Skip to main content
Glama

af-jupyterlab-mcp

AF 사용자가 UChicago ATLAS Analysis Facility Kubernetes 클러스터에서 자신의 사용자별 JupyterLab 서버를 생성, 검사, 삭제할 수 있게 해주는 MCP 서버입니다. 현재 af-portal이 배포하는 것과 동일한 노트북을 LLM용 도구로 노출합니다.

아키텍처

LLM <--MCP/HTTP--> af-jupyterlab-mcp <--k8s API--> notebook namespace (Pod/Service/Secret/Ingress)
                         ^
                         | Authorization: Bearer <broker-issued JWT>
                         |
              af-mcp-platform credential broker

1단계(현재 이 저장소)는 af-portal의 portal/jupyterlab.py와 네 개의 Jinja 템플릿에서 포팅한, 노트북의 Pod/Service/Secret/Ingress 4중 항목을 관리하는 여섯 가지 도구를 제공합니다. 2단계(추적 중, 아직 구축되지 않음)는 노트북 내부에서 실행되는 Datalayer jupyter-mcp-server에 대한 타입 프록시를 추가합니다 — maniaclab/af-mcp-platform#189 참조.

Related MCP server: jlab-mcp

프로젝트 구조

src/af_jupyterlab_mcp/
├── cli.py               # argparse: `af-jupyterlab-mcp serve` (HTTP only)
├── config.py            # env-driven Settings: namespace, domain, image allowlist, quotas
├── server.py            # FastMCP setup, lifespan (k8s client + broker verifier), tool registration
├── auth/
│   └── broker.py        # extract_bearer(), get_broker_claims() -- broker-issued JWT verification
├── k8s/
│   ├── errors.py         # GuardrailError, NameConflictError, NotFoundOrNotYoursError, ...
│   ├── guardrails.py     # CPU/memory/duration range + image allowlist validation
│   ├── names.py          # sanitize_k8s_pod_name, name availability, name generation
│   ├── templates.py      # Jinja rendering of the four ported manifests
│   ├── notebooks.py      # create/get/list/delete notebook (ported portal logic)
│   ├── gpu.py            # get_gpu_availability (ported portal logic)
│   └── templates/        # pod.yaml.j2, service.yaml.j2, secret.yaml.j2, ingress.yaml.j2
│                          # (ported verbatim from af-portal/portal/templates/jupyterlab/)
└── tools/
    └── jupyterlab.py     # the six @mcp.tool() functions

도구 목록

  • create_jupyter_server

  • list_jupyter_servers

  • get_jupyter_server

  • delete_jupyter_server

  • get_gpu_availability

  • list_supported_images

모든 서버의 소유자는 항상 검증된 브로커 JWT의 claims.unixname입니다. 어떤 도구도 소유자/사용자 이름 인수를 받지 않습니다.

빌드 및 테스트 명령

pixi run test          # quick tests
pixi run lint          # pre-commit + pylint
pixi run helm-lint      # lint + smoke-render the Helm chart
A
license - permissive license
Not graded
quality - not tested
A
maintenance

Maintenance

Maintainers
<1hResponse time
0dRelease cycle
6Releases (12mo)
Commit activity

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Servers

  • F
    license
    A
    quality
    B
    maintenance
    An MCP server that enables LLMs to execute Python code on GPU-accelerated compute nodes within SLURM-managed HPC environments. It bridges local clients to remote clusters by launching JupyterLab sessions via SLURM jobs to facilitate high-performance notebook-based computation.
    7
  • A
    license
    Not graded
    quality
    B
    maintenance
    An MCP server that exposes Rucio distributed data management operations as tools for LLMs. Designed for ATLAS physicists working with grid data on analysis facilities, but usable with any Rucio instance.
    5
    Apache 2.0
  • A
    license
    A
    quality
    C
    maintenance
    Enables code execution in isolated Docker containers with persistent IPython, Node.js, or R kernels, supporting file import/export and cross-session transfers via MCP tools.
    6
    MIT

View all related MCP servers

Related MCP Connectors

  • Massed Compute MCP — GPU inventory, VM lifecycle, billing, SSH keys, and setup recipes.

  • Create, browse, remix, collaborate on, and run durable AI workflow nodes from MCP hosts.

  • This MCP server enables users to perform scientific computations regarding linear algebra and vect…

View all MCP Connectors

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/maniaclab/af-jupyterlab-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server