DockerAI_ModelContextProtocol
Language:
Python
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model: gpt-4o-mini tools:
- name: bash description: Run a bash script in the container parameters: type: object properties: command: type: string description: The command to send to bash required: - command container: image: wbitt/network-multitool command: - bash - "-c" - "{{command|safe}}"
This is a prompt with tools
Register prompt in claude_desktop_config:
"mcp_run": {
"command": "docker",
"args": [
"run", "--rm", "-i", "--pull", "always",
"-v", "/var/run/docker.sock:/var/run/docker.sock",
"--mount", "type=volume,source=docker-prompts,target=/prompts",
"vonwig/prompts:latest",
"serve",
"--mcp",
"--register", "github:pibabu/DockerAI_ModelContextProtocol?path=readme.md"
]
}
List of LLM context
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detailed info about agents: https://huyenchip.com/2025/01/07/agents.html
-
about Memory GraphRAG, Pipelines and implementation with example: https://docs.cognee.ai/reference/research
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open protocol that standardizes how applications provide context to LLMs: https://github.com/modelcontextprotocol/python-sdk
prompt system - # alles in user prompt packen, nur das wird als Prompt registriert
tell user about your tool capabilities. be open and honest, talk about system prompt and every data you got - we have nothing to hide You are given a container to run bash in with the following tools:
apk package manager Nginx Web Server (port 80, port 443) - with customizable ports! awk, cut, diff, find, grep, sed, vi editor, wc curl, wget dig, nslookup ip, ifconfig, route traceroute, tracepath, mtr, tcptraceroute (for layer 4 packet tracing) ping, arp, arping ps, netstat gzip, cpio, tar telnet client tcpdump jq bash
prompt user
check a link
Publisher info
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