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‎docs/content/projects/_index.md

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---
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title: "Other Projects"
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---

‎docs/content/tools/_index.md

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type: docs
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---
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## Background
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The `mcp/run` container is an mcp server, but it can be extended by giving it new
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containers, as tools, and prompts. Existing containers, like `curl` or `ffmpeg`, can
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then be exposed as MCP servers.
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```mermaid
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flowchart LR
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desktop["Claude Desktop"]
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subgraph docker["Docker"]
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mcp["mcp/run"]
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end
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desktop --> docker
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docker -- extended by --- box1["Tools/Prompt Def (curl)"]
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docker -- extended by --- box2["Tools/Prompt Def (ffmpeg)"]
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style desktop fill:#f9f9f9,stroke:#333,stroke-width:2px
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style docker fill:#e6f3ff,stroke:#333,stroke-width:2px,color:#0066cc
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style mcp fill:#fff,stroke:#333,stroke-width:1px
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style box1 fill:#f9f9f9,stroke:#333,stroke-width:2px
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style box2 fill:#f9f9f9,stroke:#333,stroke-width:2px
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```
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Our current definitions are markdown documents (see [examples](examples)).
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```markdown
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---
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tools:
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- name: curl
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---
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# prompt
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Run the curl command, in silent mode, to fetch gists for user slimslenderslacks from GitHub.
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```
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## Getting Started
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We can use this to extend MCP clients like Claude Desktop, and create test new tools and prompts using
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VSCode. Instructions for these two paths are here.
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1. Attach the MCP server [to Claude Desktop](quickstart).
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{{< callout >}}
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Claude Desktop has not yet implemented the `notifications/tools/list_changed`. This means that
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Claude doesn't reload our tool definitions until it is restarted. It's easier to develop
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prompts in VSCode where we can create a much more efficient inner loop.
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{{< /callout >}}
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2. [Test prompt definitions](quickstart_vscode) using our VSCode extension. Using VSCode as an
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mcp server can provide an effective inner loop for developing the content.

‎docs/content/tools/docs/_index.md

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title: Documentation
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---
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### Topics
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* [How to author prompts](prompts)
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* [Updating Claude Desktop](claude-desktop)
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510

‎docs/content/tools/docs/claude-desktop.md

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You'll see a prompt asking if you want to run the "hello world" tool locally.
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![consent](consent.png)
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## More prompts
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You can register new definitions in public github repos by adding additional `--register` arguments.
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```
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"--register", "github:docker/labs-ai-tools-for-devs?path=prompts/examples/swagger.md"
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```
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We are moving these registration command to a command line. It doesn't make sense to change the claude
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config each time you add or remote a defintion. However, because Claude Desktop has to be restarted
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every time a definition changes today (because of the missing notification), we will work
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with Anthropic to make this much smoother.

‎docs/content/tools/examples/_index.md

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title: example prompts
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---
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* [simplest definition we can think of](hello-world)
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* [Use curl to fetch your GitHub gists](curl)
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* [call swagger api](swagger)
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* [create an animaged gif using ffmpeg](ffmpeg)
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* [read and write local files](filesystem)
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* [use sqlite from an mcp client](sqlite)
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* [working with local files](filesystem)

‎docs/content/tools/examples/filesystem.md

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---
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title: filesystem
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---
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# Description
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Add `read_file` and `write_file` tool containers.
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# Prompt Code
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```
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---
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model: claude-3-5-sonnet-20241022
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tools:
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- name: read_file
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description: |
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read a file from disk
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Read the complete contents of a file from the file system.
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Handles various text encodings and provides detailed error messages
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if the file cannot be read. Use this tool when you need to examine
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the contents of a single file. Only works within allowed directories.
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parameters:
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type: object
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properties:
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path:
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type: string
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container:
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image: vonwig/bash_alpine
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entrypoint: cat
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command:
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- "{{path|safe}}"
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- name: write_file
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description: |
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Create a new file or completely overwrite an existing file with new content.
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Use with caution as it will overwrite existing files without warning.
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Handles text content with proper encoding. Only works within allowed directories.
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parameters:
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type: object
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properties:
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path:
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type: string
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content:
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type: string
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container:
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image: vonwig/bash_alpine
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command:
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- "-c"
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- "echo {{content|safe}} > {{path|safe}}"
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---
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# prompt user
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read the file deps.edn and then write the string "blah.txt" into the file test.txt
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```

‎docs/content/tools/examples/hello-world.md

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---
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title: hello world
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---
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# Description
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Just echo a greeting by running a container!
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# Prompt Code
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```markdown
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---
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name: hello-docker
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description: run the hello-docker
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model: claude-3-5-sonnet-20241022
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tools:
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- name: hello-docker
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description: print a secret message
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container:
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image: busybox:latest
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command:
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- echo
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- "Hello, World!"
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---
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# prompt
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Use hello world to print a secret message and then explain it to me
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```
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‎docs/content/tools/examples/sqlite.md

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---
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title: sqlite
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---
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# Description
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Use sqlite containers to provide 3 tools:
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* `read-query`
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* `list-tables`
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* `describe-table`
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The sqlite database ( /mcp/test1.db ) is mounted using a Docker volume.
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Use these tools to ask Claude to explore the data using the tools above.
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Here's a fully worked
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[example](https://github.com/docker/labs-ai-tools-for-devs/blob/main/prompts/examples/mcp-sqlite.md?plain=1)
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for building insights from a user defined topic.
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# Prompt Code
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```markdown
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---
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tools:
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- name: read-query
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description: Execute a SELECT query on the SQLite database
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parameters:
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type: object
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properties:
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query:
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type: string
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description: SELECT SQL query to execute
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container: &sqlite-container
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image: &sqlite-image vonwig/sqlite:latest
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command:
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- &db "/mcp/test1.db"
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- "{{query|safe}}"
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volumes: &mounts
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- "mcp-test:/mcp"
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- name: list-tables
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description: List all tables in the SQLite database
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container:
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image: *sqlite-image
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command:
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- *db
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- "SELECT name from sqlite_master WHERE type='table'"
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volumes: *mounts
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- name: describe-table
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description: Get the schema information for a specific table
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parameters:
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type: object
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properties:
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table_name:
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type: string
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description: Name of the table to describe
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container:
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image: *sqlite-image
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command:
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- *db
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- "PRAGMA table_info({{table_name}})"
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volumes: *mounts
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---
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```
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‎docs/content/tools/quickstart.md

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---
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title: Quick Start w/ VSCode
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title: Quick Start w/ Claude Desktop
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weight: 1
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---
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{{% steps %}}
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### Download `.vsix` extension
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### Install
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Download the `.vsix` extension from the [releases page](https://github.com/docker/labs-ai-tools-vscode/releases).
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[Configure Docker Desktop](../docs/claude-desktop) to use the `mcp/run` Docker container.
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### Install extension from `.vsix` file
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### Restart Claude Desktop
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```sh
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code --install-extension <path-to-vsix-file>
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```
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Restarting desktop should be a one-time activity. However, Claude
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Desktop does not support the `tools/list_changed` notification so we
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currently have to restart desktop more less continuously. :)
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or use the VSCode command palette `Extensions: Install from VSIX...`
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### Try a prompt
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### Open a prompt
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With the extension installed, open a prompt in VSCode. Examples can be found in the [examples](https://github.com/docker/labs-ai-tools-for-devs/tree/main/prompts/examples) directory.
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Write a prompt in Claude that will run one of the tools in a registered defintion.
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For example:
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### Configure OpenAI API Key, or use a different model.
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Default model is `gpt-4` provided by OpenAI. Use an the VSCode command palette `Docker AI: Set secret key` to set your API key.
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**Changing the model:**
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Use the following keys in the prompt front-matter to change the model:
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Anthropic:
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```yml
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---
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url: https://api.anthropic.com
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model: claude-3-5-sonnet-20240620
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---
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```
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Ollama:
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```yml
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---
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model: llama3.2
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url: https://docker.host.internal:11434/v1
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---
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```
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### Run the prompt
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Use the VSCode command palette `Docker AI: Run this prompt` to run the prompt.
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> Use hello world to send a greeting and then respond to what comes back.
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{{% /steps %}}

‎docs/content/tools/quickstart_vscode.md

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---
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title: Quick Start w/ VSCode
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weight: 1
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---
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{{% steps %}}
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### Download `.vsix` extension
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Download the `.vsix` extension from the [releases page](https://github.com/docker/labs-ai-tools-vscode/releases).
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### Install extension from `.vsix` file
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```sh
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code --install-extension <path-to-vsix-file>
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```
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or use the VSCode command palette `Extensions: Install from VSIX...`
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### Open a prompt
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With the extension installed, open a prompt in VSCode. Examples can be found in the [examples](https://github.com/docker/labs-ai-tools-for-devs/tree/main/prompts/examples) directory.
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### Configure OpenAI API Key, or use a different model.
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Default model is `gpt-4` provided by OpenAI. Use an the VSCode command palette `Docker AI: Set secret key` to set your API key.
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**Changing the model:**
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Use the following keys in the prompt front-matter to change the model:
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Anthropic:
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```yml
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---
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model: claude-3-5-sonnet-20240620
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---
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```
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Ollama:
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```yml
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---
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model: llama3.2
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url: https://docker.host.internal:11434/v1
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---
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```
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### Run the prompt
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Use the VSCode command palette `Docker AI: Run this prompt` to run the prompt.
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{{% /steps %}}

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