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release?v=1.5

Release 1.5.0

We’ve introduced a complete MCP Server SDK, enabling you to build production-ready MCP servers with routing, advanced logging, inspector integration, and multiple transport protocols.

Major Changes

Complete MCP Server SDK

Build powerful MCP servers with a comprehensive SDK that rivals FastMCP while providing unique capabilities for production deployments. Key Components:

MCPServer - Production-Ready Server Class

Built on top of FastMCP with significant enhancements for production use:
from mcp_use.server import MCPServer

server = MCPServer(
    name="my-awesome-server",
    version="1.0.0",
    instructions="A production-ready MCP server",
    debug=True,  # Enable development tools
    pretty_print_jsonrpc=True,  # Beautiful JSON-RPC logs
)

@server.tool()
def calculate(expression: str) -> float:
    """Evaluate a mathematical expression."""
    return eval(expression)

# Run with multiple transport options
server.run(
    transport="streamable-http",  # or "stdio", "sse"
    host="0.0.0.0",
    port=8000,
    reload=True  # Auto-reload on code changes
)
Features:
  • Multiple transport protocols: stdio, streamable-http, SSE
  • Integrated development tools and inspector
  • Advanced logging with customizable formats
  • Production-ready with signal handling
  • FastMCP compatibility layer

MCPRouter - Modular Server Organization

Organize your MCP server into reusable modules, similar to FastAPI’s APIRouter:
from mcp_use.server import MCPServer, MCPRouter

# routes/math.py
math_router = MCPRouter()

@math_router.tool()
def add(a: float, b: float) -> float:
    """Add two numbers."""
    return a + b

@math_router.tool()
def multiply(a: float, b: float) -> float:
    """Multiply two numbers."""
    return a * b

# routes/weather.py
weather_router = MCPRouter()

@weather_router.resource(uri="weather://current/{city}")
def get_weather(city: str) -> str:
    """Get current weather for a city."""
    return f"Weather data for {city}"

# main.py
server = MCPServer(name="multi-module-server")
server.include_router(math_router, prefix="math")  # Tools: math_add, math_multiply
server.include_router(weather_router, prefix="weather")
server.include_router(admin_router, enabled=False)  # Conditionally disable routers
Features:
  • Clean separation of concerns
  • Reusable modules across projects
  • Optional prefixing for namespacing
  • Conditional router enabling/disabling
  • Support for tools, resources, and prompts

Enhanced Context with Advanced Capabilities

Extended context object with powerful server-side features:
from mcp_use.server import MCPServer, Context

server = MCPServer(name="context-demo")

@server.tool()
async def smart_search(query: str, ctx: Context) -> str:
    """Intelligent search with LLM refinement."""
    # Sampling: Request LLM assistance from the client
    result = await ctx.sample(
        messages=f"Refine this search query: {query}",
        max_tokens=100,
        temperature=0.7,
        model_preferences={"hints": [{"name": "claude-3-5-sonnet"}]}
    )
    refined_query = result.content.text
    
    # Elicitation: Get structured input from user
    from dataclasses import dataclass
    
    @dataclass
    class SearchFilters:
        date_range: str
        categories: list[str]
        max_results: int = 10
    
    filters = await ctx.elicit(
        message="Please specify search filters",
        schema=SearchFilters  # Supports both Pydantic and dataclasses
    )
    
    # Perform search with refined query and filters...
    return f"Results for '{refined_query}' with filters: {filters.data}"

@server.tool()
async def add_new_tool(name: str, ctx: Context) -> str:
    """Dynamically register a new tool."""
    # Notify clients about tool list changes
    await ctx.send_tool_list_changed()
    return f"Added tool: {name}"

@server.tool()
async def get_request_info(ctx: Context) -> dict:
    """Access HTTP request details."""
    request = ctx.get_http_request()
    if request:
        return {
            "method": request.method,
            "url": str(request.url),
            "headers": dict(request.headers)
        }
    return {"transport": "stdio"}
Context Features:
  • sample(): Client-side LLM sampling with model preferences
  • elicit(): Structured user input with Pydantic or dataclass schemas
  • send_tool_list_changed(): Dynamic tool registration notifications
  • send_resource_list_changed(): Resource update notifications
  • send_prompt_list_changed(): Prompt update notifications
  • get_http_request(): Access underlying HTTP request (streamable-http only)

Advanced Logging System

Production-grade logging with beautiful formatting and debugging tools: Features:
  • Customizable log formats with color-coded output
  • JSON-RPC request/response logging
  • Session ID tracking across requests
  • Request/response size monitoring
  • Configurable debug levels (0=production, 1=debug, 2=verbose)
  • Middleware-based architecture for extensibility
Debug Levels:
# Production: Clean logs only
DEBUG=0 python server.py

# Debug: Clean logs + dev routes (/docs, /inspector, /openmcp.json)
DEBUG=1 python server.py

# Verbose: Everything + JSON-RPC logging with pretty printing
DEBUG=2 python server.py

Built-in Development Tools

Inspector Integration:
  • Auto-populated inspector at /inspector
  • Real-time tool testing
  • Request/response inspection
  • Session management
Documentation UI:
  • Auto-generated docs at /docs
  • Interactive API explorer
  • Tool/resource/prompt documentation
OpenMCP Configuration:
  • Standard OpenMCP config at /openmcp.json
  • Easy integration with MCP clients
  • Auto-discovery support

Multiple Transport Protocols

# Stdio - Traditional MCP transport
server.run(transport="stdio")

# Streamable HTTP - Recommended for production
server.run(
    transport="streamable-http",
    host="0.0.0.0",
    port=8000
)

# SSE - Server-Sent Events (deprecated, use streamable-http)
server.run(
    transport="sse",
    host="127.0.0.1",
    port=8000
)
Transport Comparison:
  • stdio: Best for local CLI tools and desktop apps
  • streamable-http: Recommended for web services and cloud deployments
  • sse: Legacy support (deprecated in favor of streamable-http)

FastMCP Migration Path

Seamless migration from FastMCP with compatibility exports:
# Old FastMCP code
from fastmcp import FastMCP

server = FastMCP(name="my-server")

# New mcp-use code - drop-in replacement
from mcp_use.server import FastMCP  # Compatibility alias

server = FastMCP(name="my-server")  # Works identically

# Or use enhanced MCPServer for new features
from mcp_use.server import MCPServer

server = MCPServer(name="my-server")  # Recommended
See FastMCP compatibility guide for migration details.

Enhancements

Middleware Parameter Mutation

Middleware can now modify request parameters, with changes properly propagated:
from mcp_use.client import MCPClient, Middleware, MiddlewareContext

class ParameterEnrichmentMiddleware(Middleware):
    async def process_request(self, context: MiddlewareContext):
        # Middleware can now modify context.params
        if context.request_type == "call_tool":
            # Add/modify parameters
            context.params["enriched"] = True
            context.params["timestamp"] = time.time()
        
        # Changes are automatically propagated to the tool call
        return await context.next()

client = MCPClient(
    config={"mcpServers": {...}},
    middleware=[ParameterEnrichmentMiddleware()]
)
Changes:
  • Middleware parameter modifications are now preserved
  • context.params can be mutated and changes propagate
  • Improved middleware documentation with examples
See PR #522 for details.

Enhanced Sampling & Elicitation

Server-side support for advanced MCP protocols: Sampling:
@server.tool()
async def intelligent_tool(query: str, ctx: Context) -> str:
    # Request LLM assistance from the client
    response = await ctx.sample(
        messages=[
            "You are a helpful assistant",
            {"role": "user", "content": query}
        ],
        max_tokens=500,
        temperature=0.8,
        model_preferences={"hints": [{"name": "claude-3-5-sonnet"}]}
    )
    return response.content.text
Elicitation:
@server.tool()
async def structured_input(ctx: Context) -> dict:
    # Get structured user input
    result = await ctx.elicit(
        message="Please provide task details",
        schema=TaskSchema
    )
    
    if result.action == "accept":
        return result.data.model_dump()
    else:
        return {"cancelled": True}

Tool Enable/Disable Support

Dynamic tool management during runtime:
@server.tool()
async def toggle_feature(feature: str, enabled: bool, ctx: Context) -> str:
    # Enable or disable tools dynamically
    if enabled:
        # Register new tool
        pass
    else:
        # Unregister tool
        pass
    
    # Notify clients
    await ctx.send_tool_list_changed()
    return f"Feature {feature} {'enabled' if enabled else 'disabled'}"

Code Quality

Type Checking with Ty

Introduced ty as the official type checker for better type safety:
# Run type checking
ty check

# Pre-commit integration
git commit  # Automatically runs ty on staged files
Benefits:
  • Strict type checking for improved code quality
  • Pre-commit integration with prek
  • Configured to ignore certain patterns for flexibility

Pre-commit Hooks with Prek

Standardized pre-commit workflow with prek:
# Install pre-commit hooks
prek install

# Run on all files
prek run --all-files
Hooks:
  • Type checking with ty
  • Code formatting with ruff
  • Import sorting
  • Trailing whitespace removal

Refactored Test Suite

Complete test reorganization for better maintainability: Structure:
tests/
├── client/           # Client-side tests
│   ├── primitives/   # MCP primitives (tools, resources, prompts)
│   ├── transports/   # Transport protocols
│   └── others/       # Other client features
└── server/           # Server-side integration tests (future)
Improvements:
  • Tests now use MCPServer instead of external servers
  • Removed dependency on FastMCP test servers
  • Better test isolation
  • Clearer test organization

Ruff Configuration

Moved Ruff configuration from separate file to pyproject.toml:
[tool.ruff]
line-length = 120
target-version = "py311"

[tool.ruff.lint]
select = ["E", "F", "I", "W", "B", "UP"]
Benefits:
  • Single configuration file
  • Consistent with Python ecosystem standards
  • Easier project setup

Documentation

New Server Documentation

Comprehensive documentation for the new server SDK:

Updated Examples

New example servers showcasing features:
  • context_example.py - Context features demo
  • fastmcp_example.py - FastMCP compatibility
  • fastmcp2_example.py - Advanced FastMCP patterns
  • fmcp_use_server_example.py - Full-featured server

API Reference

Auto-generated API documentation for all new modules:
  • mcp_use.server.server - MCPServer class
  • mcp_use.server.router - MCPRouter class
  • mcp_use.server.context - Enhanced Context
  • mcp_use.server.logging - Logging components
  • mcp_use.server.runner - Server runner
  • mcp_use.server.types - Type definitions
  • mcp_use.server.utils - Utility functions

Breaking Changes

None - all changes are backward compatible. Existing client code continues to work without modifications.

Migration Guide

Starting a New Server

from mcp_use.server import MCPServer

server = MCPServer(
    name="my-server",
    version="1.0.0",
    debug=True  # Enable dev tools during development
)

@server.tool()
def my_tool(arg: str) -> str:
    return f"Result: {arg}"

if __name__ == "__main__":
    server.run(transport="streamable-http", port=8000)

Migrating from FastMCP

Replace imports and enjoy enhanced features:
# Before
from fastmcp import FastMCP
server = FastMCP(name="my-server")

# After - Option 1: Compatibility mode
from mcp_use.server import FastMCP
server = FastMCP(name="my-server")

# After - Option 2: Full features (recommended)
from mcp_use.server import MCPServer
server = MCPServer(name="my-server", debug=True)

Organizing with Routers

Split large servers into modules:
# routes/database.py
from mcp_use.server import MCPRouter

db_router = MCPRouter()

@db_router.tool()
def query(sql: str) -> list:
    return []

# main.py
from mcp_use.server import MCPServer
from routes.database import db_router

server = MCPServer(name="my-server")
server.include_router(db_router, prefix="db")

Enabling Advanced Features

from mcp_use.server import MCPServer, Context

server = MCPServer(name="advanced-server")

@server.tool()
async def advanced_tool(query: str, ctx: Context) -> str:
    # Use sampling
    result = await ctx.sample(messages=query)
    
    # Send notifications
    await ctx.send_tool_list_changed()
    
    # Access HTTP request
    request = ctx.get_http_request()
    
    return result.content.text

Dependencies

Updated Requirements

mcp>=1.10.0  # Updated for latest MCP features
pydantic>=2.11.0  # Enhanced schema support

New Development Tools

[project.optional-dependencies]
dev = [
    "prek>=0.2.0",  # Pre-commit framework
    "ty>=0.0.1a7",  # Type checker
]

Contributors

Thank you to all contributors who made this release possible:
Contributors
@pietrozullo@vkrasnoselskikh@renvins@tonxxd

Statistics

  • Total Commits: 30+ (Python-specific)
  • Files Changed: 106
  • Lines Added: 5,818+
  • Lines Removed: 4,402+
  • New Modules: 15+
  • New Examples: 4
  • New Documentation Pages: 10+

For full changelog and commit history, see the commit log.