seekvfs 0.1.0

A protocol-level unified VFS for AI agents with L0/L1/L2 tiered storage.

seekvfs

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seekvfs is a virtual file system interface for AI agents. It lets you assign different URI prefixes to different storage backends and expose them through a single file interface. The core package only handles URI normalization, prefix-based routing, cross-backend search merging, and agent tool export. Storage layout, indexing, summaries, embeddings, and other implementation details are left to the backend.

Install

Requires Python 3.11+.

pip install seekvfs

For the full built-in integrations:

pip install "seekvfs[full]"

Quickstart

from seekvfs import VFS
from seekvfs_recipes.minimal import FileBackend

vfs = VFS(
    routes={
        "seekvfs://notes/": {
            "backend": FileBackend("/data/agent_notes"),
        },
    }
)

vfs.write("seekvfs://notes/hello.md", "hello world")

fd = vfs.read("seekvfs://notes/hello.md")
print(fd.content.decode())

for item in vfs.ls("seekvfs://notes/"):
    print(item.path, item.size)

The route key can also be written as a bare prefix like notes/; SeekVFS will normalize it to seekvfs://notes/.

More examples: docs/quickstart.md

Tools

vfs.tools returns a neutral set of 8 agent tool specs: search, read, read_full, write, edit, ls, grep, and delete. You can export them to different agent runtimes, including OpenAI, Anthropic, LangGraph, and MCP.

Recipes

Recipe	Use when	Storage shape	Docs
seekvfs_recipes.minimal	You want the smallest persistent backend	One file per path on local disk	docs/recipes/minimal.md
seekvfs_recipes.maximal	You want tiered reads and semantic search	L2 on filesystem, L0/L1 + embeddings in OceanBase	docs/recipes/maximal.md

You can mix recipes in one VFS by mounting them on different URI prefixes.

Documentation

• Quickstart: docs/quickstart.md
• Minimal recipe: docs/recipes/minimal.md
• Maximal recipe: docs/recipes/maximal.md

License

Apache 2.0.