Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Descripción del creador (original en inglés)
Analyze Java heap dumps locally with Eclipse MAT, including live JVM capture.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"jvmind-mat": {
"command": "uvx",
"args": [
"jvmind-mat-mcp"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add jvmind-mat -- uvx jvmind-mat-mcpPégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"jvmind-mat": {
"command": "uvx",
"args": [
"jvmind-mat-mcp"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"jvmind-mat": {
"type": "stdio",
"command": "uvx",
"args": [
"jvmind-mat-mcp"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 6 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub kengrary, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (0.2.1) llegó al registro hace 14 días.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Python (uv) en tu computadora.
En la misma categoría: Spec Driven Development, Remote Desktop Commander, Zoo MCP
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
An MCP server that provides access to the Zoo API for various CAD operations and tools.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
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.
mat-study/README.md (the design blueprint; Chinese).uvx jvmind-mat-mcp, local stdio).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
| Channel | Location |
|---|---|
| PyPI | https://pypi.org/project/jvmind-mat-mcp/ |
| Official MCP Registry | io.github.kengrary/jvmind-mat |
| MCPRush | https://mcprush.com/kengrary/jvmind-mat-heap-dump-analyzer-mcp |
| Documentation | mcp-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).
All analysis tools take the report_id returned by open_heapdump.
open_heapdump — open a local .hprof, start background indexing, return a report_idget_heapdump_status — poll parse status, progress, and phaselist_heapdumps — list heap dumps known to this MCP serverclose_heapdump — release a heap dump handle and optionally stop the MAT helperlist_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 versionmat_histogram — class histogram sorted by shallow, retained, or object countmat_dominator — dominator tree of the largest retained objects, with parent drill-downmat_threads — list threads or drill into stack frames and frame localsmat_threadlocals — inspect ThreadLocal values grouped by value class or threadmat_object — inspect a single object's fields, statics, references, and GC rootmat_path2gc — shortest path from an object to a GC rootmat_oql — run an OQL query and return rows plus a reusable result set idmat_leak_suspects — run LeakHunter and return suspects with retained sizes and descriptionsmat_diagnose_oom — composite OOM diagnosis: leak suspects + SQL in threads + dominator analysismat_connection_pools — diagnose database connection pools and leaked connectionsmat_top_consumers — top memory consumers by retained heapmat_sql_in_threads — find SQL statements in thread stacks 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
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)
| File | Contents |
|---|---|
| README.md | English overview (this file) |
| README.zh.md | Chinese overview |
| PROJECT-STATUS.md | Milestones, module status, TODOs, lessons learned |
| TODO-PYTHON-TEAM.md | Python integration task list, API contract, acceptance |
mat-study/ — design documents (Chinese)| # | Document | What it covers |
|---|---|---|
| — | README.md | Design blueprint (four-layer architecture, decisions, milestones) |
| 01 | MAT source study and architecture | How MAT works and how to reuse it; index file format |
| 02 | Core algorithms and implementation | Dominator tree, paths, retained size; web backend design |
| 03 | Beyond OOM: connection-pool leaks | What else a heap dump can answer; pools, thread pools, classloaders |
| 04 | Tooling the MAT API for agents | How an LLM drives MAT; tool granularity and output trimming |
| 05 | End-to-end integration design | Upload, queue, progress, three-layer soft-reference cache |
| 06 | Technology choices and four-view API | Finalized choices and the four-view API contract |
| 07 | Integrating with JVMind | How to connect to the existing platform (required for the Python team) |
| 08 | MAT feature inventory and gaps | 57 queries reviewed; gap priorities |
| 09 | Frontend implementation guidance | Making the web UI feel like MAT |
| 10 | MAT Inspector capabilities | Inspector features and what is already implemented |
| 12 | Python integration plan | Phased plan for the Python side |
| 13 | Thread-level OOM diagnosis | Finding the OOM-triggering thread and its SQL |
| 14 | Heap dump frontend design | Endpoint mapping, async state machine, integration rules |
parser-cli/ — parsing layer (hprof → index)| File | Contents |
|---|---|
| README.md | Parser overview (V1/V2 routes) |
| MAT-DEPENDENCIES.md | How to obtain MAT dependencies, version/JDK matrix, bundle list |
| v1-parsehd/README.md | V1 (zero build; MAT distribution + text progress) — current |
| v1-parsehd/VERIFICATION.md | V1 verification report (real hprof, three bugs fixed) |
v1-parsehd/mat_parse_runner.py | Progress parser (Python; reusable by the worker) |
python-worker-snippet.py | Worker snippet for calling the parser |
src/.../*.java | V2 skeleton (self-built jar + JSONL progress; not active) |
query-service/ — query layer (OSGi bundle, :8090) ✅| File | Contents |
|---|---|
| README.md | Service overview (endpoints, SnapshotManager, route 2) |
| DEPLOY.md | Deploy + end-to-end verification (bundles.info + -clean, curl examples) |
| EQUINOX-A-VERIFICATION.md | Embedded Equinox test and CNF fix (why route 2) |
| BUILD-TROUBLESHOOTING.md | Build 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)| File | Contents |
|---|---|
| README.md | Install, client config, 19 tools, privacy, troubleshooting |
src/jvmind_mat_mcp/server.py | MCP SDK tool registration |
src/jvmind_mat_mcp/engine.py | Heap dump registry, background parsing, MAT lifecycle |
src/jvmind_mat_mcp/vendor/ | Query-service OSGi bundle shipped with the package |
| Dockerfile | Glama 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)| File | Contents |
|---|---|
| README.md | Platform status, remaining steps, quality gaps |
| metadata.json | Shared name, description, tags, install command |
smithery/manifest.json | MCPB manifest (Smithery skipped, kept for later) |
| mcp.so.md / glama.md / pulsemcp.md | Form copy and steps per platform |
| Module | Form | Status | Entry point |
|---|---|---|---|
| parser-cli | V1 = MAT command; V2 = standalone jar | ✅ V1 tested | v1-parsehd/mat_parse_runner.py |
| query-service | OSGi bundle (HTTP :8090) | ✅ tested | QueryServiceApp.java / QueryHttpServer.java |
| mcp-server | Python stdio MCP (PyPI + official Registry) | ✅ v0.2.1 published | src/jvmind_mat_mcp/server.py |
| marketplace | Directory copy (Smithery skipped) | 🟡 prepared, pending submission | marketplace/README.md |
| Python integration | FastAPI + DB + agent | ⏳ in progress | TODO-PYTHON-TEAM.md |
eclipse-plugin) with a p2 repository or a local Directory target; do not add .plugins/, add a line to bundles.info (auto-start=true), and restart with `-clean` (not dropins/).dumpDir (= the dump directory).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.com.jvmind.mat.query into MAT's plugins/ and bundles.info; the MAT install must be writable.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.Solo se muestra el principio; lee el resto en el repo