fastmcp/docs/servers/middleware.mdx

---
title: Middleware
sidebarTitle: Middleware
description: Add cross-cutting functionality to your MCP server with middleware that intercepts and modifies requests and responses.
icon: layer-group
---

import { VersionBadge } from "/snippets/version-badge.mdx"

<VersionBadge version="2.9.0" />

Middleware adds behavior that applies across multiple operations—authentication, logging, rate limiting, or request transformation—without modifying individual tools or resources.

<Tip>
MCP middleware is a FastMCP-specific concept and is not part of the official MCP protocol specification.
</Tip>

## Overview

MCP middleware forms a pipeline around your server's operations. When a request arrives, it flows through each middleware in order—each can inspect, modify, or reject the request before passing it along. After the operation completes, the response flows back through the same middleware in reverse order.

```
Request → Middleware A → Middleware B → Handler → Middleware B → Middleware A → Response
```

This bidirectional flow means middleware can:
- **Pre-process**: Validate authentication, log incoming requests, check rate limits
- **Post-process**: Transform responses, record timing metrics, handle errors consistently

The key decision point is `call_next(context)`. Calling it continues the chain; not calling it stops processing entirely.

```python
from fastmcp import FastMCP
from fastmcp.server.middleware import Middleware, MiddlewareContext

class LoggingMiddleware(Middleware):
    async def on_message(self, context: MiddlewareContext, call_next):
        print(f"→ {context.method}")
        result = await call_next(context)
        print(f"← {context.method}")
        return result

mcp = FastMCP("MyServer")
mcp.add_middleware(LoggingMiddleware())
```

### Execution Order

Middleware executes in the order added to the server. The first middleware runs first on the way in and last on the way out:

```python
from fastmcp import FastMCP
from fastmcp.server.middleware.error_handling import ErrorHandlingMiddleware
from fastmcp.server.middleware.rate_limiting import RateLimitingMiddleware
from fastmcp.server.middleware.logging import LoggingMiddleware

mcp = FastMCP("MyServer")
mcp.add_middleware(ErrorHandlingMiddleware())   # 1st in, last out
mcp.add_middleware(RateLimitingMiddleware())    # 2nd in, 2nd out
mcp.add_middleware(LoggingMiddleware())         # 3rd in, first out
```

This ordering matters. Place error handling early so it catches exceptions from all subsequent middleware. Place logging late so it records the actual execution after other middleware has processed the request.

### Server Composition

When using [mounted servers](/servers/composition), middleware behavior follows a clear hierarchy:

- **Parent middleware** runs for all requests, including those routed to mounted servers
- **Mounted server middleware** only runs for requests handled by that specific server

```python
from fastmcp import FastMCP
from fastmcp.server.middleware.logging import LoggingMiddleware

parent = FastMCP("Parent")
parent.add_middleware(AuthMiddleware())  # Runs for ALL requests

child = FastMCP("Child")
child.add_middleware(LoggingMiddleware())  # Only runs for child's tools

parent.mount(child, namespace="child")
```

Requests to `child_tool` flow through the parent's `AuthMiddleware` first, then through the child's `LoggingMiddleware`.

Middleware-stored state does not automatically cross mount boundaries. If `AuthMiddleware` on the parent calls `ctx.set_state("user_id", ...)`, a tool on the child server calling `ctx.get_state("user_id")` will get `None` — each `FastMCP` instance owns its own session state store. To share state across the mount, either pass the same `session_state_store` to both servers or use `serializable=False` for request-scoped values. See [State and Mounted Servers](/servers/context#state-and-mounted-servers) for details.

## Hooks

Rather than processing every message identically, FastMCP provides specialized hooks at different levels of specificity. Multiple hooks fire for a single request, going from general to specific:

| Level | Hooks | Purpose |
|-------|-------|---------|
| Message | `on_message` | All MCP traffic (requests and notifications) |
| Type | `on_request`, `on_notification` | Requests expecting responses vs fire-and-forget |
| Operation | `on_call_tool`, `on_read_resource`, `on_get_prompt`, etc. | Specific MCP operations |

When a client calls a tool, the middleware chain processes `on_message` first, then `on_request`, then `on_call_tool`. This hierarchy lets you target exactly the right scope—use `on_message` for logging everything, `on_request` for authentication, and `on_call_tool` for tool-specific behavior.

### What middleware sees

<VersionBadge version="4.0.0" />

Dispatch begins in the SDK's middleware layer — the single point every inbound message passes through. As a result, `on_message`, `on_request`, and `on_notification` observe **every** message a client sends, including the ones that never reach a tool, resource, or prompt handler:

- **Notifications** such as `notifications/cancelled`, `notifications/initialized`, and `notifications/progress` reach `on_message` and `on_notification`.
- **Cancellations** are observed as a `notifications/cancelled` message. The connection applies the cancellation itself and then hands the notification to your middleware.
- **Malformed or unroutable requests**—an unknown method, or a `tools/call` whose params fail validation before the tool runs—reach `on_message` and `on_request` as a raised error propagating through `call_next`, so logging and error-handling middleware record them.

The operation hooks (`on_call_tool`, `on_list_tools`, and the rest) fire exactly once per request, and their `call_next` still returns the typed component result—a `ToolResult`, a `list[Tool]`, and so on—so a tool exception propagates through `on_call_tool`, `on_request`, and `on_message` exactly where error, logging, and timing middleware expect it.

#### Multi-round tool calls

A guard tool asks the client for input by returning an `InputRequiredResult` (see [Elicitation on the modern protocol](/servers/elicitation#elicitation-on-the-modern-protocol)). Each round of a multi-round call is a complete request→response cycle that runs the **full middleware chain**: `on_call_tool` fires once per round, and on an asking round `call_next` returns the ask as that round's ordinary result value—an `InputRequiredToolResult`, a `ToolResult` subclass. Nothing is raised and nothing is held open, so default middleware completes normally on every round (logging logs the ask, timing times it, error handling does not fire—an ask is a legitimate result, not an error). Middleware that needs to treat an ask differently identifies it with an `isinstance(result, InputRequiredToolResult)` check; see [Middleware and multi-round calls](/servers/elicitation#middleware) for a worked example.

### Hook Signature

Every hook follows the same pattern:

```python
async def hook_name(self, context: MiddlewareContext, call_next) -> result_type:
    # Pre-processing
    result = await call_next(context)
    # Post-processing
    return result
```

**Parameters:**
- `context` — `MiddlewareContext` containing request information
- `call_next` — Async function to continue the middleware chain

**Returns:** The appropriate result type for the hook (varies by operation).

### MiddlewareContext

The `context` parameter provides access to request details:

| Attribute | Type | Description |
|-----------|------|-------------|
| `method` | `str` | MCP method name (e.g., `"tools/call"`) |
| `source` | `str` | Origin: `"client"` or `"server"` |
| `type` | `str` | Message type: `"request"` or `"notification"` |
| `message` | `object` | The MCP message data |
| `timestamp` | `datetime` | When the request was received |
| `fastmcp_context` | `Context` | FastMCP context object (if available) |

### Message Hooks

#### on_message

Called for every MCP message—both requests and notifications.

```python
async def on_message(self, context: MiddlewareContext, call_next):
    result = await call_next(context)
    return result
```

Use for: Logging, metrics, or any cross-cutting concern that applies to all traffic.

#### on_request

Called for MCP requests that expect a response.

```python
async def on_request(self, context: MiddlewareContext, call_next):
    result = await call_next(context)
    return result
```

Use for: Authentication, authorization, request validation.

#### on_notification

Called for fire-and-forget MCP notifications.

```python
async def on_notification(self, context: MiddlewareContext, call_next):
    await call_next(context)
    # Notifications don't return values
```

Use for: Event logging, async side effects.

### Operation Hooks

#### on_call_tool

Called when a tool is executed. The `context.message` contains `name` (tool name) and `arguments` (dict).

```python
async def on_call_tool(self, context: MiddlewareContext, call_next):
    tool_name = context.message.name
    args = context.message.arguments
    result = await call_next(context)
    return result
```

**Returns:** Tool execution result or raises `ToolError`.

#### on_read_resource

Called when a resource is read. The `context.message` contains `uri` (resource URI).

```python
async def on_read_resource(self, context: MiddlewareContext, call_next):
    uri = context.message.uri
    result = await call_next(context)
    return result
```

**Returns:** Resource content.

#### on_get_prompt

Called when a prompt is retrieved. The `context.message` contains `name` (prompt name) and `arguments` (dict).

```python
async def on_get_prompt(self, context: MiddlewareContext, call_next):
    prompt_name = context.message.name
    result = await call_next(context)
    return result
```

**Returns:** Prompt messages.

#### on_list_tools

Called when listing available tools. Returns a list of FastMCP `Tool` objects before MCP conversion.

```python
async def on_list_tools(self, context: MiddlewareContext, call_next):
    tools = await call_next(context)
    # Filter or modify the tool list
    return tools
```

**Returns:** `list[Tool]` — Can be filtered before returning to client.

#### on_list_resources

Called when listing available resources. Returns FastMCP `Resource` objects.

```python
async def on_list_resources(self, context: MiddlewareContext, call_next):
    resources = await call_next(context)
    return resources
```

**Returns:** `list[Resource]`

#### on_list_resource_templates

Called when listing resource templates.

```python
async def on_list_resource_templates(self, context: MiddlewareContext, call_next):
    templates = await call_next(context)
    return templates
```

**Returns:** `list[ResourceTemplate]`

#### on_list_prompts

Called when listing available prompts.

```python
async def on_list_prompts(self, context: MiddlewareContext, call_next):
    prompts = await call_next(context)
    return prompts
```

**Returns:** `list[Prompt]`

#### on_initialize

<VersionBadge version="2.13.0" />

Called when a client connects and initializes the session. Middleware can reject the client before `call_next()` raises an error response, or inspect and modify the `InitializeResult` after `call_next()` returns.

The request params carry the identity the client declared for itself on `client_info`, which makes this the natural place to gate access by client. Note that these fields are snake_case: the MCP wire format spells it `clientInfo`, but the Python model exposes `client_info` and treats the camelCase form as a serialization alias only.

```python
from fastmcp.exceptions import McpError

async def on_initialize(self, context: MiddlewareContext, call_next):
    client_name = context.message.params.client_info.name

    # Reject before call_next to send error to client
    if client_name == "blocked-client":
        raise McpError(code=-32000, message="Client not supported")

    result = await call_next(context)
    print(f"Client {client_name} initialized")
    return result
```

**Returns:** `InitializeResult | None` — The value you return is what gets serialized to the client, so modifying the result from `call_next()` changes what the client receives, including fields like `instructions` and `server_info`.

```python
async def on_initialize(self, context: MiddlewareContext, call_next):
    result = await call_next(context)
    result.instructions = "Custom instructions for this client"
    return result
```

<Warning>
Rejection works only **before** `call_next()`. Raising `McpError` afterward logs the error without sending it — the client still receives a successful initialize response.
</Warning>

### Raw Handler

For complete control over all messages, override `__call__` instead of individual hooks:

```python
from fastmcp.server.middleware import Middleware, MiddlewareContext

class RawMiddleware(Middleware):
    async def __call__(self, context: MiddlewareContext, call_next):
        print(f"Processing: {context.method}")
        result = await call_next(context)
        print(f"Completed: {context.method}")
        return result
```

This bypasses the hook dispatch system entirely. Use when you need uniform handling regardless of message type.

### Session Availability

<VersionBadge version="2.13.1" />

The MCP session may not be available during certain phases like initialization. Check before accessing session-specific attributes:

```python
async def on_request(self, context: MiddlewareContext, call_next):
    ctx = context.fastmcp_context

    if ctx.request_context:
        # MCP session available
        session_id = ctx.session_id
        request_id = ctx.request_id
    else:
        # Session not yet established (e.g., during initialization)
        # Use HTTP helpers if needed
        from fastmcp.server.dependencies import get_http_headers
        headers = get_http_headers()

    return await call_next(context)
```

For HTTP-specific data (headers, client IP) when using HTTP transports, see [HTTP Requests](/servers/context#http-requests).

## Built-in Middleware

FastMCP includes production-ready middleware for common server concerns.

### Logging

```python
from fastmcp.server.middleware.logging import LoggingMiddleware, StructuredLoggingMiddleware
```

`LoggingMiddleware` provides human-readable request and response logging. `StructuredLoggingMiddleware` outputs JSON-formatted logs for aggregation tools like Datadog or Splunk.

```python
from fastmcp import FastMCP
from fastmcp.server.middleware.logging import LoggingMiddleware

mcp = FastMCP("MyServer")
mcp.add_middleware(LoggingMiddleware(
    include_payloads=True,
    max_payload_length=1000
))
```

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `include_payloads` | `bool` | `False` | Log request/response content |
| `max_payload_length` | `int` | `500` | Truncate payloads beyond this length |
| `logger` | `Logger` | module logger | Custom logger instance |

### Timing

```python
from fastmcp.server.middleware.timing import TimingMiddleware, DetailedTimingMiddleware
```

`TimingMiddleware` logs execution duration for all requests. `DetailedTimingMiddleware` provides per-operation timing with separate tracking for tools, resources, and prompts.

```python
from fastmcp import FastMCP
from fastmcp.server.middleware.timing import TimingMiddleware

mcp = FastMCP("MyServer")
mcp.add_middleware(TimingMiddleware())
```

### Caching

```python
from fastmcp.server.middleware.caching import ResponseCachingMiddleware
```

Caches tool calls, resource reads, and list operations with TTL-based expiration.

```python
from fastmcp import FastMCP
from fastmcp.server.middleware.caching import ResponseCachingMiddleware

mcp = FastMCP("MyServer")
mcp.add_middleware(ResponseCachingMiddleware())
```

Each operation type can be configured independently using settings classes:

```python
from fastmcp.server.middleware.caching import (
    ResponseCachingMiddleware,
    CallToolSettings,
    ListToolsSettings,
    ReadResourceSettings
)

mcp.add_middleware(ResponseCachingMiddleware(
    list_tools_settings=ListToolsSettings(ttl=30),
    call_tool_settings=CallToolSettings(included_tools=["expensive_tool"]),
    read_resource_settings=ReadResourceSettings(enabled=False)
))
```

| Settings Class | Configures |
|----------------|------------|
| `ListToolsSettings` | `on_list_tools` caching |
| `CallToolSettings` | `on_call_tool` caching |
| `ListResourcesSettings` | `on_list_resources` caching |
| `ReadResourceSettings` | `on_read_resource` caching |
| `ListPromptsSettings` | `on_list_prompts` caching |
| `GetPromptSettings` | `on_get_prompt` caching |

Each settings class accepts:
- `enabled` — Enable/disable caching for this operation
- `ttl` — Time-to-live in seconds
- `included_*` / `excluded_*` — Whitelist or blacklist specific items

For persistence or distributed deployments, configure a different storage backend:

```python
from pathlib import Path
from fastmcp.server.middleware.caching import ResponseCachingMiddleware
from key_value.aio.stores.filetree import (
    FileTreeStore,
    FileTreeV1KeySanitizationStrategy,
    FileTreeV1CollectionSanitizationStrategy,
)

cache_dir = Path("cache")
mcp.add_middleware(ResponseCachingMiddleware(
    cache_storage=FileTreeStore(
        data_directory=cache_dir,
        key_sanitization_strategy=FileTreeV1KeySanitizationStrategy(cache_dir),
        collection_sanitization_strategy=FileTreeV1CollectionSanitizationStrategy(cache_dir),
    )
))
```

See [Storage Backends](/servers/storage-backends) for complete options.

<Note>
Cache keys are based on the operation name and arguments only — they do not include user or session identity. If your tools return user-specific data derived from auth context (e.g., headers or session state) rather than from the request arguments, you should either disable caching for those tools or ensure user identity is part of the tool arguments.
</Note>

### Rate Limiting

```python
from fastmcp.server.middleware.rate_limiting import (
    RateLimitingMiddleware,
    SlidingWindowRateLimitingMiddleware
)
```

`RateLimitingMiddleware` uses a token bucket algorithm allowing controlled bursts. `SlidingWindowRateLimitingMiddleware` provides precise time-window rate limiting without burst allowance.

```python
from fastmcp import FastMCP
from fastmcp.server.middleware.rate_limiting import RateLimitingMiddleware

mcp = FastMCP("MyServer")
mcp.add_middleware(RateLimitingMiddleware(
    max_requests_per_second=10.0,
    burst_capacity=20
))
```

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `max_requests_per_second` | `float` | `10.0` | Sustained request rate |
| `burst_capacity` | `int` | `20` | Maximum burst size |
| `get_client_id` | `Callable` | `None` | Custom client identification |

For sliding window rate limiting:

```python
from fastmcp.server.middleware.rate_limiting import SlidingWindowRateLimitingMiddleware

mcp.add_middleware(SlidingWindowRateLimitingMiddleware(
    max_requests=100,
    window_minutes=1
))
```

### Error Handling

```python
from fastmcp.server.middleware.error_handling import ErrorHandlingMiddleware, RetryMiddleware
```

`ErrorHandlingMiddleware` provides centralized error logging and transformation. `RetryMiddleware` automatically retries with exponential backoff for transient failures.

```python
from fastmcp import FastMCP
from fastmcp.server.middleware.error_handling import ErrorHandlingMiddleware

mcp = FastMCP("MyServer")
mcp.add_middleware(ErrorHandlingMiddleware(
    include_traceback=True,
    transform_errors=True,
    error_callback=my_error_callback
))
```

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `include_traceback` | `bool` | `False` | Include stack traces in logs |
| `transform_errors` | `bool` | `False` | Convert exceptions to MCP errors |
| `error_callback` | `Callable` | `None` | Custom callback on errors |

For automatic retries:

```python
from fastmcp.server.middleware.error_handling import RetryMiddleware

mcp.add_middleware(RetryMiddleware(
    max_retries=3,
    retry_exceptions=(ConnectionError, TimeoutError)
))
```

### Ping

<VersionBadge version="3.0.0" />

```python
from fastmcp.server.middleware import PingMiddleware
```

Keeps long-lived connections alive by sending periodic pings.

```python
from fastmcp import FastMCP
from fastmcp.server.middleware import PingMiddleware

mcp = FastMCP("MyServer")
mcp.add_middleware(PingMiddleware(interval_ms=5000))
```

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `interval_ms` | `int` | `30000` | Ping interval in milliseconds |

The ping task starts on the first message and stops automatically when the session ends. Most useful for stateful HTTP connections; has no effect on stateless connections.

### Response Limiting

<VersionBadge version="3.0.0" />

```python
from fastmcp.server.middleware.response_limiting import ResponseLimitingMiddleware
```

Large tool responses can overwhelm LLM context windows or cause memory issues. You can add response-limiting middleware to enforce size constraints on tool outputs.

```python
from fastmcp import FastMCP
from fastmcp.server.middleware.response_limiting import ResponseLimitingMiddleware

mcp = FastMCP("MyServer")

# Limit all tool responses to 500KB
mcp.add_middleware(ResponseLimitingMiddleware(max_size=500_000))

@mcp.tool
def search(query: str) -> str:
    # This could return a very large result
    return "x" * 1_000_000  # 1MB response

# When called, the response will be truncated to ~500KB with:
# "...\n\n[Response truncated due to size limit]"
```

When a response exceeds the limit, the middleware extracts all text content, joins it together, truncates to fit within the limit, and returns a single `TextContent` block. For non-text responses, the serialized JSON is used as the text source.

<Note>
If a tool defines an `output_schema`, truncated responses will no longer conform to that schema — the client will receive a plain `TextContent` block instead of the expected structured output. Keep this in mind when setting size limits for tools with structured responses.
</Note>

```python
# Limit only specific tools
mcp.add_middleware(ResponseLimitingMiddleware(
    max_size=100_000,
    tools=["search", "fetch_data"],
))
```

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `max_size` | `int` | `1_000_000` | Maximum response size in bytes (1MB default) |
| `truncation_suffix` | `str` | `"\n\n[Response truncated due to size limit]"` | Suffix appended to truncated responses |
| `tools` | `list[str] \| None` | `None` | Limit only these tools (None = all tools) |

### Combining Middleware

Order matters. Place middleware that should run first (on the way in) earliest:

```python
from fastmcp import FastMCP
from fastmcp.server.middleware.error_handling import ErrorHandlingMiddleware
from fastmcp.server.middleware.rate_limiting import RateLimitingMiddleware
from fastmcp.server.middleware.timing import TimingMiddleware
from fastmcp.server.middleware.logging import LoggingMiddleware

mcp = FastMCP("Production Server")

mcp.add_middleware(ErrorHandlingMiddleware())   # Catch all errors
mcp.add_middleware(RateLimitingMiddleware(max_requests_per_second=50))
mcp.add_middleware(TimingMiddleware())
mcp.add_middleware(LoggingMiddleware())

@mcp.tool
def my_tool(data: str) -> str:
    return f"Processed: {data}"
```

## Custom Middleware

When the built-in middleware doesn't fit your needs—custom authentication schemes, domain-specific logging, or request transformation—subclass `Middleware` and override the hooks you need.

```python
from fastmcp import FastMCP
from fastmcp.server.middleware import Middleware, MiddlewareContext

class CustomMiddleware(Middleware):
    async def on_request(self, context: MiddlewareContext, call_next):
        # Pre-processing
        print(f"→ {context.method}")

        result = await call_next(context)

        # Post-processing
        print(f"← {context.method}")
        return result

mcp = FastMCP("MyServer")
mcp.add_middleware(CustomMiddleware())
```

Override only the hooks relevant to your use case. Unoverridden hooks pass through automatically.

### Denying Requests

Raise the appropriate error type to stop processing and return an error to the client.

```python
from fastmcp.server.middleware import Middleware, MiddlewareContext
from fastmcp.exceptions import ToolError

class AuthMiddleware(Middleware):
    async def on_call_tool(self, context: MiddlewareContext, call_next):
        tool_name = context.message.name

        if tool_name in ["delete_all", "admin_config"]:
            raise ToolError("Access denied: requires admin privileges")

        return await call_next(context)
```

| Operation | Error Type |
|-----------|------------|
| Tool calls | `ToolError` |
| Resource reads | `ResourceError` |
| Prompt retrieval | `PromptError` |
| General requests | `McpError` |

Do not return error values or skip `call_next()` to indicate errors—raise exceptions for proper error propagation.

### Modifying Requests

Change the message before passing it down the chain.

```python
from fastmcp.server.middleware import Middleware, MiddlewareContext

class InputSanitizer(Middleware):
    async def on_call_tool(self, context: MiddlewareContext, call_next):
        if context.message.name == "search":
            # Normalize search query
            query = context.message.arguments.get("query", "")
            context.message.arguments["query"] = query.strip().lower()

        return await call_next(context)
```

### Modifying Responses

Transform results after the handler executes.

```python
from fastmcp.server.middleware import Middleware, MiddlewareContext

class ResponseEnricher(Middleware):
    async def on_call_tool(self, context: MiddlewareContext, call_next):
        result = await call_next(context)

        if context.message.name == "get_data" and result.structured_content:
            result.structured_content["processed_by"] = "enricher"

        return result
```

For more complex tool transformations, consider [Transforms](/servers/transforms/transforms) instead.

### Filtering Lists

List operations return FastMCP objects that you can filter before they reach the client. When filtering list results, also block execution in the corresponding operation hook to maintain consistency:

```python
from fastmcp.server.middleware import Middleware, MiddlewareContext
from fastmcp.exceptions import ToolError

class PrivateToolFilter(Middleware):
    async def on_list_tools(self, context: MiddlewareContext, call_next):
        tools = await call_next(context)
        return [tool for tool in tools if "private" not in tool.tags]

    async def on_call_tool(self, context: MiddlewareContext, call_next):
        if context.fastmcp_context:
            tool = await context.fastmcp_context.fastmcp.get_tool(context.message.name)
            if "private" in tool.tags:
                raise ToolError("Tool not found")

        return await call_next(context)
```

### Accessing Component Metadata

During execution hooks, component metadata (like tags) isn't directly available. Look up the component through the server:

```python
from fastmcp.server.middleware import Middleware, MiddlewareContext
from fastmcp.exceptions import ToolError

class TagBasedAuth(Middleware):
    async def on_call_tool(self, context: MiddlewareContext, call_next):
        if context.fastmcp_context:
            try:
                tool = await context.fastmcp_context.fastmcp.get_tool(context.message.name)

                if "requires-auth" in tool.tags:
                    # Check authentication here
                    pass

            except Exception:
                pass  # Let execution handle missing tools

        return await call_next(context)
```

The same pattern works for resources and prompts:

```python
resource = await context.fastmcp_context.fastmcp.get_resource(context.message.uri)
prompt = await context.fastmcp_context.fastmcp.get_prompt(context.message.name)
```

### Storing State

<VersionBadge version="2.11.0" />

Middleware can store state that tools access later through the FastMCP context.

```python
from fastmcp.server.middleware import Middleware, MiddlewareContext

class UserMiddleware(Middleware):
    async def on_request(self, context: MiddlewareContext, call_next):
        # Extract user from headers (HTTP transport)
        from fastmcp.server.dependencies import get_http_headers
        headers = get_http_headers() or {}
        user_id = headers.get("x-user-id", "anonymous")

        # Store for tools to access
        if context.fastmcp_context:
            context.fastmcp_context.set_state("user_id", user_id)

        return await call_next(context)
```

Tools retrieve the state:

```python
from fastmcp import FastMCP, Context

mcp = FastMCP("MyServer")

@mcp.tool
def get_user_data(ctx: Context) -> str:
    user_id = ctx.get_state("user_id")
    return f"Data for user: {user_id}"
```

See [Context State Management](/servers/context#state-management) for details.

### Constructor Parameters

Initialize middleware with configuration:

```python
from fastmcp.server.middleware import Middleware, MiddlewareContext

class ConfigurableMiddleware(Middleware):
    def __init__(self, api_key: str, rate_limit: int = 100):
        self.api_key = api_key
        self.rate_limit = rate_limit
        self.request_counts = {}

    async def on_request(self, context: MiddlewareContext, call_next):
        # Use self.api_key, self.rate_limit, etc.
        return await call_next(context)

mcp.add_middleware(ConfigurableMiddleware(
    api_key="secret",
    rate_limit=50
))
```

### Error Handling in Custom Middleware

Wrap `call_next()` to handle errors from downstream middleware and handlers.

```python
from fastmcp.server.middleware import Middleware, MiddlewareContext

class ErrorLogger(Middleware):
    async def on_request(self, context: MiddlewareContext, call_next):
        try:
            return await call_next(context)
        except Exception as e:
            print(f"Error in {context.method}: {type(e).__name__}: {e}")
            raise  # Re-raise to let error propagate
```

Catching and not re-raising suppresses the error entirely. Usually you want to log and re-raise.

### Audit and Event Records

A common need is to emit one structured record per tool call — for audit logs, policy decisions, or offline analysis — without wrapping individual tools or storing raw payloads. `on_call_tool` is the right place: it sees the call start, the resolved `ToolResult` (so it can detect empty or error results), the duration, and can deny the call before it runs.

Use [OpenTelemetry](/servers/telemetry) when the goal is to *export* spans to an observability backend. Reach for a record like this when you want a self-contained, redacted audit trail — or to drive runtime decisions from the result.

```python
import hashlib
import json
from datetime import datetime

from fastmcp.server.middleware import Middleware, MiddlewareContext
from fastmcp.exceptions import ToolError


def _schema_hash(arguments: dict | None) -> str:
    """Stable hash of the argument shape — detects schema drift without storing values."""
    shape = sorted(arguments or {})
    return hashlib.sha256(json.dumps(shape).encode()).hexdigest()[:12]


def _redact(arguments: dict | None) -> dict:
    """Keep keys, drop values — raw inputs stay out of the default path."""
    return {key: "<redacted>" for key in (arguments or {})}


def _call_id(context: MiddlewareContext) -> str | None:
    """Request id when an MCP session is active (see Session Availability above)."""
    ctx = context.fastmcp_context
    if ctx is not None and ctx.request_context:
        return ctx.request_id
    return None


class AuditMiddleware(Middleware):
    async def on_call_tool(self, context: MiddlewareContext, call_next):
        record = {
            "tool": context.message.name,
            "call_id": _call_id(context),
            "schema_hash": _schema_hash(context.message.arguments),
            "arguments": _redact(context.message.arguments),
            "received_at": context.timestamp.isoformat(),
        }

        try:
            result = await call_next(context)
        except Exception as exc:
            record["status"] = "failed"
            record["error"] = type(exc).__name__
            self.emit(record)
            raise

        empty = not result.content and result.structured_content is None
        record["status"] = "error" if result.is_error else "empty" if empty else "completed"
        now = datetime.now(context.timestamp.tzinfo)
        record["duration_ms"] = round((now - context.timestamp).total_seconds() * 1000, 2)
        self.emit(record)
        return result

    def emit(self, record: dict) -> None:
        # Swap in your sink: structured logger, queue, audit store, etc.
        print(json.dumps(record))
```

Each record carries the fields downstream tools tend to need — tool name, call id, input schema hash, redacted arguments, result class (`completed` / `empty` / `error` / `failed`), and duration — while raw inputs and outputs stay out by default.

To make this a policy layer, deny inside the same hook before calling `call_next`:

```python
async def on_call_tool(self, context: MiddlewareContext, call_next):
    if not self.is_allowed(context.message.name, context.message.arguments):
        self.emit({"tool": context.message.name, "status": "denied", "reason": "policy"})
        raise ToolError("Call blocked by policy")
    return await call_next(context)
```

### Complete Example

Authentication middleware checking API keys for specific tools:

```python
from fastmcp import FastMCP
from fastmcp.server.middleware import Middleware, MiddlewareContext
from fastmcp.server.dependencies import get_http_headers
from fastmcp.exceptions import ToolError

class ApiKeyAuth(Middleware):
    def __init__(self, valid_keys: set[str], protected_tools: set[str]):
        self.valid_keys = valid_keys
        self.protected_tools = protected_tools

    async def on_call_tool(self, context: MiddlewareContext, call_next):
        tool_name = context.message.name

        if tool_name not in self.protected_tools:
            return await call_next(context)

        headers = get_http_headers() or {}
        api_key = headers.get("x-api-key")

        if api_key not in self.valid_keys:
            raise ToolError(f"Invalid API key for protected tool: {tool_name}")

        return await call_next(context)

mcp = FastMCP("Secure Server")
mcp.add_middleware(ApiKeyAuth(
    valid_keys={"key-1", "key-2"},
    protected_tools={"delete_user", "admin_panel"}
))

@mcp.tool
def delete_user(user_id: str) -> str:
    return f"Deleted user {user_id}"

@mcp.tool
def get_user(user_id: str) -> str:
    return f"User {user_id}"  # Not protected
```