teleskopio logo

teleskopio

Organization
teleskopio

teleskopio is a lightweight kubernetes web client

Publisherteleskopio
Repositoryteleskopio
LanguageTypeScript
Forks
7
Stars
162
Available tools
0
Transport typestdio
Categories
Links
  • Connect tools to AI workflows

    teleskopio exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 0 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    162 stars and 7 forks from the linked repository.

Features

  • Multiple config support – respect $KUBECONFIG variable and checks the config.yaml file.
  • Simple JWT token authorization, admin and viewer role - Full access (admin) or Read Only access (viewer) to cluster.
  • Resource editor/creator - integrated Monaco Editor with syntax highlighting.
  • Live updates - real-time resource changes with Kubernetes watchers.
  • Pod logs and Event's - inspect logs and event history directly in the UI, owner links, share link to resource.
  • Light and dark themes and fonts.
  • Scale resources Deployments, ReplicaSets
  • Shortcuts to filter CTRL + F any resource, jump to section CTRL + J any menu.
  • Objects multi-select operations (delete, drain, cordon, e.t.c.)
  • go-client - based native implementation that interacts directly with the Kubernetes API server, no pulling, only websocket events.
  • Kubernetes resource schemas per API version.
  • Helm integration.
  • Zero dependencies, no need to install kubectl, helm on the host.
  • Air-gapped environments ready. No external requests.
  • Built-in MCP server

Install

Linux

Download release.

MacOS

Use brew (ARM and Intel):

  1. brew tap teleskopio/homebrew-teleskopio
  2. brew install --cask teleskopio

Docker

  1. Pull docker image from Packages
sh
docker pull ghcr.io/teleskopio/teleskopio:latest
  1. Generate config
sh
docker run -it --rm ghcr.io/teleskopio/teleskopio:latest config > config.yaml
  1. Edit config, generate user passwords, add kube configs
sh
$ htpasswd -nbB admin MySecret123 # apache2-utils
> admin:$2y$05$U7puDu7wKOMP6i4eI1nO4ux909bH8FuPadEQq2oxx7SRXrBh3xJIG
vim config.yaml # edit confAig and add admin user
# add kubeconfig content to kube.configs
# check example in config.yaml
  1. Run

Run with --network=host if you're using kind cluster

bash
docker run -it --rm --network=host -p 3080:3080 \
  -v $(pwd)/config.yaml:/usr/bin/config.yaml ghcr.io/teleskopio/teleskopio:latest \
  --config=/usr/bin/config.yaml

Or run with docker network

bash
docker run -it --rm -p 3080:3080 \
  -v $(pwd)/config.yaml:/usr/bin/config.yaml ghcr.io/teleskopio/teleskopio:latest \
  --config=/usr/bin/config.yaml
5:47AM INF set loglevel level=DEBUG
5:47AM INF version version=""
5:47AM INF initialize web server addr=:3080
...

Helm

Right now only building helm package from sources install option available.

Clone repository. Run make build-helm-chart (helm binary in PATH is required.)

Check out helm chart values.yaml.

By default RBAC's for teleskopio give access to all cluster and to any kind of operation.

bash
$ git clone git@github.com:teleskopio/teleskopio.git
$ cd teleskopio
$ make build-helm-char
helm package ./deploy/teleskopio
Successfully packaged chart and saved it to: /home/dev/teleskopio/teleskopio-0.1.4.tgz
# Add you own config.yaml
$ cat config.yaml
service:
  type: ClusterIP
  port: 3090

config:
  name: config
  content:
    log_color: false
    log_json: true
    log_level: INFO
    server_http: ":3090"
    jwt_key: "b2436e01424c714e4583f2f2851a0e1304440157" # openssl rand -hex 20
    auth_disabled: false
    users:
      - username: admin
        password: "$2y$05$PgEhSAwkE0RlbYiJqSxF/e529Xu5HGey.cEY/qqoksLlFckk3kaiW" # htpasswd -nbB admin MySecret123
        role: "admin"
      - username: user
        password: "$2y$05$PgEhSAwkE0RlbYiJqSxF/e529Xu5HGey.cEY/qqoksLlFckk3kaiW"
        role: "viewer"
    kube:
      configs:
# Install local helm chart with own values.yaml
$ helm install teleskopio ./teleskopio-0.1.4.tgz -f values.yaml
NAME: teleskopio
LAST DEPLOYED: Sun Feb  1 15:39:52 2026
NAMESPACE: default
STATUS: deployed
REVISION: 1
DESCRIPTION: Install complete
NOTES:
1. Get the application URL by running these commands:
  export POD_NAME=$(kubectl get pods --namespace default -l "app.kubernetes.io/name=teleskopio,app.kubernetes.io/instance=teleskopio" -o jsonpath="{.items[0].metadata.name}")
  export CONTAINER_PORT=$(kubectl get pod --namespace default $POD_NAME -o jsonpath="{.spec.containers[0].ports[0].containerPort}")
  echo "Visit http://127.0.0.1:8080 to use your application"
  kubectl --namespace default port-forward $POD_NAME 8080:$CONTAINER_PORT

# Follow NOTES instruction and use port-forward
$ kubectl --namespace default port-forward $POD_NAME 8080:$CONTAINER_PORT
Forwarding from 127.0.0.1:8080 -> 3090
Forwarding from [::1]:8080 -> 3090

Open http://127.0.0.1:8080.

Configuration

config.example

Use teleskopio MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once teleskopio is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add teleskopio as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the teleskopio MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "teleskopio": {
      "command": "npx",
      "args": [
        "-y",
        "<mcp-server-package>"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the teleskopio MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the teleskopio MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use teleskopio to help me with this task?
teleskopio
Sure. I read it.
Here is what I found using teleskopio.

Frequently asked questions

What is the teleskopio MCP server used for?

teleskopio is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use teleskopio MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use teleskopio with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use teleskopio MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With teleskopio connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect teleskopio MCP to TypingMind?

teleskopio runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does teleskopio MCP provide in TypingMind?

teleskopio exposes MCP capabilities that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use teleskopio MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If teleskopio requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

Related MCP Servers

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇