fastmcp/docs/development/v3-notes/v3-features.mdx
claude[bot] 96b67aed5d docs: add fastmcp install stdio to beta2 section
Co-authored-by: Jeremiah Lowin <jlowin@users.noreply.github.com>
2026-01-30 03:48:47 +00:00

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---
title: v3.0 Feature Tracking
---
This document tracks major features in FastMCP v3.0 for release notes preparation.
## 3.0.0beta2
### CLI: `fastmcp install stdio`
The new `fastmcp install stdio` command ([#3032](https://github.com/jlowin/fastmcp/pull/3032)) generates the full `uv run` command needed to run a FastMCP server over stdio, making it easy to paste into Claude Desktop or other MCP client configurations.
```bash
$ fastmcp install stdio server.py
uv run --with fastmcp fastmcp run /absolute/path/to/server.py
$ fastmcp install stdio fastmcp.json
uv run --with fastmcp --with pillow --with 'qrcode[pil]>=8.0' fastmcp run /absolute/path/to/qr_server.py
```
When given a `fastmcp.json` config file, dependencies are automatically included. The `--copy` flag sends the command directly to the clipboard.
## 3.0.0beta1
#### Provider-Based Architecture
v3.0 introduces a provider-based component system that replaces v2's static-only registration ([#2622](https://github.com/jlowin/fastmcp/pull/2622)). Providers dynamically source tools, resources, templates, and prompts at runtime.
**Core abstraction** (`src/fastmcp/server/providers/base.py`):
```python
class Provider:
async def list_tools(self) -> Sequence[Tool]: ...
async def get_tool(self, name: str) -> Tool | None: ...
async def list_resources(self) -> Sequence[Resource]: ...
async def get_resource(self, uri: str) -> Resource | None: ...
async def list_resource_templates(self) -> Sequence[ResourceTemplate]: ...
async def get_resource_template(self, uri: str) -> ResourceTemplate | None: ...
async def list_prompts(self) -> Sequence[Prompt]: ...
async def get_prompt(self, name: str) -> Prompt | None: ...
```
Providers support:
- **Lifecycle management**: `async def lifespan()` for setup/teardown
- **Visibility control**: `enable()` / `disable()` with name, version, tags, components, and allowlist mode
- **Transform stacking**: `provider.add_transform(Namespace(...))`, `provider.add_transform(ToolTransform(...))`
#### LocalProvider
`LocalProvider` (`src/fastmcp/server/providers/local_provider.py`) manages components registered via decorators. Can be used standalone and attached to multiple servers:
```python
from fastmcp.server.providers import LocalProvider
provider = LocalProvider()
@provider.tool
def greet(name: str) -> str:
return f"Hello, {name}!"
# Attach to multiple servers
server1 = FastMCP("Server1", providers=[provider])
server2 = FastMCP("Server2", providers=[provider])
```
#### ProxyProvider
`ProxyProvider` (`src/fastmcp/server/providers/proxy.py`) proxies components from remote MCP servers via a client factory. Used by `create_proxy()` and `FastMCP.mount()` for remote server integration.
```python
from fastmcp.server import create_proxy
# Create proxy to remote server
server = create_proxy("http://remote-server/mcp")
```
#### OpenAPIProvider
`OpenAPIProvider` (`src/fastmcp/server/providers/openapi/provider.py`) creates MCP components from OpenAPI specifications. Routes map HTTP operations to tools, resources, or templates based on configurable rules.
```python
from fastmcp.server.providers.openapi import OpenAPIProvider
import httpx
client = httpx.AsyncClient(base_url="https://api.example.com")
provider = OpenAPIProvider(openapi_spec=spec, client=client)
mcp = FastMCP("API Server", providers=[provider])
```
Features:
- Automatic route-to-component mapping (GET → resource, POST/PUT/DELETE → tool)
- Custom route mappings via `route_maps` or `route_map_fn`
- Component customization via `mcp_component_fn`
- Name collision detection and handling
#### FastMCPProvider
`FastMCPProvider` (`src/fastmcp/server/providers/fastmcp_provider.py`) wraps a FastMCP server to enable mounting one server onto another. Components delegate execution through the wrapped server's middleware chain.
```python
from fastmcp import FastMCP
from fastmcp.server.providers import FastMCPProvider
from fastmcp.server.transforms import Namespace
main = FastMCP("Main")
sub = FastMCP("Sub")
@sub.tool
def greet(name: str) -> str:
return f"Hello, {name}!"
# Mount with namespace
provider = FastMCPProvider(sub)
provider.add_transform(Namespace("sub"))
main.add_provider(provider)
# Tool accessible as "sub_greet"
```
#### Transforms
Transforms modify components (tools, resources, prompts) as they flow from providers to clients ([#2836](https://github.com/jlowin/fastmcp/pull/2836)). They use a middleware pattern where each transform receives a `call_next` callable to continue the chain.
**Built-in transforms** (`src/fastmcp/server/transforms/`):
- `Namespace` - adds prefixes to names (`tool` → `api_tool`) and path segments to URIs (`data://x` → `data://api/x`)
- `ToolTransform` - modifies tool schemas (rename, description, tags, argument transforms)
- `Visibility` - sets visibility state on components by key or tag (backs `enable()`/`disable()` API)
- `VersionFilter` - filters components by version range (`version_gte`, `version_lt`)
- `ResourcesAsTools` - exposes resources as tools for tool-only clients
- `PromptsAsTools` - exposes prompts as tools for tool-only clients
```python
from fastmcp.server.transforms import Namespace, ToolTransform
from fastmcp.tools.tool_transform import ToolTransformConfig
provider = SomeProvider()
provider.add_transform(Namespace("api"))
provider.add_transform(ToolTransform({
"api_verbose_tool_name": ToolTransformConfig(name="short")
}))
# Stacking composes transformations
# "foo" → "api_foo" (namespace) → "short" (rename)
```
**Custom transforms** subclass `Transform` and override needed methods:
```python
from collections.abc import Sequence
from fastmcp.server.transforms import Transform, ListToolsNext, GetToolNext
from fastmcp.tools import Tool
class TagFilter(Transform):
def __init__(self, required_tags: set[str]):
self.required_tags = required_tags
async def list_tools(self, call_next: ListToolsNext) -> Sequence[Tool]:
tools = await call_next() # Get tools from downstream
return [t for t in tools if t.tags & self.required_tags]
async def get_tool(self, name: str, call_next: GetToolNext) -> Tool | None:
tool = await call_next(name)
return tool if tool and tool.tags & self.required_tags else None
```
Transforms apply at two levels:
- **Provider-level**: `provider.add_transform()` - affects only that provider's components
- **Server-level**: `server.add_transform()` - affects all components from all providers
Documentation: `docs/servers/transforms/transforms.mdx`, `docs/servers/visibility.mdx`
#### ResourcesAsTools and PromptsAsTools
These transforms expose resources and prompts as tools for clients that only support the tools protocol. Each transform generates two tools that provide listing and access functionality.
**ResourcesAsTools** generates `list_resources` and `read_resource` tools:
```python
from fastmcp import FastMCP
from fastmcp.server.transforms import ResourcesAsTools
mcp = FastMCP("Server")
@mcp.resource("data://config")
def get_config() -> dict:
return {"setting": "value"}
mcp.add_transform(ResourcesAsTools(mcp))
# Now has list_resources and read_resource tools
```
The `list_resources` tool returns JSON with resource metadata. The `read_resource` tool accepts a URI and returns the resource content, preserving both text and binary data through base64 encoding.
**PromptsAsTools** generates `list_prompts` and `get_prompt` tools:
```python
from fastmcp import FastMCP
from fastmcp.server.transforms import PromptsAsTools
mcp = FastMCP("Server")
@mcp.prompt
def analyze_code(code: str, language: str = "python") -> str:
return f"Analyze this {language} code:\n{code}"
mcp.add_transform(PromptsAsTools(mcp))
# Now has list_prompts and get_prompt tools
```
The `list_prompts` tool returns JSON with prompt metadata including argument information. The `get_prompt` tool accepts a prompt name and optional arguments dict, returning the rendered prompt as a messages array. Non-text content (like embedded resources) is preserved as structured JSON.
Both transforms:
- Capture a provider reference at construction for deferred querying
- Route through `FastMCP.read_resource()` / `FastMCP.render_prompt()` when the provider is FastMCP, ensuring middleware chains execute
- Fall back to direct provider methods for plain providers
- Return JSON for easy parsing by tool-only clients
Documentation: `docs/servers/transforms/resources-as-tools.mdx`, `docs/servers/transforms/prompts-as-tools.mdx`
---
### Session-Scoped State
v3.0 changes context state from request-scoped to session-scoped. State now persists across multiple tool calls within the same MCP session.
```python
@mcp.tool
async def increment_counter(ctx: Context) -> int:
count = await ctx.get_state("counter") or 0
await ctx.set_state("counter", count + 1)
return count + 1
```
State is automatically keyed by session ID, ensuring isolation between different clients. The implementation uses [pykeyvalue](https://github.com/strawgate/py-key-value) for pluggable storage backends:
```python
from key_value.aio.stores.redis import RedisStore
# Use Redis for distributed deployments
mcp = FastMCP("server", session_state_store=RedisStore(...))
```
**Key details:**
- Methods are now async: `await ctx.get_state()`, `await ctx.set_state()`, `await ctx.delete_state()`
- State expires after 1 day (TTL) to prevent unbounded memory growth
- Works during `on_initialize` middleware when using the same session object
- For distributed HTTP, session identity comes from the `mcp-session-id` header
Documentation: `docs/servers/context.mdx`
---
### Visibility System
Components can be enabled/disabled using the visibility system. Each `enable()` or `disable()` call adds a stateless Visibility transform that marks components via internal metadata. Later transforms override earlier ones.
```python
mcp = FastMCP("Server")
# Disable by name and component type
mcp.disable(names={"dangerous_tool"}, components=["tool"])
# Disable by tag
mcp.disable(tags={"admin"})
# Disable by version
mcp.disable(names={"old_tool"}, version="1.0", components=["tool"])
# Allowlist mode - only show components with these tags
mcp.enable(tags={"public"}, only=True)
# Enable overrides earlier disable (later transform wins)
mcp.disable(tags={"internal"})
mcp.enable(names={"safe_tool"}) # safe_tool is visible despite internal tag
```
Works at both server and provider level. Supports:
- **Blocklist mode** (default): All components visible except explicitly disabled
- **Allowlist mode** (`only=True`): Only explicitly enabled components visible
- **Tag-based filtering**: Enable/disable groups of components by tag
- **Override semantics**: Later transforms override earlier marks (enable after disable = enabled)
- **Transform ordering**: Visibility transforms are injected at the point you call them, so component state is known
#### Per-Session Visibility
Server-level visibility changes affect all connected clients. For per-session control, use `Context` methods that apply rules only to the current session ([#2917](https://github.com/jlowin/fastmcp/pull/2917)):
```python
from fastmcp import FastMCP
from fastmcp.server.context import Context
mcp = FastMCP("Server")
@mcp.tool(tags={"premium"})
def premium_analysis(data: str) -> str:
return f"Premium analysis of: {data}"
@mcp.tool
async def unlock_premium(ctx: Context) -> str:
"""Unlock premium features for this session only."""
await ctx.enable_components(tags={"premium"})
return "Premium features unlocked"
@mcp.tool
async def reset_features(ctx: Context) -> str:
"""Reset to default feature set."""
await ctx.reset_visibility()
return "Features reset to defaults"
# Globally disabled - sessions unlock individually
mcp.disable(tags={"premium"})
```
Session visibility methods:
- `await ctx.enable_components(...)`: Enable components for this session
- `await ctx.disable_components(...)`: Disable components for this session
- `await ctx.reset_visibility()`: Clear session rules, return to global defaults
Session rules override global transforms. FastMCP automatically sends `ToolListChangedNotification` (and resource/prompt equivalents) to affected sessions when visibility changes.
Documentation: `docs/servers/visibility.mdx`
---
### Component Versioning
v3.0 introduces versioning support for tools, resources, and prompts. Components can declare a version, and when multiple versions of the same component exist, the highest version is automatically exposed to clients.
**Declaring versions:**
```python
@mcp.tool(version="1.0")
def add(x: int, y: int) -> int:
return x + y
@mcp.tool(version="2.0")
def add(x: int, y: int, z: int = 0) -> int:
return x + y + z
# Only v2.0 is exposed to clients via list_tools()
# Calling "add" invokes the v2.0 implementation
```
**Version comparison:**
- Uses PEP 440 semantic versioning (1.10 > 1.9 > 1.2)
- Falls back to string comparison for non-PEP 440 versions (dates like `2025-01-15` work)
- Unversioned components sort lower than any versioned component
- The `v` prefix is normalized (`v1.0` equals `1.0`)
**Version visibility in meta:**
List operations expose all available versions in the component's `meta` field:
```python
tools = await client.list_tools()
# Each tool's meta includes:
# - meta["fastmcp"]["version"]: the version of this component ("2.0")
# - meta["fastmcp"]["versions"]: all available versions ["2.0", "1.0"]
```
**Retrieving and calling specific versions:**
```python
# Get the highest version (default)
tool = await server.get_tool("add")
# Get a specific version
tool_v1 = await server.get_tool("add", version="1.0")
# Call a specific version
result = await server.call_tool("add", {"x": 1, "y": 2}, version="1.0")
```
**Client version requests:**
The FastMCP client supports version selection:
```python
async with Client(server) as client:
# Call specific tool version
result = await client.call_tool("add", {"x": 1, "y": 2}, version="1.0")
# Get specific prompt version
prompt = await client.get_prompt("my_prompt", {"text": "..."}, version="2.0")
```
For generic MCP clients, pass version via `_meta` in arguments:
```json
{
"x": 1,
"y": 2,
"_meta": {
"fastmcp": {
"version": "1.0"
}
}
}
```
**VersionFilter transform:**
The `VersionFilter` transform enables serving different API versions from a single codebase:
```python
from fastmcp import FastMCP
from fastmcp.server.providers import LocalProvider
from fastmcp.server.transforms import VersionFilter
# Define components on a shared provider
components = LocalProvider()
@components.tool(version="1.0")
def calculate(x: int, y: int) -> int:
return x + y
@components.tool(version="2.0")
def calculate(x: int, y: int, z: int = 0) -> int:
return x + y + z
# Create servers that share the provider with different filters
api_v1 = FastMCP("API v1", providers=[components])
api_v1.add_transform(VersionFilter(version_lt="2.0"))
api_v2 = FastMCP("API v2", providers=[components])
api_v2.add_transform(VersionFilter(version_gte="2.0"))
```
Parameters mirror comparison operators:
- `version_gte`: Versions >= this value pass through
- `version_lt`: Versions < this value pass through
**Key format:**
Component keys now include a version suffix using `@` as a delimiter:
- Versioned: `tool:add@1.0`, `resource:data://config@2.0`
- Unversioned: `tool:add@`, `resource:data://config@`
The `@` is always present (even for unversioned components) to enable unambiguous parsing of URIs that may contain `@`.
---
### Type-Safe Canonical Results
v3.0 introduces type-safe result classes that provide explicit control over component responses while supporting MCP runtime metadata: `ToolResult` ([#2736](https://github.com/jlowin/fastmcp/pull/2736)), `ResourceResult` ([#2734](https://github.com/jlowin/fastmcp/pull/2734)), and `PromptResult` ([#2738](https://github.com/jlowin/fastmcp/pull/2738)).
#### ToolResult
`ToolResult` (`src/fastmcp/tools/tool.py:79`) provides structured tool responses:
```python
from fastmcp.tools import ToolResult
@mcp.tool
def process(data: str) -> ToolResult:
return ToolResult(
content=[TextContent(type="text", text="Done")],
structured_content={"status": "success", "count": 42},
meta={"processing_time_ms": 150}
)
```
Fields:
- `content`: List of MCP ContentBlocks (text, images, etc.)
- `structured_content`: Dict matching tool's output schema
- `meta`: Runtime metadata passed to MCP as `_meta`
#### ResourceResult
`ResourceResult` (`src/fastmcp/resources/resource.py:117`) provides structured resource responses:
```python
from fastmcp.resources import ResourceResult, ResourceContent
@mcp.resource("data://items")
def get_items() -> ResourceResult:
return ResourceResult(
contents=[
ResourceContent({"key": "value"}), # auto-serialized to JSON
ResourceContent(b"binary data"),
],
meta={"count": 2}
)
```
Accepts strings, bytes, or `list[ResourceContent]` for flexible content handling.
#### PromptResult
`PromptResult` (`src/fastmcp/prompts/prompt.py:109`) provides structured prompt responses:
```python
from fastmcp.prompts import PromptResult, Message
@mcp.prompt
def conversation() -> PromptResult:
return PromptResult(
messages=[
Message("What's the weather?"),
Message("It's sunny today.", role="assistant"),
],
meta={"generated_at": "2024-01-01"}
)
```
---
### Background Tasks (SEP-1686)
v3.0 implements MCP SEP-1686 for background task execution via Docket integration.
**Configuration** (`src/fastmcp/server/tasks/config.py`):
```python
from fastmcp.server.tasks import TaskConfig
@mcp.tool(task=TaskConfig(mode="required"))
async def long_running_task():
# Must be executed as background task
...
@mcp.tool(task=TaskConfig(mode="optional"))
async def flexible_task():
# Supports both sync and task execution
...
@mcp.tool(task=True) # Shorthand for mode="optional"
async def simple_task():
...
```
Task modes:
- `"forbidden"`: Component does not support task execution (default)
- `"optional"`: Supports both synchronous and task execution
- `"required"`: Must be executed as background task
Requires Docket server for task scheduling and result polling.
---
### Decorators Return Functions
v3.0 changes what decorators (`@tool`, `@resource`, `@prompt`) return ([#2856](https://github.com/jlowin/fastmcp/pull/2856)). Decorators now return the original function unchanged, rather than transforming it into a component object.
**v3 behavior (default):**
```python
@mcp.tool
def greet(name: str) -> str:
return f"Hello, {name}!"
# greet is still your function - call it directly
greet("World") # "Hello, World!"
```
**Why this matters:**
- Functions stay callable - useful for testing and reuse
- Instance methods just work: `mcp.add_tool(obj.method)`
- Matches how Flask, FastAPI, and Typer decorators behave
**For v2 compatibility:**
```python
import fastmcp
# v2 behavior: decorators return FunctionTool/FunctionResource/FunctionPrompt objects
fastmcp.settings.decorator_mode = "object"
```
Environment variable: `FASTMCP_DECORATOR_MODE=object`
---
### CLI Auto-Reload
The `--reload` flag enables file watching with automatic server restarts for development ([#2816](https://github.com/jlowin/fastmcp/pull/2816)).
```bash
# Watch for changes and restart
fastmcp run server.py --reload
# Watch specific directories
fastmcp run server.py --reload --reload-dir ./src --reload-dir ./lib
# Works with any transport
fastmcp run server.py --reload --transport http --port 8080
```
Implementation (`src/fastmcp/cli/run.py`):
- Uses `watchfiles` for efficient file monitoring
- Runs server as subprocess for clean restarts
- Stateless mode for seamless reconnection after restart
- stdio: Full MCP features including elicitation
- HTTP: Limited bidirectional features during reload
Also available with `fastmcp dev`:
```bash
fastmcp dev server.py # Includes --reload by default
```
---
### Component Authorization
v3.0 introduces callable-based authorization for tools, resources, and prompts ([#2855](https://github.com/jlowin/fastmcp/pull/2855)).
**Component-level auth**:
```python
from fastmcp import FastMCP
from fastmcp.server.auth import require_auth, require_scopes
mcp = FastMCP()
@mcp.tool(auth=require_auth)
def protected_tool(): ...
@mcp.resource("data://secret", auth=require_scopes("read"))
def secret_data(): ...
@mcp.prompt(auth=require_scopes("admin"))
def admin_prompt(): ...
```
**Server-wide auth via middleware**:
```python
from fastmcp.server.middleware import AuthMiddleware
from fastmcp.server.auth import require_auth, restrict_tag
# Require auth for all components
mcp = FastMCP(middleware=[AuthMiddleware(auth=require_auth)])
# Tag-based restrictions
mcp = FastMCP(middleware=[
AuthMiddleware(auth=restrict_tag("admin", scopes=["admin"]))
])
```
Built-in checks:
- `require_auth`: Requires any valid token
- `require_scopes(*scopes)`: Requires specific OAuth scopes
- `restrict_tag(tag, scopes)`: Requires scopes only for tagged components
Custom checks receive `AuthContext` with `token` and `component`:
```python
def custom_check(ctx: AuthContext) -> bool:
return ctx.token is not None and "admin" in ctx.token.scopes
```
STDIO transport bypasses all auth checks (no OAuth concept).
---
### MCP Apps (SDK Compatibility)
v3.0 adds Phase 1 support for [MCP Apps](https://modelcontextprotocol.io/specification/2025-06-18/server/apps) — the spec extension that lets MCP servers deliver interactive UIs via sandboxed iframes. Phase 1 is SDK compatibility only: extension negotiation, typed UI metadata on tools and resources, and the `ui://` resource scheme. No component DSL, renderer, or `FastMCPApp` class yet — those are future phases.
**Registering tools with UI metadata:**
```python
from fastmcp import FastMCP
from fastmcp.server.apps import ToolUI, ResourceUI, UI_MIME_TYPE
mcp = FastMCP("My Server")
# Register the HTML bundle as a ui:// resource
@mcp.resource("ui://my-app/view.html")
def app_html() -> str:
from pathlib import Path
return Path("./dist/index.html").read_text()
# Tool with UI — clients render an iframe alongside the result
@mcp.tool(ui=ToolUI(resource_uri="ui://my-app/view.html"))
async def list_users() -> list[dict]:
return [{"id": "1", "name": "Alice"}]
# App-only tool — visible to the UI but hidden from the model
@mcp.tool(ui=ToolUI(resource_uri="ui://my-app/view.html", visibility=["app"]))
async def delete_user(id: str) -> dict:
return {"deleted": True}
```
The `ui=` parameter accepts either a typed model (`ToolUI`, `ResourceUI`) or a raw dict for forward compatibility. It merges into `meta["ui"]` — alongside any other metadata you set.
**`ui://` resources** automatically get the correct MIME type (`text/html;profile=mcp-app`) unless you override it explicitly.
**Extension negotiation**: The server advertises `io.modelcontextprotocol/ui` in `capabilities.extensions`. UI metadata (`_meta.ui`) always flows through to clients — the MCP Apps spec assigns visibility enforcement to the host, not the server. Tools can check whether the connected client supports a given extension at runtime via `ctx.client_supports_extension()`:
```python
from fastmcp import Context
from fastmcp.server.apps import ToolUI, UI_EXTENSION_ID
@mcp.tool(ui=ToolUI(resource_uri="ui://dashboard"))
async def dashboard(ctx: Context) -> dict:
data = compute_dashboard()
if ctx.client_supports_extension(UI_EXTENSION_ID):
# Client will render the iframe with structured data
return data
# Fallback: text-only summary
return {"summary": format_text(data)}
```
**Key details:**
- `ToolUI` fields: `resource_uri`, `visibility`, `csp`, `permissions`, `domain`, `prefers_border` (all optional except for typical usage of `resource_uri`)
- `ResourceUI` fields: `csp`, `permissions`, `domain`, `prefers_border` — metadata for the resource itself when it's a UI bundle
- Models use Pydantic aliases for wire format (`resourceUri`, `prefersBorder`)
- `ctx.client_supports_extension(id)` is a general-purpose method — works for any extension, not just MCP Apps
- `structuredContent` in tool results already works via `ToolResult` — MCP Apps clients use this to pass data into the iframe
- Text content fallback already works — tools return both `content` and `structured_content`
- The server does not strip `_meta.ui` for non-UI clients; per the spec, visibility enforcement is the host's responsibility
**Future phases** will add a component DSL for building UIs declaratively, an in-repo renderer, and a `FastMCPApp` class.
Implementation: `src/fastmcp/server/apps.py` (models and constants), with integration points in `server.py` (decorator parameters), `low_level.py` (extension advertisement), and `context.py` (`client_supports_extension` method).
---
### FileSystemProvider
v3.0 introduces `FileSystemProvider`, a fundamentally different approach to organizing MCP servers. Instead of importing a server instance and decorating functions with `@server.tool`, you use standalone decorators in separate files and let the provider discover them.
**The problem it solves**: Traditional servers require coordination between files—either tool files import the server (creating coupling) or the server imports all tool modules (creating a registry bottleneck). FileSystemProvider removes this coupling entirely.
**Usage** ([#2823](https://github.com/jlowin/fastmcp/pull/2823)):
```python
from fastmcp import FastMCP
from fastmcp.server.providers import FileSystemProvider
# Scans mcp/ directory for decorated functions
mcp = FastMCP("server", providers=[FileSystemProvider("mcp/")])
```
**Tool files are self-contained**:
```python
# mcp/tools/greet.py
from fastmcp.tools import tool
@tool
def greet(name: str) -> str:
"""Greet someone by name."""
return f"Hello, {name}!"
```
Features:
- **Standalone decorators**: `@tool`, `@resource`, `@prompt` from `fastmcp.tools`, `fastmcp.resources`, `fastmcp.prompts` ([#2832](https://github.com/jlowin/fastmcp/pull/2832))
- **Reload mode**: `FileSystemProvider("mcp/", reload=True)` re-scans on every request for development
- **Package support**: Directories with `__init__.py` support relative imports
- **Warning deduplication**: Broken imports warn once per file modification
Documentation: [FileSystemProvider](/servers/providers/filesystem)
---
### SkillsProvider
v3.0 introduces `SkillsProvider` for exposing agent skills as MCP resources ([#2944](https://github.com/jlowin/fastmcp/pull/2944)). Skills are directories containing instructions and supporting files that teach AI assistants how to perform tasks—used by Claude Code, Cursor, VS Code Copilot, and other AI coding tools.
**Usage**:
```python
from pathlib import Path
from fastmcp import FastMCP
from fastmcp.server.providers.skills import SkillsDirectoryProvider
mcp = FastMCP("Skills Server")
mcp.add_provider(SkillsDirectoryProvider(roots=Path.home() / ".claude" / "skills"))
```
Each subdirectory with a `SKILL.md` file becomes a discoverable skill. Clients see:
- `skill://{name}/SKILL.md` - Main instruction file
- `skill://{name}/_manifest` - JSON listing of all files with sizes and hashes
- `skill://{name}/{path}` - Supporting files (via template or resources)
**Two-layer architecture**:
- `SkillProvider` - Handles a single skill folder
- `SkillsDirectoryProvider` - Scans directories, creates a `SkillProvider` per valid skill
**Vendor providers** with locked default paths:
| Provider | Directory |
|----------|-----------|
| `ClaudeSkillsProvider` | `~/.claude/skills/` |
| `CursorSkillsProvider` | `~/.cursor/skills/` |
| `VSCodeSkillsProvider` | `~/.copilot/skills/` |
| `CodexSkillsProvider` | `/etc/codex/skills/`, `~/.codex/skills/` |
| `GeminiSkillsProvider` | `~/.gemini/skills/` |
| `GooseSkillsProvider` | `~/.config/agents/skills/` |
| `CopilotSkillsProvider` | `~/.copilot/skills/` |
| `OpenCodeSkillsProvider` | `~/.config/opencode/skills/` |
**Progressive disclosure**: By default, supporting files are hidden from `list_resources()` and accessed via template. Set `supporting_files="resources"` for full enumeration.
Documentation: [Skills Provider](/servers/providers/skills)
---
### OpenTelemetry Tracing
v3.0 adds OpenTelemetry instrumentation for observability into server and client operations ([#2869](https://github.com/jlowin/fastmcp/pull/2869)).
**Server spans**: Created for tool calls, resource reads, and prompt renders with attributes including component key, provider type, session ID, and auth context.
**Client spans**: Wrap outgoing calls with W3C trace context propagation via request meta.
```python
# Tracing is passive - configure an OTel SDK to export spans
from opentelemetry import trace
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor
from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter
provider = TracerProvider()
provider.add_span_processor(BatchSpanProcessor(OTLPSpanExporter()))
trace.set_tracer_provider(provider)
# Use fastmcp normally - spans export to your configured backend
```
Components provide their own span attributes through a `get_span_attributes()` method that subclasses override—this lets LocalProvider, FastMCPProvider, and ProxyProvider each include relevant context (original names, backend URIs, etc.).
Documentation: [Telemetry](/servers/telemetry)
---
### Pagination
v3.0 adds pagination support for list operations when servers expose many components ([#2903](https://github.com/jlowin/fastmcp/pull/2903)).
```python
from fastmcp import FastMCP
# Enable pagination with 50 items per page
server = FastMCP("ComponentRegistry", list_page_size=50)
```
When `list_page_size` is set, `tools/list`, `resources/list`, `resources/templates/list`, and `prompts/list` paginate responses with `nextCursor` for subsequent pages.
**Client behavior**: The FastMCP Client fetches all pages automatically—`list_tools()` and similar methods return the complete list. For manual pagination (memory constraints, progress reporting), use `_mcp` variants:
```python
async with Client(server) as client:
result = await client.list_tools_mcp()
while result.nextCursor:
result = await client.list_tools_mcp(cursor=result.nextCursor)
```
Documentation: [Pagination](/servers/pagination)
---
### Composable Lifespans
Lifespans can be combined with the `|` operator for modular setup/teardown ([#2828](https://github.com/jlowin/fastmcp/pull/2828)):
```python
from fastmcp import FastMCP
from fastmcp.server.lifespan import lifespan
@lifespan
async def db_lifespan(server):
db = await connect_db()
try:
yield {"db": db}
finally:
await db.close()
@lifespan
async def cache_lifespan(server):
cache = await connect_cache()
try:
yield {"cache": cache}
finally:
await cache.close()
mcp = FastMCP("server", lifespan=db_lifespan | cache_lifespan)
```
Both enter lifespans in order and exit in reverse (LIFO). Context dicts are merged.
Also adds `combine_lifespans()` utility for FastAPI integration:
```python
from fastmcp.utilities.lifespan import combine_lifespans
app = FastAPI(lifespan=combine_lifespans(app_lifespan, mcp_app.lifespan))
```
Documentation: [Lifespan](/servers/lifespan)
---
### Tool Timeout
Tools can limit foreground execution time with a `timeout` parameter ([#2872](https://github.com/jlowin/fastmcp/pull/2872)):
```python
@mcp.tool(timeout=30.0)
async def fetch_data(url: str) -> dict:
"""Fetch with 30-second timeout."""
...
```
When exceeded, clients receive MCP error code `-32000`. Both sync and async tools are supported—sync functions run in thread pools so the timeout applies regardless of execution model.
Note: This timeout applies to foreground execution only. Background tasks (`task=True`) execute in Docket workers where this timeout isn't enforced.
---
### PingMiddleware
Sends periodic server-to-client pings to keep long-lived connections alive ([#2838](https://github.com/jlowin/fastmcp/pull/2838)):
```python
from fastmcp import FastMCP
from fastmcp.server.middleware import PingMiddleware
mcp = FastMCP("server")
mcp.add_middleware(PingMiddleware(interval_ms=5000))
```
The middleware starts a background ping task on first message from each session, using the session's existing task group for automatic cleanup when the session ends.
---
### Context.transport Property
Tools can detect which transport is active ([#2850](https://github.com/jlowin/fastmcp/pull/2850)):
```python
from fastmcp import FastMCP, Context
mcp = FastMCP("example")
@mcp.tool
def my_tool(ctx: Context) -> str:
if ctx.transport == "stdio":
return "short response"
return "detailed response with more context"
```
Returns `Literal["stdio", "sse", "streamable-http"]` when running, or `None` outside a server context.
---
### Automatic Threadpool for Sync Functions
Synchronous tools, resources, and prompts now automatically run in a threadpool, preventing event loop blocking during concurrent requests ([#2865](https://github.com/jlowin/fastmcp/pull/2865)):
```python
import time
@mcp.tool
def slow_tool():
time.sleep(10) # No longer blocks other requests
return "done"
```
Three concurrent calls now execute in parallel (~10s) rather than sequentially (30s). Uses `anyio.to_thread.run_sync()` which properly propagates contextvars, so `Context` and `Depends` continue to work.
---
### CLI Update Notifications
The CLI notifies users when a newer FastMCP version is available on PyPI ([#2840](https://github.com/jlowin/fastmcp/pull/2840)).
**Setting**: `FASTMCP_CHECK_FOR_UPDATES`
- `"stable"` - Check for stable releases (default)
- `"prerelease"` - Include alpha/beta/rc versions
- `"off"` - Disable
12-hour cache, 2-second timeout, fails silently on network errors.
---
### Deprecated Features
These emit deprecation warnings but continue to work.
#### Mount Prefix Parameter
The `prefix` parameter for `mount()` renamed to `namespace`:
```python
# Deprecated
main.mount(subserver, prefix="api")
# New
main.mount(subserver, namespace="api")
```
#### Tag Filtering Init Parameters
`FastMCP(include_tags=..., exclude_tags=...)` deprecated. Use `enable()`/`disable()` methods:
```python
# Deprecated
mcp = FastMCP("server", exclude_tags={"internal"})
# New
mcp = FastMCP("server")
mcp.disable(tags={"internal"})
```
#### Tool Serializer Parameter
The `tool_serializer` parameter on `FastMCP` is deprecated. Return `ToolResult` for explicit serialization control.
#### Tool Transformation Methods
`add_tool_transformation()`, `remove_tool_transformation()`, and `tool_transformations` constructor parameter are deprecated. Use `add_transform(ToolTransform({...}))` instead:
```python
# Deprecated
mcp.add_tool_transformation("name", config)
# New
from fastmcp.server.transforms import ToolTransform
mcp.add_transform(ToolTransform({"name": config}))
```
---
### Breaking Changes
#### WSTransport Removed
The deprecated `WSTransport` client transport has been removed ([#2826](https://github.com/jlowin/fastmcp/pull/2826)). Use `StreamableHttpTransport` instead.
#### Decorators Return Functions
Decorators (`@tool`, `@resource`, `@prompt`) now return the original function instead of component objects. Code that treats the decorated function as a `FunctionTool`, `FunctionResource`, or `FunctionPrompt` will break.
```python
# v2.x
@mcp.tool
def greet(name: str) -> str:
return f"Hello, {name}!"
isinstance(greet, FunctionTool) # True
# v3.0
@mcp.tool
def greet(name: str) -> str:
return f"Hello, {name}!"
isinstance(greet, FunctionTool) # False
callable(greet) # True - it's still your function
greet("World") # "Hello, World!"
```
Set `FASTMCP_DECORATOR_MODE=object` or `fastmcp.settings.decorator_mode = "object"` for v2 behavior.
#### Component Enable/Disable Moved to Server/Provider
The `enabled` field and `enable()`/`disable()` methods removed from component objects:
```python
# v2.x
tool = await server.get_tool("my_tool")
tool.disable()
# v3.0
server.disable(names={"my_tool"}, components=["tool"])
```
#### Component Lookup Methods
Server lookup and listing methods have updated signatures:
- Parameter names: `get_tool(name=...)`, `get_resource(uri=...)`, etc. (was `key`)
- Return types: `get_tools()`, `get_resources()`, etc. return lists instead of dicts
```python
# v2.x
tools = await server.get_tools()
tool = tools["my_tool"]
# v3.0
tools = await server.get_tools()
tool = next((t for t in tools if t.name == "my_tool"), None)
```
#### Prompt Return Types
Prompt functions now use `Message` instead of `mcp.types.PromptMessage`:
```python
# v2.x
from mcp.types import PromptMessage, TextContent
@mcp.prompt
def my_prompt() -> PromptMessage:
return PromptMessage(role="user", content=TextContent(type="text", text="Hello"))
# v3.0
from fastmcp.prompts import Message
@mcp.prompt
def my_prompt() -> Message:
return Message("Hello") # role defaults to "user"
```
#### Auth Provider Environment Variables Removed
Auth providers no longer auto-load from environment variables ([#2752](https://github.com/jlowin/fastmcp/pull/2752)):
```python
# v2.x - auto-loaded from FASTMCP_SERVER_AUTH_GITHUB_*
auth = GitHubProvider()
# v3.0 - explicit configuration
import os
auth = GitHubProvider(
client_id=os.environ["GITHUB_CLIENT_ID"],
client_secret=os.environ["GITHUB_CLIENT_SECRET"],
)
```
See `docs/development/v3-notes/auth-provider-env-vars.mdx` for rationale.
#### Server Banner Environment Variable
`FASTMCP_SHOW_CLI_BANNER` → `FASTMCP_SHOW_SERVER_BANNER` ([#2771](https://github.com/jlowin/fastmcp/pull/2771))
Now applies to all server startup methods, not just the CLI.
#### Context State Methods Are Async
`ctx.set_state()` and `ctx.get_state()` are now async and session-scoped:
```python
# v2.x
ctx.set_state("key", "value")
value = ctx.get_state("key")
# v3.0
await ctx.set_state("key", "value")
value = await ctx.get_state("key")
```
State now persists across requests within a session. See "Session-Scoped State" above.