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JVMind MAT Heap Dump Analyzer

by kengraryversion 0.2.1i★ –iRuns on your computer
Registry nameio.github.kengrary/jvmind-mat

Install

Overview

Description from the maker (original English)

Analyze Java heap dumps locally with Eclipse MAT, including live JVM capture.

PopNx MCP’s three pillars

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

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: Other

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

  • PyPIPython’s uv installed (for the uvx command)

Which app do you use?

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": {
    "jvmind-mat": {
      "command": "uvx",
      "args": [
        "jvmind-mat-mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add jvmind-mat -- uvx jvmind-mat-mcp

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "jvmind-mat": {
      "command": "uvx",
      "args": [
        "jvmind-mat-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": {
    "jvmind-mat": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "jvmind-mat-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 kengrary, 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 Otheri

  • More stars than 0% of the other 32537 servers in this category
  • Published to the registry more recently than 72% of the other 32537 servers in this category
  • Basic checks equal to or better than 100% of the other 32537 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 JVMind MAT Heap Dump Analyzer 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 (0.2.1) reached the registry 14 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, TF Rooms

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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.

JVMind × MAT — Heap Dump Analysis

English | 中文

Java heap dump analysis built on the Eclipse Memory Analyzer (MAT) engine:

upload → parse → MAT-like web queries → domain diagnostics (connection-pool

leaks and more) → natural-language agent diagnosis.

Status: the Java parser and query service are tested. MCP Server v0.2.1

is published on PyPI and the official MCP Registry. Python platform

integration is still in progress. See PROJECT-STATUS.md.


Quick start

  1. Project overview → this file + mat-study/README.md (the design blueprint; Chinese).
  2. Current progress → PROJECT-STATUS.md (completed work, remaining tasks, lessons learned).
  3. Python team onboarding → TODO-PYTHON-TEAM.md (task list, API contract, acceptance criteria).
  4. Run the query service → query-service/DEPLOY.md (deploy + curl verification).
  5. Run the parser → parser-cli/v1-parsehd/README.md (no build required; uses the MAT distribution).
  6. Analyze heap dumps from Claude/Cursor/VS Code → mcp-server/README.md (uvx jvmind-mat-mcp, local stdio).

MCP Server (published)

A local stdio MCP server that exposes MAT heap analysis to Claude Desktop, Cursor, and VS Code. It can discover local Java processes and capture a live heap dump from a running JVM, or open an existing .hprof file. Heap dumps never leave the machine; the MAT helper binds to 127.0.0.1 only.

uvx jvmind-mat-mcp doctor      # checks JDK 21 / MAT 1.17 / permissions
ChannelLocation
PyPIhttps://pypi.org/project/jvmind-mat-mcp/
Official MCP Registryio.github.kengrary/jvmind-mat
MCPRushhttps://mcprush.com/kengrary/jvmind-mat-heap-dump-analyzer-mcp
Documentationmcp-server/README.md

Capabilities: list_java_processes / dump_java_heap for live capture, open_heapdump for existing files, then mat_overview / mat_histogram / mat_dominator / mat_threads / mat_object / mat_path2gc / mat_oql / mat_leak_suspects / mat_diagnose_oom and more — 19 tools in total.

Requirements: Python 3.10+, JDK 21+, Eclipse MAT 1.17.x (a small query bundle is installed into MAT on first use).

Tools

All analysis tools take the report_id returned by open_heapdump.

  • open_heapdump — open a local .hprof, start background indexing, return a report_id
  • get_heapdump_status — poll parse status, progress, and phase
  • list_heapdumps — list heap dumps known to this MCP server
  • close_heapdump — release a heap dump handle and optionally stop the MAT helper
  • list_java_processes — discover local attachable JVMs (pid, main class, command; MAT helper excluded)
  • dump_java_heap — preview and capture a live heap dump, then start MAT parsing (confirm=true)
  • mat_overview — heap overview: used/committed/live heap, object/class/classloader counts, JDK version
  • mat_histogram — class histogram sorted by shallow, retained, or object count
  • mat_dominator — dominator tree of the largest retained objects, with parent drill-down
  • mat_threads — list threads or drill into stack frames and frame locals
  • mat_threadlocals — inspect ThreadLocal values grouped by value class or thread
  • mat_object — inspect a single object's fields, statics, references, and GC root
  • mat_path2gc — shortest path from an object to a GC root
  • mat_oql — run an OQL query and return rows plus a reusable result set id
  • mat_leak_suspects — run LeakHunter and return suspects with retained sizes and descriptions
  • mat_diagnose_oom — composite OOM diagnosis: leak suspects + SQL in threads + dominator analysis
  • mat_connection_pools — diagnose database connection pools and leaked connections
  • mat_top_consumers — top memory consumers by retained heap
  • mat_sql_in_threads — find SQL statements in thread stacks

Architecture

  User uploads a heap dump

│ [Python/FastAPI] ← in progress (TODO-PYTHON-TEAM.md) upload / queue / progress / auth / agent ├── fork ─────────────▶ [parser-cli / V1] hprof → *.index ✅ tested │ (writes to NFS) └── reverse proxy ────▶ [query-service] queries over indexes ✅ tested (OSGi bundle, :8090) histogram / dominators / threads / OQL

  • Leak Suspects / path2gc etc. Shared: NFS (dump files) + PostgreSQL (tasks/reports)

Local MCP path (v0.2.1 published): Claude Desktop / Cursor / VS Code │ stdio ▼ [mcp-server] ──HTTP 127.0.0.1──▶ [query-service :8090] └── runs MAT ParseHeapDump when index files are missing (reuses the parser-cli V1 logic)


Repository layout

Top level
FileContents
README.mdEnglish overview (this file)
README.zh.mdChinese overview
PROJECT-STATUS.mdMilestones, module status, TODOs, lessons learned
TODO-PYTHON-TEAM.mdPython integration task list, API contract, acceptance
mat-study/ — design documents (Chinese)
#DocumentWhat it covers
—README.mdDesign blueprint (four-layer architecture, decisions, milestones)
01MAT source study and architectureHow MAT works and how to reuse it; index file format
02Core algorithms and implementationDominator tree, paths, retained size; web backend design
03Beyond OOM: connection-pool leaksWhat else a heap dump can answer; pools, thread pools, classloaders
04Tooling the MAT API for agentsHow an LLM drives MAT; tool granularity and output trimming
05End-to-end integration designUpload, queue, progress, three-layer soft-reference cache
06Technology choices and four-view APIFinalized choices and the four-view API contract
07Integrating with JVMindHow to connect to the existing platform (required for the Python team)
08MAT feature inventory and gaps57 queries reviewed; gap priorities
09Frontend implementation guidanceMaking the web UI feel like MAT
10MAT Inspector capabilitiesInspector features and what is already implemented
12Python integration planPhased plan for the Python side
13Thread-level OOM diagnosisFinding the OOM-triggering thread and its SQL
14Heap dump frontend designEndpoint mapping, async state machine, integration rules
parser-cli/ — parsing layer (hprof → index)
FileContents
README.mdParser overview (V1/V2 routes)
MAT-DEPENDENCIES.mdHow to obtain MAT dependencies, version/JDK matrix, bundle list
v1-parsehd/README.mdV1 (zero build; MAT distribution + text progress) — current
v1-parsehd/VERIFICATION.mdV1 verification report (real hprof, three bugs fixed)
v1-parsehd/mat_parse_runner.pyProgress parser (Python; reusable by the worker)
python-worker-snippet.pyWorker snippet for calling the parser
src/.../*.javaV2 skeleton (self-built jar + JSONL progress; not active)
query-service/ — query layer (OSGi bundle, :8090) ✅
FileContents
README.mdService overview (endpoints, SnapshotManager, route 2)
DEPLOY.mdDeploy + end-to-end verification (bundles.info + -clean, curl examples)
EQUINOX-A-VERIFICATION.mdEmbedded Equinox test and CNF fix (why route 2)
BUILD-TROUBLESHOOTING.mdBuild troubleshooting (p2 repositories, JDK versions)
src/.../*.java (21 files)Service implementation: core/http/model/task/view/equinox
mcp-server/ — local stdio MCP (✅ v0.2.1 published)
FileContents
README.mdInstall, client config, 19 tools, privacy, troubleshooting
src/jvmind_mat_mcp/server.pyMCP SDK tool registration
src/jvmind_mat_mcp/engine.pyHeap dump registry, background parsing, MAT lifecycle
src/jvmind_mat_mcp/vendor/Query-service OSGi bundle shipped with the package
DockerfileGlama review image (MAT/JDK not included; mount at runtime)
tests/Unit tests, stdio protocol tests, optional real-MAT integration tests
marketplace/ — directory submission pack (🟡 prepared, not submitted)
FileContents
README.mdPlatform status, remaining steps, quality gaps
metadata.jsonShared name, description, tags, install command
smithery/manifest.jsonMCPB manifest (Smithery skipped, kept for later)
mcp.so.md / glama.md / pulsemcp.mdForm copy and steps per platform

Module status

ModuleFormStatusEntry point
parser-cliV1 = MAT command; V2 = standalone jar✅ V1 testedv1-parsehd/mat_parse_runner.py
query-serviceOSGi bundle (HTTP :8090)✅ testedQueryServiceApp.java / QueryHttpServer.java
mcp-serverPython stdio MCP (PyPI + official Registry)✅ v0.2.1 publishedsrc/jvmind_mat_mcp/server.py
marketplaceDirectory copy (Smithery skipped)🟡 prepared, pending submissionmarketplace/README.md
Python integrationFastAPI + DB + agent⏳ in progressTODO-PYTHON-TEAM.md

Key facts (avoid re-learning these)

  • MAT dependencies are not on Maven Central → use Tycho (eclipse-plugin) with a p2 repository or a local Directory target; do not add .
  • Version ↔ JDK: 1.17 → JDK 21, 1.14 → JDK 17, 1.12 → JDK 11 (keep all three places in sync).
  • Deployment: copy the jar into plugins/, add a line to bundles.info (auto-start=true), and restart with `-clean` (not dropins/).
  • The query service has no authentication and is intranet-only. The Python proxy injects dumpDir (= the dump directory).
  • Reopening a dump requires both the hprof and index files on a seekable filesystem (NFS works).
  • MCP package jvmind-mat-mcp; Registry name io.github.kengrary/jvmind-mat. After changing the Java query layer, rerun mcp-server/scripts/vendor-bundle.sh, otherwise the wheel ships a stale bundle.
  • On first use the MCP server writes com.jvmind.mat.query into MAT's plugins/ and bundles.info; the MAT install must be writable.
  • Live capture uses jmap -dump:live: it dumps only live objects, triggers a Full GC, and may pause the target JVM. The default output is the server's current working directory; override it with JVMIND_MCP_DUMP_DIR or the tool's output_dir.
  • Smithery is skipped for now: its web UI only exposes remot

Only the beginning is shown; read the rest in the repo

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