# Filesystem Provider

> Automatic component discovery from Python files

`FileSystemProvider` scans a directory for Python files and automatically registers functions decorated with `@tool`, `@resource`, or `@prompt`. This enables a file-based organization pattern similar to Next.js routing, where your project structure becomes your component registry.

## Why Filesystem Discovery

Traditional FastMCP servers require coordination between files. Either your tool files import the server to call `@server.tool()`, or your server file imports all the tool modules. Both approaches create coupling that some developers prefer to avoid.

`FileSystemProvider` eliminates this coordination. Each file is self-contained—it uses standalone decorators (`@tool`, `@resource`, `@prompt`) that don't require access to a server instance. The provider discovers these files at startup, so you can add new tools without modifying your server file.

This is a convention some teams prefer, not necessarily better for all projects. The tradeoffs:

* **No coordination**: Files don't import the server; server doesn't import files
* **Predictable naming**: Function names become component names (unless overridden)
* **Development mode**: Optionally re-scan files on every request for rapid iteration

## Quick Start

Create a provider pointing to your components directory, then pass it to your server. Use `Path(__file__).parent` to make the path relative to your server file.

```python
from pathlib import Path

from fastmcp import FastMCP
from fastmcp.server.providers import FileSystemProvider

mcp = FastMCP("MyServer", providers=[FileSystemProvider(Path(__file__).parent / "mcp")])
```

In your `mcp/` directory, create Python files with decorated functions.

```python
# mcp/tools/greet.py
from fastmcp.tools import tool

@tool
def greet(name: str) -> str:
    """Greet someone by name."""
    return f"Hello, {name}!"
```

When the server starts, `FileSystemProvider` scans the directory, imports all Python files, and registers any decorated functions it finds.

## Decorators

FastMCP provides standalone decorators that mark functions for discovery: `@tool` from `fastmcp.tools`, `@resource` from `fastmcp.resources`, and `@prompt` from `fastmcp.prompts`. These support the full syntax of server-bound decorators—all the same parameters work identically.

### @tool

Mark a function as a tool. The function name becomes the tool name by default.

```python
from fastmcp.tools import tool

@tool
def calculate_sum(a: float, b: float) -> float:
    """Add two numbers together."""
    return a + b
```

Customize the tool with optional parameters.

```python
from fastmcp.tools import tool

@tool(
    name="add-numbers",
    description="Add two numbers together.",
    tags={"math", "arithmetic"},
)
def add(a: float, b: float) -> float:
    return a + b
```

The decorator supports all standard tool options: `name`, `title`, `description`, `icons`, `tags`, `output_schema`, `annotations`, and `meta`.

### @resource

Mark a function as a resource. Unlike `@tool`, the `@resource` decorator requires a URI argument.

```python
from fastmcp.resources import resource

@resource("config://app")
def get_app_config() -> str:
    """Get application configuration."""
    return '{"version": "1.0"}'
```

URIs with template parameters create resource templates. The provider automatically detects whether to register a static resource or a template based on whether the URI contains `{parameters}` or the function has arguments.

```python
from fastmcp.resources import resource

@resource("users://{user_id}/profile")
def get_user_profile(user_id: str) -> str:
    """Get a user's profile by ID."""
    return f'{{"id": "{user_id}", "name": "User"}}'
```

The decorator supports: `uri` (required), `name`, `title`, `description`, `icons`, `mime_type`, `tags`, `annotations`, and `meta`.

### @prompt

Mark a function as a prompt template.

````python
from fastmcp.prompts import prompt

@prompt
def code_review(code: str, language: str = "python") -> str:
    """Generate a code review prompt."""
    return f"Please review this {language} code:\n\n```{language}\n{code}\n```"
````

```python
from fastmcp.prompts import prompt

@prompt(name="explain-concept", tags={"education"})
def explain(topic: str) -> str:
    """Generate an explanation prompt."""
    return f"Explain {topic} using clear examples and analogies."
```

The decorator supports: `name`, `title`, `description`, `icons`, `tags`, and `meta`.

## Directory Structure

The directory structure is purely organizational. The provider recursively scans all `.py` files regardless of which subdirectory they're in. Subdirectories like `tools/`, `resources/`, and `prompts/` are optional conventions that help you organize code.

```
mcp/
├── tools/
│   ├── greeting.py      # @tool functions
│   └── calculator.py    # @tool functions
├── resources/
│   └── config.py        # @resource functions
└── prompts/
    └── assistant.py     # @prompt functions
```

You can also put all components in a single file or organize by feature rather than type.

```
mcp/
├── user_management.py   # @tool, @resource, @prompt for users
├── billing.py           # @tool, @resource for billing
└── analytics.py         # @tool for analytics
```

## Discovery Rules

The provider follows these rules when scanning:

| Rule                | Behavior                                                              |
| ------------------- | --------------------------------------------------------------------- |
| File extensions     | Only `.py` files are scanned                                          |
| `__init__.py`       | Skipped (used for package structure, not components)                  |
| `__pycache__`       | Skipped                                                               |
| Private functions   | Functions starting with `_` are ignored, even if decorated            |
| No decorators       | Files without `@tool`, `@resource`, or `@prompt` are silently skipped |
| Multiple components | A single file can contain any number of decorated functions           |

### Package Imports

If your directory contains an `__init__.py` file, the provider imports files as proper Python package members. This means relative imports work correctly within your components directory.

```python
# mcp/__init__.py exists

# mcp/tools/greeting.py
from ..helpers import format_name  # Relative imports work

@tool
def greet(name: str) -> str:
    return f"Hello, {format_name(name)}!"
```

Without `__init__.py`, files are imported directly using `importlib.util.spec_from_file_location`.

## Reload Mode

During development, you may want changes to component files to take effect without restarting the server. Enable reload mode to re-scan the directory on every request.

```python
from pathlib import Path

from fastmcp.server.providers import FileSystemProvider

provider = FileSystemProvider(Path(__file__).parent / "mcp", reload=True)
```

With `reload=True`, the provider:

1. Re-discovers all Python files on each request
2. Re-imports modules that have changed
3. Updates the component registry with any new, modified, or removed components

> **Warning:** Reload mode adds overhead to every request. Use it only during development, not in production.


## Error Handling

When a file fails to import (syntax error, missing dependency, etc.), the provider logs a warning and continues scanning other files. Failed imports don't prevent the server from starting.

```
WARNING - Failed to import /path/to/broken.py: No module named 'missing_dep'
```

The provider tracks which files have failed and only re-logs warnings when the file's modification time changes. This prevents log spam when a broken file is repeatedly scanned in reload mode.

## Example Project

A complete example is available in the repository at `examples/filesystem-provider/`. The structure demonstrates the recommended organization.

```
examples/filesystem-provider/
├── server.py                    # Server entry point
└── mcp/
    ├── tools/
    │   ├── greeting.py          # greet, farewell tools
    │   └── calculator.py        # add, multiply tools
    ├── resources/
    │   └── config.py            # Static and templated resources
    └── prompts/
        └── assistant.py         # code_review, explain prompts
```

The server entry point is minimal.

```python
from pathlib import Path

from fastmcp import FastMCP
from fastmcp.server.providers import FileSystemProvider

provider = FileSystemProvider(
    root=Path(__file__).parent / "mcp",
    reload=True,
)

mcp = FastMCP("FilesystemDemo", providers=[provider])
```

Run with `fastmcp run examples/filesystem-provider/server.py` or inspect with `fastmcp inspect examples/filesystem-provider/server.py`.

> ## Documentation Index
> Fetch the complete documentation index at: https://gofastmcp.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Filesystem Provider

> Automatic component discovery from Python files

`FileSystemProvider` scans a directory for Python files and automatically registers functions decorated with `@tool`, `@resource`, or `@prompt`. This enables a file-based organization pattern similar to Next.js routing, where your project structure becomes your component registry.

## Why Filesystem Discovery

Traditional FastMCP servers require coordination between files. Either your tool files import the server to call `@server.tool()`, or your server file imports all the tool modules. Both approaches create coupling that some developers prefer to avoid.

`FileSystemProvider` eliminates this coordination. Each file is self-contained—it uses standalone decorators (`@tool`, `@resource`, `@prompt`) that don't require access to a server instance. The provider discovers these files at startup, so you can add new tools without modifying your server file.

This is a convention some teams prefer, not necessarily better for all projects. The tradeoffs:

* **No coordination**: Files don't import the server; server doesn't import files
* **Predictable naming**: Function names become component names (unless overridden)
* **Development mode**: Optionally re-scan files on every request for rapid iteration

## Quick Start

Create a provider pointing to your components directory, then pass it to your server. Use `Path(__file__).parent` to make the path relative to your server file.

```python
from pathlib import Path

from fastmcp import FastMCP
from fastmcp.server.providers import FileSystemProvider

mcp = FastMCP("MyServer", providers=[FileSystemProvider(Path(__file__).parent / "mcp")])
```

In your `mcp/` directory, create Python files with decorated functions.

```python
# mcp/tools/greet.py
from fastmcp.tools import tool

@tool
def greet(name: str) -> str:
    """Greet someone by name."""
    return f"Hello, {name}!"
```

When the server starts, `FileSystemProvider` scans the directory, imports all Python files, and registers any decorated functions it finds.

## Decorators

FastMCP provides standalone decorators that mark functions for discovery: `@tool` from `fastmcp.tools`, `@resource` from `fastmcp.resources`, and `@prompt` from `fastmcp.prompts`. These support the full syntax of server-bound decorators—all the same parameters work identically.

### @tool

Mark a function as a tool. The function name becomes the tool name by default.

```python
from fastmcp.tools import tool

@tool
def calculate_sum(a: float, b: float) -> float:
    """Add two numbers together."""
    return a + b
```

Customize the tool with optional parameters.

```python
from fastmcp.tools import tool

@tool(
    name="add-numbers",
    description="Add two numbers together.",
    tags={"math", "arithmetic"},
)
def add(a: float, b: float) -> float:
    return a + b
```

The decorator supports all standard tool options: `name`, `title`, `description`, `icons`, `tags`, `output_schema`, `annotations`, and `meta`.

### @resource

Mark a function as a resource. Unlike `@tool`, the `@resource` decorator requires a URI argument.

```python
from fastmcp.resources import resource

@resource("config://app")
def get_app_config() -> str:
    """Get application configuration."""
    return '{"version": "1.0"}'
```

URIs with template parameters create resource templates. The provider automatically detects whether to register a static resource or a template based on whether the URI contains `{parameters}` or the function has arguments.

```python
from fastmcp.resources import resource

@resource("users://{user_id}/profile")
def get_user_profile(user_id: str) -> str:
    """Get a user's profile by ID."""
    return f'{{"id": "{user_id}", "name": "User"}}'
```

The decorator supports: `uri` (required), `name`, `title`, `description`, `icons`, `mime_type`, `tags`, `annotations`, and `meta`.

### @prompt

Mark a function as a prompt template.

````python
from fastmcp.prompts import prompt

@prompt
def code_review(code: str, language: str = "python") -> str:
    """Generate a code review prompt."""
    return f"Please review this {language} code:\n\n```{language}\n{code}\n```"
````

```python
from fastmcp.prompts import prompt

@prompt(name="explain-concept", tags={"education"})
def explain(topic: str) -> str:
    """Generate an explanation prompt."""
    return f"Explain {topic} using clear examples and analogies."
```

The decorator supports: `name`, `title`, `description`, `icons`, `tags`, and `meta`.

## Directory Structure

The directory structure is purely organizational. The provider recursively scans all `.py` files regardless of which subdirectory they're in. Subdirectories like `tools/`, `resources/`, and `prompts/` are optional conventions that help you organize code.

```
mcp/
├── tools/
│   ├── greeting.py      # @tool functions
│   └── calculator.py    # @tool functions
├── resources/
│   └── config.py        # @resource functions
└── prompts/
    └── assistant.py     # @prompt functions
```

You can also put all components in a single file or organize by feature rather than type.

```
mcp/
├── user_management.py   # @tool, @resource, @prompt for users
├── billing.py           # @tool, @resource for billing
└── analytics.py         # @tool for analytics
```

## Discovery Rules

The provider follows these rules when scanning:

| Rule                | Behavior                                                              |
| ------------------- | --------------------------------------------------------------------- |
| File extensions     | Only `.py` files are scanned                                          |
| `__init__.py`       | Skipped (used for package structure, not components)                  |
| `__pycache__`       | Skipped                                                               |
| Private functions   | Functions starting with `_` are ignored, even if decorated            |
| No decorators       | Files without `@tool`, `@resource`, or `@prompt` are silently skipped |
| Multiple components | A single file can contain any number of decorated functions           |

### Package Imports

If your directory contains an `__init__.py` file, the provider imports files as proper Python package members. This means relative imports work correctly within your components directory.

```python
# mcp/__init__.py exists

# mcp/tools/greeting.py
from ..helpers import format_name  # Relative imports work

@tool
def greet(name: str) -> str:
    return f"Hello, {format_name(name)}!"
```

Without `__init__.py`, files are imported directly using `importlib.util.spec_from_file_location`.

## Reload Mode

During development, you may want changes to component files to take effect without restarting the server. Enable reload mode to re-scan the directory on every request.

```python
from pathlib import Path

from fastmcp.server.providers import FileSystemProvider

provider = FileSystemProvider(Path(__file__).parent / "mcp", reload=True)
```

With `reload=True`, the provider:

1. Re-discovers all Python files on each request
2. Re-imports modules that have changed
3. Updates the component registry with any new, modified, or removed components

> **Warning:** Reload mode adds overhead to every request. Use it only during development, not in production.


## Error Handling

When a file fails to import (syntax error, missing dependency, etc.), the provider logs a warning and continues scanning other files. Failed imports don't prevent the server from starting.

```
WARNING - Failed to import /path/to/broken.py: No module named 'missing_dep'
```

The provider tracks which files have failed and only re-logs warnings when the file's modification time changes. This prevents log spam when a broken file is repeatedly scanned in reload mode.

## Example Project

A complete example is available in the repository at `examples/filesystem-provider/`. The structure demonstrates the recommended organization.

```
examples/filesystem-provider/
├── server.py                    # Server entry point
└── mcp/
    ├── tools/
    │   ├── greeting.py          # greet, farewell tools
    │   └── calculator.py        # add, multiply tools
    ├── resources/
    │   └── config.py            # Static and templated resources
    └── prompts/
        └── assistant.py         # code_review, explain prompts
```

The server entry point is minimal.

```python
from pathlib import Path

from fastmcp import FastMCP
from fastmcp.server.providers import FileSystemProvider

provider = FileSystemProvider(
    root=Path(__file__).parent / "mcp",
    reload=True,
)

mcp = FastMCP("FilesystemDemo", providers=[provider])
```

Run with `fastmcp run examples/filesystem-provider/server.py` or inspect with `fastmcp inspect examples/filesystem-provider/server.py`.

> ## Documentation Index
> Fetch the complete documentation index at: https://gofastmcp.com/llms.txt
> Use this file to discover all available pages before exploring further.