JVMind MAT Heap Dump Analyzer

io.github.kengraryPublished by GitHub account kengraryv0.2.1Updated Oct 29, 2026

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

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Overview

AI-generated overview

Local stdio MCP server that lets an assistant analyze Java heap dumps with Eclipse MAT, including capturing live dumps from running JVMs.

What you can do
  • Discover local attachable JVMs and preview or capture a live heap dump, then poll parse status
  • Open an existing .hprof by absolute path, list known dumps and release handles
  • Get heap overview, class histograms, dominator trees and top memory consumers
  • Inspect threads, stack frames, thread locals, single objects and paths to GC roots
  • Run OQL queries, LeakHunter suspects, OOM diagnosis, connection-pool and SQL-in-threads checks
When to use it
Useful when debugging Java memory problems: hunting leaks, explaining why objects stay reachable, finding what holds the most retained heap, or diagnosing OOM and connection-pool issues from a heap dump on your own machine.
Requirements
Runs locally over stdio, typically launched with uvx from the PyPI package. Needs Python 3.10+, JDK 21+ and Eclipse MAT 1.17.x installed; a small query bundle is written into MAT's plugins on first use, so the MAT install must be writable. A local MAT helper listens on 127.0.0.1 only. No accounts or API keys declared.
Before you install
Live capture uses jmap -dump:live, triggers a Full GC and may pause the target JVM; the tool previews first and needs confirm=true. Dumps are written to the working directory unless JVMIND_MCP_DUMP_DIR or output_dir is set. OQL can read arbitrary strings from the heap, so results should be treated as private data. The bundled query service has no authentication and is intranet-only.

Installation

In SourceWeft

  1. Open JVMind MAT Heap Dump Analyzer in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

JVMind × MAT — Heap Dump Analysis

[JVMind MAT Heap Dump Analyzer MCP server]

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.

bash
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 <dependencies>.
  • 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 remote HTTPS URLs and the CLI server-creation endpoint was removed. MCPB artifacts are kept for a later retry. The Docker image is for directory review; real analysis still needs MAT + JDK 21 on the host.

Tech stack

  • Parsing/query: Java 21 + Eclipse MAT 1.17 (OSGi/Equinox)
  • MCP server: Python 3.10+ / MCP Python SDK 2.x / uv / stdio
  • Platform/agent: Python + FastAPI (the existing JVMind platform)
  • Storage: NFS (dump files) + PostgreSQL (tasks/reports)
  • Distribution: PyPI + official MCP Registry; mcp.so, Glama, and PulseMCP materials are prepared; Smithery is skipped
  • License: MIT for this project (see LICENSE); Eclipse MAT is EPL-2.0 and is not redistributed

Source: README.md at commit 3359777

Tools

19

open_heapdump

Open a local Java heap dump (.hprof) by absolute path. Starts MAT indexing in the background and returns a report_id immediately with status=PARSING. Poll get_heapdump_status until DONE. / 按绝对路径打开本地 Java 堆转储(.hprof)。后台启动 MAT 解析并立即返回 report_id 与 status=PARSING,用 get_heapdump_status 轮询直到 DONE。

Parameterspathrequired

get_heapdump_status

Get parse status and progress for a heap dump report. / 查询堆转储报告的解析状态与进度。

Parametersreport_idrequired

list_heapdumps

List heap dumps known to this MCP server with their status. / 列出本 MCP 服务已知的堆转储及其状态。

Takes no parameters.

close_heapdump

Release a heap dump handle. Set stop_service=true to also stop the MAT helper process. / 释放堆转储句柄;stop_service=true 时同时停止 MAT 辅助进程。

Parametersreport_idrequiredstop_service

list_java_processes

Discover local Java processes that can be attached for a live heap dump. Returns pid, main class, command, and masked JVM arguments. The managed MAT helper is excluded. / 主动发现本机可 attach 的 Java 进程,返回 pid、主类、命令行和已掩码的 JVM 参数;MAT 辅助进程会被排除。

Takes no parameters.

dump_java_heap

Capture a LIVE heap dump from a running JVM and start MAT parsing. First call with confirm=false (default) to preview the target, output directory, disk space, and timeout; call again with confirm=true to execute. A live dump triggers a Full GC and may pause the target JVM. The dump is written to output_dir (default: current working directory) and is automatically opened for MAT parsing. / 从运行中的 JVM 抓取 live 堆转储并自动开始 MAT 解析。先用默认 confirm=false 预览目标、输出目录、磁盘空间和超时,再用 confirm=true 执行。live dump 会触发 一次 Full GC,可能暂停目标 JVM;默认输出到当前目录。

Parameterspidrequiredconfirmtimeoutoutput_dir

mat_overview

Show heap overview (used/committed/live heap, object/class/classloader counts, JDK version, leak suspect count). Always call this first to understand a heapdump. / 展示堆总览(已用/已提交/存活堆、对象/类/类加载器数量、JDK 版本、泄漏嫌疑数量)。分析 heapdump 时先调用本工具。

Parametersreport_idrequired

mat_histogram

Class histogram sorted by shallow/retained/count. Top-N by default; pass top to override. objectSet reuses a prior OQL/RS result. / 按 shallow/retained/count 排序的类直方图,默认 Top-20。objectSet 可复用先前 OQL/RS 结果。

ParameterstopsortobjectSetreport_idrequired

mat_dominator

Dominator tree: list biggest retained-heap dominators, drill down by passing parent objectId. / 支配树:列出 retained 最大的支配者,传 parent=objectId 可下钻。

Parameterstopparentreport_idrequired

mat_threads

List threads (name/state/daemon/frameCount), or drill into a thread's stack frames (pass thread=id) or frame locals (pass frame=idx). / 列出线程(名/状态/daemon/帧数),或下钻到某线程的栈帧(传 thread=id)、某帧的局部变量(再传 frame=idx)。

Parametersframethreadreport_idrequired

mat_threadlocals

Inspect thread locals grouped by valueClass (default) or thread. Useful for finding thread-local leaks. / 按 valueClass(默认)或 thread 分组查看 ThreadLocal,常用于发现 ThreadLocal 泄漏。

ParametersgroupByreport_idrequired

mat_object

Inspect a single object (class, fields, statics, in/out refs, GC root). Required: object id. / 检查单个对象(类、字段、静态字段、入/出引用、GC Root)。必须传 object id。

Parametersidrequiredreport_idrequired

mat_path2gc

Path to GC roots

Read-only, synchronous lookup of the shortest reference chains from one object to GC roots, explaining why that object is still reachable and not collected. Returns up to five linear paths plus MAT's path tree. Typical flow: get an object id from mat_object, mat_histogram, mat_dominator, or a mat_leak_suspects preferredObjectId, confirm it with mat_object, then call this tool. Use mat_dominator instead when you want to know which object retains an entire subtree; use mat_leak_suspects when you do not yet have a specific object. Requires the report_id of a parsed dump (status=DONE).

Parametersobjectrequiredreport_idrequiredexcludeWeakSoft

mat_oql

Run an OQL query against the heap (slow!). Returns rows + a reusable resultSetId. Examples: "SELECT * FROM com.example.Foo s", "SELECT s.id.toString() FROM java.lang.String s". OQL can read arbitrary strings from the heap; handle results as private data. / 执行 OQL 查询(较慢)。返回行和可复用的 resultSetId。示例:SELECT * FROM com.example.Foo s。OQL 可读取堆内任意字符串,注意隐私。

Parametersqrequiredsortviewlimitreport_idrequired

mat_leak_suspects

Run LeakHunter (async) — returns leak suspects with retained size and description. SLOW: may take a minute. / 运行 LeakHunter(异步),返回疑似泄漏点及 retained 大小与描述。慢查询,可能耗时数十秒。

Parametersreport_idrequired

mat_diagnose_oom

Run comprehensive OOM diagnosis (async) combining leak suspects + SQL-in-threads + dominator analysis. / 综合 OOM 诊断(异步),聚合泄漏嫌疑、线程中的 SQL、支配树分析。

ParametersonlyRiskyreport_idrequiredculpritPct

mat_connection_pools

Diagnose DB connection pools (active/idle counts + leaked connections held > thresholdMs). / 诊断数据库连接池(活跃/空闲数 + 持有超过 thresholdMs 的泄漏连接)。

Parametersreport_idrequiredthresholdMs

mat_top_consumers

Top memory consumers

Read-only Top Consumers report: biggest individual objects plus retained-size breakdowns by class, class loader, and package. Use this as a quick 'who is using the most memory' overview after mat_overview. Prefer mat_histogram when you need a sortable list of every class with instance counts and shallow/retained sizes, and mat_dominator when you need to walk the object graph downward from a specific parent object. Requires the report_id of a parsed dump (status=DONE).

Parametersreport_idrequired

mat_sql_in_threads

SQL in thread stacks

Read-only scan of thread stacks for JDBC PreparedStatement objects and SQL strings, used to spot long-running or heavy queries held by threads at OOM time. Requires the report_id of a parsed dump (status=DONE). Results are sorted risky-first, then by the owning thread's retained heap, and include threadId, threadName, threadRetainedBytes, frame, source, objectId, sql, risk (risky|harmless|unknown), and reason. With onlyRisky=true, heartbeat/validation statements such as SELECT 1, SELECT 'x', /* ping */ and VALUES(1) are filtered out; pass onlyRisky=false to see all SQL-like strings.

ParametersonlyRiskyreport_idrequired

Version history

4
  1. v0.2.1LatestOct 23, 2026
  2. v0.2.0Oct 22, 2026
  3. v0.1.1Oct 19, 2026
  4. v0.1.0Oct 17, 2026

Score

90% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 days25 pts
  • Auth declared10 pts

    Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.

  • Tools listedRequired15 pts
  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts