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docs/patterns/composition.mdx
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docs/patterns/composition.mdx
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---
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title: Server Composition
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sidebarTitle: Composition
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description: Combine multiple FastMCP servers into a single, larger application using mounting.
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icon: puzzle-piece
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---
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As your MCP applications grow, you might want to organize your tools, resources, and prompts into logical modules or reuse existing server components. FastMCP supports composition through the `server.mount()` method, allowing you to combine multiple `FastMCP` instances into a single, unified server.
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## Why Compose Servers?
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- **Modularity**: Break down large applications into smaller, focused servers (e.g., a `WeatherServer`, a `DatabaseServer`, a `CalendarServer`).
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- **Reusability**: Create common utility servers (e.g., a `TextProcessingServer`) and mount them wherever needed.
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- **Teamwork**: Different teams can work on separate FastMCP servers that are later combined.
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- **Organization**: Keep related functionality grouped together logically.
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## Mounting Subservers
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The `mount()` method attaches all components (tools, resources, templates, prompts) from one `FastMCP` instance (the *subserver*) onto another (the *main server*). A `prefix` is added to avoid naming conflicts.
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```python
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from fastmcp import FastMCP
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from typing import dict, list
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# --- Define Subservers ---
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# Weather Service
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weather_mcp = FastMCP(name="WeatherService")
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@weather_mcp.tool()
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def get_forecast(city: str) -> dict:
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"""Get weather forecast."""
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return {"city": city, "forecast": "Sunny"}
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@weather_mcp.resource("data://cities/supported")
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def list_supported_cities() -> list[str]:
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"""List cities with weather support."""
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return ["London", "Paris", "Tokyo"]
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# Calculator Service
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calc_mcp = FastMCP(name="CalculatorService")
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@calc_mcp.tool()
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def add(a: int, b: int) -> int:
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"""Add two numbers."""
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return a + b
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@calc_mcp.prompt()
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def explain_addition() -> str:
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"""Explain the concept of addition."""
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return "Addition is the process of combining two or more numbers."
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# --- Define Main Server ---
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main_mcp = FastMCP(name="MainApp")
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# --- Mount Subservers ---
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# Mount weather service with prefix "weather"
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main_mcp.mount("weather", weather_mcp)
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# Mount calculator service with prefix "calc"
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main_mcp.mount("calc", calc_mcp)
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# --- Now, main_mcp contains combined components ---
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# Tools:
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# - "weather_get_forecast"
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# - "calc_add"
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# Resources:
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# - "weather+data://cities/supported" (prefixed URI)
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# Prompts:
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# - "calc_explain_addition"
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if __name__ == "__main__":
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# Run the main server, which now includes components from both subservers
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main_mcp.run()
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```
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### How Mounting Works
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When you call `main_mcp.mount(prefix, subserver)`:
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1. **Tools**: All tools from `subserver` are added to `main_mcp`. Their names are automatically prefixed using the `prefix` and a default separator (`_`).
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- `subserver.tool(name="my_tool")` becomes `main_mcp.tool(name="{prefix}_my_tool")`.
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2. **Resources**: All resources from `subserver` are added. Their URIs are prefixed using the `prefix` and a default separator (`+`).
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- `subserver.resource(uri="data://info")` becomes `main_mcp.resource(uri="{prefix}+data://info")`.
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3. **Resource Templates**: All templates from `subserver` are added. Their URI *templates* are prefixed similarly to resources.
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- `subserver.resource(uri="data://{id}")` becomes `main_mcp.resource(uri="{prefix}+data://{id}")`.
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4. **Prompts**: All prompts from `subserver` are added, with names prefixed like tools.
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- `subserver.prompt(name="my_prompt")` becomes `main_mcp.prompt(name="{prefix}_my_prompt")`.
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5. **Lifespan Management**: If the `subserver` has a `lifespan` function defined, it will be automatically executed within the `main_mcp`'s lifespan context. This ensures that setup and teardown logic for the subserver runs correctly.
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### Customizing Separators
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You might prefer different separators for the prefixed names and URIs. You can customize these when calling `mount()`:
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```python
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main_mcp.mount(
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prefix="api",
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app=some_subserver,
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tool_separator="/", # Tool name becomes: "api/sub_tool_name"
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resource_separator=":", # Resource URI becomes: "api:data://sub_resource"
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prompt_separator="." # Prompt name becomes: "api.sub_prompt_name"
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)
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```
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<Warning>
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Be cautious when choosing separators. Some MCP clients (like Claude Desktop) might have restrictions on characters allowed in tool names (e.g., `/` might not be supported). The defaults (`_` for names, `+` for URIs) are generally safe.
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</Warning>
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## Example: Modular Application
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```python
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# modules/text_utils.py
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from fastmcp import FastMCP
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from typing import list
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text_mcp = FastMCP(name="TextUtilities")
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@text_mcp.tool()
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def count_words(text: str) -> int:
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"""Counts words in a text."""
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return len(text.split())
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@text_mcp.resource("resource://stopwords")
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def get_stopwords() -> list[str]:
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"""Return a list of common stopwords."""
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return ["the", "a", "is", "in"]
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# ------------------------------
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# modules/data_api.py
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from fastmcp import FastMCP
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import random
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from typing import dict
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data_mcp = FastMCP(name="DataAPI")
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@data_mcp.tool()
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def fetch_record(record_id: int) -> dict:
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"""Fetches a dummy data record."""
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return {"id": record_id, "value": random.random()}
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@data_mcp.resource("data://schema/{table}")
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def get_table_schema(table: str) -> dict:
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"""Provides a dummy schema for a table."""
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return {"table": table, "columns": ["id", "value"]}
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# ------------------------------
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# main_app.py
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from fastmcp import FastMCP
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from modules.text_utils import text_mcp # Import server instances
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from modules.data_api import data_mcp
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app = FastMCP(name="MainApplication")
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# Mount the utility servers
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app.mount("text", text_mcp)
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app.mount("data", data_mcp)
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@app.tool()
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def process_and_analyze(record_id: int) -> str:
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"""Fetches a record and analyzes its string representation."""
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# In a real application, you'd use proper methods to interact between
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# mounted tools rather than accessing internal managers
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# Get record data
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record = {"id": record_id, "value": random.random()}
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# Count words in the record string representation
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word_count = len(str(record).split())
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return (
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f"Record {record_id} has {word_count} words in its string "
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f"representation."
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)
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if __name__ == "__main__":
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app.run()
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```
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Now, running `main_app.py` starts a server that exposes:
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- `text_count_words`
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- `data_fetch_record`
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- `process_and_analyze`
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- `text+resource://stopwords`
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- `data+data://schema/{table}` (template)
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This pattern promotes code organization and reuse within your FastMCP projects.
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