Backends

Deep Agents expose a filesystem surface to the agent via tools like ls, read_file, write_file, edit_file, glob, and grep. These tools operate through a pluggable backend. The read_file tool natively supports image files (.png, .jpg, .jpeg, .gif, .webp) across all backends, returning them as multimodal content blocks. Sandboxes and the LocalShellBackend also provide an execute tool. This page explains how to:

choose a backend,
route different paths to different backends,
implement your own virtual filesystem (e.g., S3 or Postgres),
comply with the backend protocol,

Quickstart

Here are a few prebuilt filesystem backends that you can quickly use with your deep agent:

Built-in backend	Description
Default	`agent = create_deep_agent()` Ephemeral in state. The default filesystem backend for an agent is stored in `langgraph` state. Note that this filesystem only persists for a single thread.
Local filesystem persistence	`agent = create_deep_agent(backend=FilesystemBackend(root_dir="/Users/nh/Desktop/"))` This gives the deep agent access to your local machine’s filesystem. You can specify the root directory that the agent has access to. Note that any provided `root_dir` must be an absolute path.
Durable store (LangGraph store)	`agent = create_deep_agent(backend=StoreBackend())` This gives the agent access to long-term storage that is persisted across threads. This is great for storing longer term memories or instructions that are applicable to the agent over multiple executions.
Sandbox	`agent = create_deep_agent(backend=sandbox)` Execute code in isolated environments. Sandboxes provide filesystem tools plus the `execute` tool for running shell commands. Choose from Modal, Daytona, Deno, or local VFS.
Local shell	`agent = create_deep_agent(backend=LocalShellBackend(root_dir=".", env={"PATH": "/usr/bin:/bin"}))` Filesystem and shell execution directly on the host. No isolation—use only in controlled development environments. See security considerations below.
Composite	Ephemeral by default, `/memories/` persisted. The Composite backend is maximally flexible. You can specify different routes in the filesystem to point towards different backends. See Composite routing below for a ready-to-paste example.

Built-in backends

StateBackend (ephemeral)

# By default we provide a StateBackend
agent = create_deep_agent()

# Under the hood, it looks like
from deepagents.backends import StateBackend

agent = create_deep_agent(
    backend=StateBackend()
)

How it works:

Stores files in LangGraph agent state for the current thread via StateBackend.
Persists across multiple agent turns on the same thread via checkpoints.

Best for:

A scratch pad for the agent to write intermediate results.
Automatic eviction of large tool outputs which the agent can then read back in piece by piece.

Note that this backend is shared between the supervisor agent and subagents, and any files a subagent writes will remain in the LangGraph agent state even after that subagent’s execution is complete. Those files will continue to be available to the supervisor agent and other subagents.

FilesystemBackend (local disk)

FilesystemBackend reads and writes real files under a configurable root directory.

This backend grants agents direct filesystem read/write access. Use with caution and only in appropriate environments.Appropriate use cases:

Local development CLIs (coding assistants, development tools)
CI/CD pipelines (see security considerations below)

Inappropriate use cases:

Web servers or HTTP APIs - use StateBackend, StoreBackend, or a sandbox backend instead

Security risks:

Agents can read any accessible file, including secrets (API keys, credentials, .env files)
Combined with network tools, secrets may be exfiltrated via SSRF attacks
File modifications are permanent and irreversible

Recommended safeguards:

Enable Human-in-the-Loop (HITL) middleware to review sensitive operations.
Exclude secrets from accessible filesystem paths (especially in CI/CD).
Use a sandbox backend for production environments requiring filesystem interaction.
Always use virtual_mode=True with root_dir to enable path-based access restrictions (blocks .., ~, and absolute paths outside root). Note that the default (virtual_mode=False) provides no security even with root_dir set.

from deepagents.backends import FilesystemBackend

agent = create_deep_agent(
    backend=FilesystemBackend(root_dir=".", virtual_mode=True)
)

How it works:

Reads/writes real files under a configurable root_dir.
You can optionally set virtual_mode=True to sandbox and normalize paths under root_dir.
Uses secure path resolution, prevents unsafe symlink traversal when possible, can use ripgrep for fast grep.

Best for:

Local projects on your machine
CI sandboxes
Mounted persistent volumes

LocalShellBackend (local shell)

This backend grants agents direct filesystem read/write access and unrestricted shell execution on your host. Use with extreme caution and only in appropriate environments.Appropriate use cases:

Local development CLIs (coding assistants, development tools)
Personal development environments where you trust the agent’s code
CI/CD pipelines with proper secret management

Inappropriate use cases:

Production environments (such as web servers, APIs, multi-tenant systems)
Processing untrusted user input or executing untrusted code

Security risks:

Agents can execute arbitrary shell commands with your user’s permissions
Agents can read any accessible file, including secrets (API keys, credentials, .env files)
Secrets may be exposed
File modifications and command execution are permanent and irreversible
Commands run directly on your host system
Commands can consume unlimited CPU, memory, disk

Recommended safeguards:

Enable Human-in-the-Loop (HITL) middleware to review and approve operations before execution. This is strongly recommended.
Run in dedicated development environments only. Never use on shared or production systems.
Use a sandbox backend for production environments requiring shell execution.

Note: virtual_mode=True provides no security with shell access enabled, since commands can access any path on the system.

from deepagents.backends import LocalShellBackend

agent = create_deep_agent(
    backend=LocalShellBackend(root_dir=".", env={"PATH": "/usr/bin:/bin"})
)

How it works:

Extends FilesystemBackend with the execute tool for running shell commands on the host.
Commands run directly on your machine using subprocess.run(shell=True) with no sandboxing.
Supports timeout (default 120s), max_output_bytes (default 100,000), env, and inherit_env for environment variables.
Shell commands use root_dir as the working directory but can access any path on the system.

Best for:

Local coding assistants and development tools
Quick iteration during development when you trust the agent

StoreBackend (LangGraph store)

from langgraph.store.memory import InMemoryStore
from deepagents.backends import StoreBackend

agent = create_deep_agent(
    backend=StoreBackend(
        namespace=lambda ctx: (ctx.runtime.context.user_id,),
    ),
    store=InMemoryStore()  # Good for local dev; omit for LangSmith Deployment
)

When deploying to LangSmith Deployment, omit the store parameter. The platform automatically provisions a store for your agent.

The namespace parameter controls data isolation. For multi-user deployments, always set a namespace factory to isolate data per user or tenant.

How it works:

StoreBackend stores files in a LangGraph BaseStore provided by the runtime, enabling cross‑thread durable storage.

Best for:

When you already run with a configured LangGraph store (for example, Redis, Postgres, or cloud implementations behind BaseStore).
When you’re deploying your agent through LangSmith Deployment (a store is automatically provisioned for your agent).

Namespace factories

A namespace factory controls where StoreBackend reads and writes data. It receives a BackendContext and returns a tuple of strings used as the store namespace. Use namespace factories to isolate data between users, tenants, or assistants. Pass the namespace factory to the namespace parameter when constructing a StoreBackend:

NamespaceFactory = Callable[[BackendContext], tuple[str, ...]]

The BackendContext provides:

ctx.runtime.context — User-supplied context passed via LangGraph’s context schema (for example, user_id)
ctx.runtime.server_info — Server-specific metadata when running on LangGraph Server (assistant ID, graph ID, authenticated user)
ctx.runtime.execution_info — Execution identity information (thread ID, run ID, checkpoint ID)
ctx.state — Current agent state

ctx.runtime.server_info and ctx.runtime.execution_info require deepagents>=0.5.0.

Common namespace patterns:

from deepagents.backends import StoreBackend

# Per-user: each user gets their own isolated storage
backend = StoreBackend(
    namespace=lambda ctx: (ctx.runtime.server_info.user.identity,),
)

# Per-assistant: all users of the same assistant share storage
backend = StoreBackend(
    namespace=lambda ctx: (
        ctx.runtime.server_info.assistant_id,
    ),
)

# Per-thread: storage scoped to a single conversation
backend = StoreBackend(
    namespace=lambda ctx: (
        ctx.runtime.execution_info.thread_id,
    ),
)

You can combine multiple components to create more specific scopes — for example, (user_id, thread_id) for per-user per-conversation isolation, or append a suffix like "filesystem" to disambiguate when the same scope uses multiple store namespaces. Namespace components must contain only alphanumeric characters, hyphens, underscores, dots, @, +, colons, and tildes. Wildcards (*, ?) are rejected to prevent glob injection.

The namespace parameter will be required in v0.5.0. Always set it explicitly for new code.

When no namespace factory is provided, the legacy default uses the assistant_id from LangGraph config metadata. This means all users of the same assistant share the same storage. For multi-user going to production, always provide a namespace factory.

CompositeBackend (router)

from deepagents import create_deep_agent
from deepagents.backends import CompositeBackend, StateBackend, StoreBackend
from langgraph.store.memory import InMemoryStore

agent = create_deep_agent(
    backend=CompositeBackend(
        default=StateBackend(),
        routes={
            "/memories/": StoreBackend(),
        }
    ),
    store=InMemoryStore()  # Store passed to create_deep_agent, not backend
)

How it works:

CompositeBackend routes file operations to different backends based on path prefix.
Preserves the original path prefixes in listings and search results.

Best for:

When you want to give your agent both ephemeral and cross-thread storage, a CompositeBackend allows you provide both a StateBackend and StoreBackend
When you have multiple sources of information that you want to provide to your agent as part of a single filesystem.
- e.g. You have long-term memories stored under /memories/ in one Store and you also have a custom backend that has documentation accessible at /docs/.

Specify a backend

Pass a backend instance to create_deep_agent(backend=...). The filesystem middleware uses it for all tooling.
The backend must implement BackendProtocol (for example, StateBackend(), FilesystemBackend(root_dir="."), StoreBackend()).
If omitted, the default is StateBackend().

Route to different backends

Route parts of the namespace to different backends. Commonly used to persist /memories/* and keep everything else ephemeral.

from deepagents import create_deep_agent
from deepagents.backends import CompositeBackend, StateBackend, FilesystemBackend

agent = create_deep_agent(
    backend=CompositeBackend(
        default=StateBackend(),
        routes={
            "/memories/": FilesystemBackend(root_dir="/deepagents/myagent", virtual_mode=True),
        },
    )
)

Behavior:

/workspace/plan.md → StateBackend (ephemeral)
/memories/agent.md → FilesystemBackend under /deepagents/myagent
ls, glob, grep aggregate results and show original path prefixes.

Notes:

Longer prefixes win (for example, route "/memories/projects/" can override "/memories/").
For StoreBackend routing, ensure a store is provided via create_deep_agent(store=...) or provisioned by the platform.

Use a virtual filesystem

Build a custom backend to project a remote or database filesystem (e.g., S3 or Postgres) into the tools namespace. Design guidelines:

Paths are absolute (/x/y.txt). Decide how to map them to your storage keys/rows.
Implement ls and glob efficiently (server-side filtering where available, otherwise local filter).
For external persistence (S3, Postgres, etc.), return files_update=None (Python) or omit filesUpdate (JS) in write/edit results — only in-memory state backends need to return a files update dict.
Use ls and glob as the method names.
Return structured result types with an error field for missing files or invalid patterns (do not raise).

S3-style outline:

from deepagents.backends.protocol import (
    BackendProtocol, WriteResult, EditResult, LsResult, ReadResult, GrepResult, GlobResult,
)

class S3Backend(BackendProtocol):
    def __init__(self, bucket: str, prefix: str = ""):
        self.bucket = bucket
        self.prefix = prefix.rstrip("/")

    def _key(self, path: str) -> str:
        return f"{self.prefix}{path}"

    def ls(self, path: str) -> LsResult:
        # List objects under _key(path); build FileInfo entries (path, size, modified_at)
        ...

    def read(self, file_path: str, offset: int = 0, limit: int = 2000) -> ReadResult:
        # Fetch object; return ReadResult(file_data=...) or ReadResult(error=...)
        ...

    def grep(self, pattern: str, path: str | None = None, glob: str | None = None) -> GrepResult:
        # Optionally filter server‑side; else list and scan content
        ...

    def glob(self, pattern: str, path: str = "/") -> GlobResult:
        # Apply glob relative to path across keys
        ...

    def write(self, file_path: str, content: str) -> WriteResult:
        # Enforce create‑only semantics; return WriteResult(path=file_path, files_update=None)
        ...

    def edit(self, file_path: str, old_string: str, new_string: str, replace_all: bool = False) -> EditResult:
        # Read → replace (respect uniqueness vs replace_all) → write → return occurrences
        ...

Postgres-style outline:

Table files(path text primary key, content text, created_at timestamptz, modified_at timestamptz)
Map tool operations onto SQL:
- ls uses WHERE path LIKE $1 || '%'
- glob filter in SQL or fetch then apply glob in Python
- grep can fetch candidate rows by extension or last modified time, then scan lines

Add policy hooks

Enforce enterprise rules by subclassing or wrapping a backend. Block writes/edits under selected prefixes (subclass):

from deepagents.backends.filesystem import FilesystemBackend
from deepagents.backends.protocol import WriteResult, EditResult

class GuardedBackend(FilesystemBackend):
    def __init__(self, *, deny_prefixes: list[str], **kwargs):
        super().__init__(**kwargs)
        self.deny_prefixes = [p if p.endswith("/") else p + "/" for p in deny_prefixes]

    def write(self, file_path: str, content: str) -> WriteResult:
        if any(file_path.startswith(p) for p in self.deny_prefixes):
            return WriteResult(error=f"Writes are not allowed under {file_path}")
        return super().write(file_path, content)

    def edit(self, file_path: str, old_string: str, new_string: str, replace_all: bool = False) -> EditResult:
        if any(file_path.startswith(p) for p in self.deny_prefixes):
            return EditResult(error=f"Edits are not allowed under {file_path}")
        return super().edit(file_path, old_string, new_string, replace_all)

Generic wrapper (works with any backend):

from deepagents.backends.protocol import (
    BackendProtocol, WriteResult, EditResult, LsResult, ReadResult, GrepResult, GlobResult,
)

class PolicyWrapper(BackendProtocol):
    def __init__(self, inner: BackendProtocol, deny_prefixes: list[str] | None = None):
        self.inner = inner
        self.deny_prefixes = [p if p.endswith("/") else p + "/" for p in (deny_prefixes or [])]

    def _deny(self, path: str) -> bool:
        return any(path.startswith(p) for p in self.deny_prefixes)

    def ls(self, path: str) -> LsResult:
        return self.inner.ls(path)

    def read(self, file_path: str, offset: int = 0, limit: int = 2000) -> ReadResult:
        return self.inner.read(file_path, offset=offset, limit=limit)
    def grep(self, pattern: str, path: str | None = None, glob: str | None = None) -> GrepResult:
        return self.inner.grep(pattern, path, glob)
    def glob(self, pattern: str, path: str = "/") -> GlobResult:
        return self.inner.glob(pattern, path)
    def write(self, file_path: str, content: str) -> WriteResult:
        if self._deny(file_path):
            return WriteResult(error=f"Writes are not allowed under {file_path}")
        return self.inner.write(file_path, content)
    def edit(self, file_path: str, old_string: str, new_string: str, replace_all: bool = False) -> EditResult:
        if self._deny(file_path):
            return EditResult(error=f"Edits are not allowed under {file_path}")
        return self.inner.edit(file_path, old_string, new_string, replace_all)

Migrate from backend factories

The backend factory pattern is deprecated. Pass pre-constructed backend instances directly instead of factory functions.

Previously, backends like StateBackend and StoreBackend required a factory function that received a runtime object, because they needed runtime context (state, store) to operate. Backends now resolve this context internally via LangGraph’s get_config(), get_store(), and get_runtime() helpers, so you can pass instances directly.

What changed

Before (deprecated)	After
`backend=lambda rt: StateBackend(rt)`	`backend=StateBackend()`
`backend=lambda rt: StoreBackend(rt)`	`backend=StoreBackend()`
`backend=lambda rt: CompositeBackend(default=StateBackend(rt), ...)`	`backend=CompositeBackend(default=StateBackend(), ...)`
`backend: (config) => new StateBackend(config)`	`backend: new StateBackend()`
`backend: (config) => new StoreBackend(config)`	`backend: new StoreBackend()`

Deprecated APIs

Deprecated	Replacement
Passing a callable to `backend=` in `create_deep_agent`	Pass a backend instance directly
`runtime` constructor argument on `StateBackend(runtime)`	`StateBackend()` (no arguments needed)
`runtime` constructor argument on `StoreBackend(runtime)`	`StoreBackend()` or `StoreBackend(namespace=..., store=...)`
`files_update` field on `WriteResult` and `EditResult`	State writes are now handled internally by the backend
`Command` wrapping in middleware write/edit tools	Tools return plain strings; no `Command(update=...)` needed

The factory pattern still works at runtime and emits a deprecation warning. Update your code to use direct instances before the next major version.

Migration example

# Before (deprecated)
from deepagents import create_deep_agent
from deepagents.backends import CompositeBackend, StateBackend, StoreBackend

agent = create_deep_agent(
    backend=lambda rt: CompositeBackend(
        default=StateBackend(rt),
        routes={"/memories/": StoreBackend(rt, namespace=lambda ctx: (ctx.runtime.context.user_id,))},
    ),
)

# After
agent = create_deep_agent(
    backend=CompositeBackend(
        default=StateBackend(),
        routes={"/memories/": StoreBackend(namespace=lambda ctx: (ctx.runtime.context.user_id,))},
    ),
)

Protocol reference

Backends must implement BackendProtocol. Required methods:

ls(path: str) -> LsResult
- Return entries with at least path. Include is_dir, size, modified_at when available. Sort by path for deterministic output.
read(file_path: str, offset: int = 0, limit: int = 2000) -> ReadResult
- Return file data on success. On missing file, return ReadResult(error="Error: File '/x' not found").
grep(pattern: str, path: Optional[str] = None, glob: Optional[str] = None) -> GrepResult
- Return structured matches. On error, return GrepResult(error="...") (do not raise).
glob(pattern: str, path: str = "/") -> GlobResult
- Return matched files as FileInfo entries (empty list if none).
write(file_path: str, content: str) -> WriteResult
- Create-only. On conflict, return WriteResult(error=...). On success, set path and for state backends set files_update={...}; external backends should use files_update=None.
edit(file_path: str, old_string: str, new_string: str, replace_all: bool = False) -> EditResult
- Enforce uniqueness of old_string unless replace_all=True. If not found, return error. Include occurrences on success.

Supporting types:

LsResult(error, entries) — entries is a list[FileInfo] on success, None on failure.
ReadResult(error, file_data) — file_data is a FileData dict on success, None on failure.
GrepResult(error, matches) — matches is a list[GrepMatch] on success, None on failure.
GlobResult(error, matches) — matches is a list[FileInfo] on success, None on failure.
WriteResult(error, path, files_update)
EditResult(error, path, files_update, occurrences)
FileInfo with fields: path (required), optionally is_dir, size, modified_at.
GrepMatch with fields: path, line, text.
FileData with fields: content (str), encoding ("utf-8" or "base64"), created_at, modified_at. :::

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Get started

Deployment

Core capabilities

Frontend

Protocols

Command line interface

Quickstart

Built-in backends

StateBackend (ephemeral)

FilesystemBackend (local disk)

LocalShellBackend (local shell)

StoreBackend (LangGraph store)

Namespace factories

CompositeBackend (router)

Specify a backend

Route to different backends

Use a virtual filesystem

Add policy hooks

Migrate from backend factories

What changed

Deprecated APIs

Migration example

Protocol reference

Get started

Deployment

Core capabilities

Frontend

Protocols

Command line interface

​Quickstart

​Built-in backends

​StateBackend (ephemeral)

​FilesystemBackend (local disk)

​LocalShellBackend (local shell)

​StoreBackend (LangGraph store)

​Namespace factories

​CompositeBackend (router)

​Specify a backend

​Route to different backends

​Use a virtual filesystem

​Add policy hooks

​Migrate from backend factories

​What changed

​Deprecated APIs

​Migration example

​Protocol reference

Quickstart

Built-in backends

StateBackend (ephemeral)

FilesystemBackend (local disk)

LocalShellBackend (local shell)

StoreBackend (LangGraph store)

Namespace factories

CompositeBackend (router)

Specify a backend

Route to different backends

Use a virtual filesystem

Add policy hooks

Migrate from backend factories

What changed

Deprecated APIs

Migration example

Protocol reference