Agent skill

ftpc-storage-write

Full read-write access to remote storage backends (local, FTP, SFTP, S3, Azure). Upload files, delete files, create directories, in addition to listing and downloading. Use when you need to modify files on cloud storage, FTP servers, or remote filesystems.

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Forks 31

Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/development/ftpc-storage-write-edoannunziata-ftpc

SKILL.md

FTPC Storage (Full Access)

Use the ftpc library to read and write files across storage backends.

This skill can modify remote storage. Confirm destructive operations with the user.

Supported Backends

Protocol URL Format Example
Local file:///path or /path /home/user/data
FTP ftp://[user:pass@]host[:port]/path ftp://ftp.example.com/pub
FTPS ftps://[user:pass@]host[:port]/path ftps://secure.example.com
SFTP sftp://[user:pass@]host[:port]/path sftp://user:pass@host/data
S3 s3://bucket/path s3://my-bucket/folder
Azure Data Lake azure://account.dfs.core.windows.net/fs/path azure://myacct.dfs.core.windows.net/data
Azure Blob blob://account.blob.core.windows.net/container/path blob://myacct.blob.core.windows.net/files

Quick Start

python
from ftpc import connect_sync

with connect_sync("s3://my-bucket") as store:
    # List files
    files = store.list("/")

    # Download
    store.download("/data.csv", "local.csv")

    # Upload
    store.upload("report.pdf", "/reports/report.pdf")

    # Create directory
    store.mkdir("/new-folder")

    # Delete file
    store.delete("/old-file.txt")

All Operations

List Directory

python
from ftpc import connect_sync

with connect_sync("ftp://ftp.example.com") as store:
    files = store.list("/documents")
    for f in files:
        print(f"{f.name}  {'DIR' if f.is_directory else f.size}")

Download File

python
with connect_sync("sftp://user:pass@host") as store:
    store.download("/remote/file.csv", "local_file.csv")

    # With progress callback
    def progress(bytes_done: int) -> bool:
        print(f"Downloaded {bytes_done} bytes")
        return True  # False cancels transfer

    store.download("/large.zip", "out.zip", progress)

Upload File

python
with connect_sync("s3://my-bucket") as store:
    store.upload("local_report.pdf", "/reports/2024/report.pdf")

    # With progress
    def progress(bytes_done: int) -> bool:
        print(f"Uploaded {bytes_done} bytes")
        return True

    store.upload("large_backup.tar.gz", "/backups/backup.tar.gz", progress)

Create Directory

python
with connect_sync("ftp://ftp.example.com") as store:
    success = store.mkdir("/new-directory")
    if success:
        print("Directory created")

Delete File

python
with connect_sync("s3://my-bucket") as store:
    success = store.delete("/obsolete-file.txt")
    if success:
        print("File deleted")

Async Usage

python
import asyncio
from ftpc import Storage

async def main():
    async with Storage.connect("s3://bucket") as store:
        await store.upload("local.txt", "/remote.txt")
        await store.mkdir("/new-dir")
        await store.delete("/old.txt")

asyncio.run(main())

Named Constructors

python
from ftpc import Storage

# S3 with credentials
with Storage.s3(
    bucket="my-bucket",
    region="us-east-1",
    access_key_id="AKIAIOSFODNN7EXAMPLE",
    secret_access_key="wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY"
).sync() as store:
    store.upload("data.csv", "/uploads/data.csv")

# FTP with TLS
with Storage.ftp(
    host="ftp.example.com",
    username="user",
    password="pass",
    tls=True
).sync() as store:
    store.upload("report.pdf", "/reports/report.pdf")

# SFTP with key auth
with Storage.sftp(
    host="server.example.com",
    username="deploy",
    key_filename="/home/user/.ssh/id_rsa"
).sync() as store:
    store.upload("deploy.tar.gz", "/var/releases/deploy.tar.gz")

# Azure Data Lake
with Storage.azure(
    account_url="https://myaccount.dfs.core.windows.net",
    filesystem="data",
    account_key="your-account-key"
).sync() as store:
    store.upload("dataset.parquet", "/datasets/dataset.parquet")

Using Named Remotes from Config

With ~/.ftpcconf.toml:

toml
[prod-s3]
type = "s3"
bucket = "production-data"
region = "us-east-1"
python
from ftpc.config import Config
from ftpc.clients.s3client import S3Client

config = Config.from_file()
remote = config.remotes["prod-s3"]

with S3Client(bucket_name=remote.bucket, region_name=remote.region) as client:
    client.put("local.csv", "/uploads/data.csv")

FileDescriptor Structure

All list() calls return List[FileDescriptor]:

python
@dataclass
class FileDescriptor:
    path: PurePath              # Full path
    filetype: FileType          # FILE or DIRECTORY
    size: Optional[int]         # Bytes (None for dirs)
    modified_time: Optional[datetime]

    @property
    def name(self) -> str       # Filename only

    @property
    def is_file(self) -> bool

    @property
    def is_directory(self) -> bool

Dependencies

bash
pip install ftpc            # Core (local + FTP)
pip install ftpc[sftp]      # + SFTP
pip install ftpc[s3]        # + S3
pip install ftpc[azure]     # + Azure
pip install ftpc[all]       # All backends

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