fixing one leak per year, the value is mostly the dev-time saving. For a team running CI gates with verifyFix across every PR, the token + time savings stack across hundreds of runs.

---

Configure

The memorydetective binary speaks MCP over stdio. Point any MCP-compatible client at it.

<details> <summary><b>Claude Code</b></summary>

// ~/.claude/settings.json (global) or .mcp.json (per-project)
{
  "mcpServers": {
    "memorydetective": { "command": "memorydetective" }
  }
}

</details>

<details> <summary><b>Claude Desktop</b></summary>

// ~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "memorydetective": { "command": "memorydetective" }
  }
}

Restart Claude Desktop after editing.

</details>

<details> <summary><b>Cursor</b></summary>

// ~/.cursor/mcp.json
{
  "mcpServers": {
    "memorydetective": { "command": "memorydetective" }
  }
}

</details>

<details> <summary><b>Cline (VS Code)</b></summary>

// VS Code settings.json
{
  "cline.mcpServers": {
    "memorydetective": { "command": "memorydetective" }
  }
}

</details>

<details> <summary><b>Kiro</b></summary>

Kiro supports MCP servers via its global config. The block mirrors Claude Desktop's:

{
  "mcpServers": {
    "memorydetective": { "command": "memorydetective" }
  }
}

Consult Kiro's MCP setup docs for the exact config file path on your system.

</details>

<details> <summary><b>GitHub Copilot</b> (experimental)</summary>

GitHub Copilot supports MCP servers in Agent mode (VS Code 1.94+). Add to .vscode/mcp.json in your repo:

{
  "servers": {
    "memorydetective": {
      "type": "stdio",
      "command": "memorydetective"
    }
  }
}

Copilot's MCP integration moves fast. If this snippet is stale, see the VS Code MCP docs.

</details>

---

API

28 MCP tools + 34 Resources + 5 Prompts, grouped by purpose. Tool descriptions are tagged with a category prefix ([mg.memory], [mg.trace], [mg.code], [mg.log], [mg.render], [mg.ci], [mg.discover], [meta]) so related tools are visible at a glance.

Many tools include a suggestedNextCalls field in their response. A typed list of { tool, args, why } entries pre-populated from the current result, so the orchestrating LLM can chain calls without re-reasoning. Start with getInvestigationPlaybook(kind) for the canonical sequence. Or just type /investigate-leak (one of the Prompts) in any client that exposes MCP slash commands.

The cycle classifier ships 34 named antipatterns spanning SwiftUI (including the Swift 6 / @Observable / SwiftData / NavigationStack era), Combine, Swift Concurrency (incl. AsyncSequence-on-self and the new Observations API), UIKit (Timer/CADisplayLink/UIGestureRecognizer/KVO/URLSession/WebKit/DispatchSource), Core Animation, Core Data, Coordinator pattern, and the popular third-party libs RxSwift + Realm. Each pattern carries:

• a textual one-line fixHint
• a confidence tier (high / medium / low)
• a staticAnalysisHint pointing at the SwiftLint rule that complements the runtime evidence (or an explicit gap notice when no rule exists. Reinforces the differentiator: memorydetective sees what linters miss at parse time)
• a fixTemplate with concrete Swift before/after snippets (new in v1.7) the agent can adapt directly to the user's code via the SourceKit-LSP source-bridging tools

Read & analyze (13)

Tool	What
analyzeMemgraph	Run leaks against a .memgraph and return summary (totals, ROOT CYCLE blocks, plain-English diagnosis).
findCycles	Extract just the ROOT CYCLE blocks as flattened chains, with optional className substring filter.
findRetainers	"Who is keeping <class> alive?". Returns retain chain paths from a top-level node down to the match.
countAlive	Count instances by class. Provide className for one number, or omit for top-N most-leaked classes.
reachableFromCycle	Cycle-scoped reachability. "How many <X> instances are reachable from the cycle rooted at <Y>?". Distinguishes the actual culprit from its retained dependencies.
diffMemgraphs	Compare two .memgraph snapshots: total deltas + class-count changes + cycles new/gone/persisted.
verifyFix	Cycle-semantic diff: per-pattern PASS/PARTIAL/FAIL verdict + bytes freed. CI-gateable.
classifyCycle	Match each ROOT CYCLE against a built-in catalog of 34 named antipatterns (SwiftUI / Combine / Concurrency / UIKit / Core Animation / Core Data / Coordinator / RxSwift / Realm) with confidence + textual fixHint + staticAnalysisHint (which SwiftLint rule complements this, or explicit gap) + fixTemplate (Swift before/after snippet).
analyzeHangs	Parse xctrace potential-hangs schema; return Hang vs Microhang counts + top N longest.
analyzeAnimationHitches	Parse xctrace animation-hitches schema; report by-type counts and how many hitches crossed Apple's user-perceptible 100ms threshold.
analyzeTimeProfile	Parse xctrace time-profile schema; return top symbols by sample count. Reports SIGSEGV with workarounds when xctrace can't symbolicate.
analyzeAllocations	Parse xctrace allocations schema; return per-category aggregates (cumulative bytes, allocation count, lifecycle = transient/persistent/mixed) and top allocators.
analyzeAppLaunch	Parse xctrace app-launch schema; return cold/warm launch type + per-phase breakdown (process-creation, dyld-init, ObjC-init, AppDelegate, first-frame).
logShow	One-shot query of macOS unified logging via log show --style compact with predicate / process / subsystem filters. Returns parsed entries (timestamp, type, process, subsystem, category, message).

Capture / record (3)

Tool	What	Sim	Device
recordTimeProfile	Wrap xcrun xctrace record --template "Time Profiler" --attach ... --time-limit Ns --output ....	✅	✅
captureMemgraph	Wrap leaks --outputGraph <path> <pid>. Resolves appName → pid via pgrep -x.	✅	❌. Use Xcode
logStream	Wrap log stream --style compact for a bounded duration (≤ 60 s). Returns parsed entries collected during the window.	n/a	n/a

Discover (2)

Tool	What
listTraceDevices	Parse xcrun xctrace list devices (devices + simulators + UDIDs).
listTraceTemplates	Parse xcrun xctrace list templates (standard + custom).

Render (1)

Tool	What
renderCycleGraph	Read a .memgraph, pick a ROOT CYCLE, and emit a Mermaid graph (markdown-embeddable) or Graphviz DOT. App-level classes highlighted in red; CYCLE BACK terminators amber.

CI / test integration (2)

Tool	What
detectLeaksInXCUITest	Experimental. Build the workspace for testing, run the named XCUITest, capture .memgraph baseline + after, diff. Returns passed: false when new ROOT CYCLEs appear that aren't in the user's allowlist. CI-runnable.
compareTracesByPattern	Trace-side counterpart to verifyFix. Compares two .trace bundles for a perf category (hangs, animation-hitches, or app-launch) and returns PASS/PARTIAL/FAIL with before/after stats and deltas. Apply thresholds: hangs PASS when longest is below hangsMaxLongestMs; hitches PASS when longest is below hitchesMaxLongestMs (default 100ms. Apple's user-perceptible threshold); app-launch PASS when total is below appLaunchMaxTotalMs (default 1000ms).

Swift source bridging (5)

Pair the memory-graph diagnosis with source-code lookups via SourceKit-LSP. Closes the loop "found this leak in the cycle → find the file/line in your project".

Tool	What
swiftGetSymbolDefinition	Locate the file:line where a Swift symbol is declared. Pre-scans candidatePaths (or hint.filePath) with a fast regex, then asks SourceKit-LSP for jump-to-definition.
swiftFindSymbolReferences	Find every reference to a Swift symbol via SourceKit-LSP textDocument/references. Requires an IndexStoreDB for cross-file results. The response carries a needsIndex hint when the index is missing.
swiftGetSymbolsOverview	List top-level symbols (classes, structs, enums, protocols, free functions) in a Swift file via documentSymbol. Cheap orientation when the agent lands in a new file.
swiftGetHoverInfo	Type info / docs at a (line, character) position. Disambiguates self captures: a class self in a closure can leak; a struct self can't.
swiftSearchPattern	Pure regex search over a Swift file (no LSP, no index). Catches what LSP misses: closure capture lists, Task { ... self ... } blocks, custom patterns from a leak chain.

These tools require macOS + Xcode (full Xcode, not just Command Line Tools. xcrun sourcekit-lsp must be available). They start a sourcekit-lsp subprocess per project root and reuse it across calls; the subprocess shuts down after a 5-minute idle window.

Why captureMemgraph doesn't work on physical iOS devices: leaks(1) only attaches to processes running on the local Mac (which includes iOS simulators). Memory Graph capture from a real device goes through Xcode's debugger over USB/lockdownd. Different mechanism, no public CLI equivalent.

Resources (34)

The cycle-pattern catalog is also surfaced as MCP resources, browsable at memorydetective://patterns/{patternId}. Each resource is a markdown body with the pattern name, a longer description, and the fix hint. Use this to let an agent (or a human in a UI-aware MCP client) browse the catalog without burning a classifyCycle call.

memorydetective://patterns/swiftui.tag-index-projection
memorydetective://patterns/concurrency.async-sequence-on-self
memorydetective://patterns/webkit.wkscriptmessagehandler-bridge
memorydetective://patterns/swiftdata.modelcontext-actor-cycle
…

resources/list returns all 34 entries. resources/read resolves any memorydetective://patterns/{id} URI to its markdown body.

Prompts (5)

Investigation playbooks are exposed as MCP prompts (slash commands in clients that surface them, e.g. Claude Code).

Slash command	What it does	Args
/investigate-leak	Runs the canonical 6-step memgraph-leak investigation: analyzeMemgraph → classifyCycle → reachableFromCycle → swiftSearchPattern → swiftGetSymbolDefinition → swiftFindSymbolReferences.	memgraphPath
/investigate-hangs	Diagnose user-visible main-thread hangs from a .trace.	tracePath
/investigate-jank	Diagnose dropped frames / animation hitches from a .trace.	tracePath
/investigate-launch	Diagnose cold/warm launch slowness from a .trace.	tracePath
/verify-cycle-fix	Diff a before/after pair of .memgraph snapshots to confirm a fix landed.	before, after

Each prompt fills the canonical playbook's argument templates with the user-provided values, then hands the agent a ready-to-execute brief. Calls the same tools listed in Read & analyze. Prompts are an orchestration shortcut, not a separate engine.

CLI mode

The same binary is also a thin CLI for scripting and CI:

memorydetective analyze   <path-to-.memgraph>    # totals, ROOT CYCLEs, diagnosis
memorydetective classify  <path-to-.memgraph>    # match patterns + render fix hint
memorydetective --help
memorydetective --version

When called with no arguments, the binary starts as an MCP server over stdio.

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Requirements

• macOS with Xcode Command Line Tools (xcode-select --install)
• Node.js ≥ 20

Develop

git clone https://github.com/carloshpdoc/memorydetective
cd memorydetective
npm install
npm test                  # 61 unit tests
npm run build             # build → dist/
npm run dev               # tsx, stdio mode (dev mode)
./scripts/demo.sh         # full demo against a real .memgraph (set MEMGRAPH=path)

Contributing

Contributions are welcome. Bug reports, feature requests, new cycle patterns, all of it.

• Bugs / feature requests: open an issue.
• PRs: fork → branch → npm install → make changes → npm test (206 tests must stay green) → open a PR with a concise description of what changed and why.

Adding a cycle pattern to classifyCycle

classifyCycle ships with 34 built-in patterns covering SwiftUI (incl. Swift 6 / @Observable / SwiftData / NavigationStack), Combine, Swift Concurrency (incl. AsyncSequence-on-self and Observations), UIKit (Timer / CADisplayLink / UIGestureRecognizer / KVO / URLSession / WebKit / DispatchSource), Core Animation, Core Data, the Coordinator pattern, RxSwift, and Realm. To add one:

1. Edit src/tools/classifyCycle.ts. Add an entry to PATTERNS with id, name, fixHint, and a match function.
2. Add a test in src/tools/readTools.test.ts that asserts the new pattern fires against a representative memgraph fixture.
3. Add a staticAnalysisHint entry in src/runtime/staticAnalysisHints.ts (the test in that file enforces 1:1 coverage with PATTERNS).
4. Add a fixTemplate entry in src/runtime/fixTemplates.ts (same 1:1 coverage guard).
5. Open a PR.

Support this project

If memorydetective saves you time, you can support continued development:

• ☕ Buy me a coffee
• 💖 Sponsor on GitHub

Every contribution helps keep this maintained and documented.

License

Apache 2.0. See LICENSE and NOTICE.

Permits commercial use, modification, distribution, patent use. Includes attribution clause via the NOTICE file.

Why "memorydetective"?

Hunting retain cycles in SwiftUI feels like detective work: you have a body (the leaked instance), a crime scene (the .memgraph), and a chain of suspects (the retain chain). The tool helps you read the evidence and name the killer. The brand follows the work.