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Add schema validation to lowlevel server (#1005)

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bhosmer-ant
2025-06-25 09:23:49 -04:00
committed by GitHub
parent 0b11bdb629
commit c8bbfc034d
8 changed files with 1155 additions and 8 deletions
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README.md
+61
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@@ -829,6 +829,67 @@ if __name__ == "__main__":
Caution: The `mcp run` and `mcp dev` tool doesn't support low-level server.
#### Structured Output Support
The low-level server supports structured output for tools, allowing you to return both human-readable content and machine-readable structured data. Tools can define an `outputSchema` to validate their structured output:
```python
from types import Any
import mcp.types as types
from mcp.server.lowlevel import Server
server = Server("example-server")
@server.list_tools()
async def list_tools() -> list[types.Tool]:
return [
types.Tool(
name="calculate",
description="Perform mathematical calculations",
inputSchema={
"type": "object",
"properties": {
"expression": {"type": "string", "description": "Math expression"}
},
"required": ["expression"],
},
outputSchema={
"type": "object",
"properties": {
"result": {"type": "number"},
"expression": {"type": "string"},
},
"required": ["result", "expression"],
},
)
]
@server.call_tool()
async def call_tool(name: str, arguments: dict[str, Any]) -> dict[str, Any]:
if name == "calculate":
expression = arguments["expression"]
try:
result = eval(expression) # Use a safe math parser
structured = {"result": result, "expression": expression}
# low-level server will validate structured output against the tool's
# output schema, and automatically serialize it into a TextContent block
# for backwards compatibility with pre-2025-06-18 clients.
return structured
except Exception as e:
raise ValueError(f"Calculation error: {str(e)}")
```
Tools can return data in three ways:
1. **Content only**: Return a list of content blocks (default behavior before spec revision 2025-06-18)
2. **Structured data only**: Return a dictionary that will be serialized to JSON (Introduced in spec revision 2025-06-18)
3. **Both**: Return a tuple of (content, structured_data) preferred option to use for backwards compatibility
When an `outputSchema` is defined, the server automatically validates the structured output against the schema. This ensures type safety and helps catch errors early.
### Writing MCP Clients
The SDK provides a high-level client interface for connecting to MCP servers using various [transports](https://modelcontextprotocol.io/specification/2025-03-26/basic/transports):
examples/servers/structured_output_lowlevel.py
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@@ -0,0 +1,98 @@
#!/usr/bin/env python3
"""
Example low-level MCP server demonstrating structured output support.
This example shows how to use the low-level server API to return
structured data from tools, with automatic validation against output
schemas.
"""
import asyncio
from datetime import datetime
from typing import Any
import mcp.server.stdio
import mcp.types as types
from mcp.server.lowlevel import NotificationOptions, Server
from mcp.server.models import InitializationOptions
# Create low-level server instance
server = Server("structured-output-lowlevel-example")
@server.list_tools()
async def list_tools() -> list[types.Tool]:
"""List available tools with their schemas."""
return [
types.Tool(
name="get_weather",
description="Get weather information (simulated)",
inputSchema={
"type": "object",
"properties": {"city": {"type": "string", "description": "City name"}},
"required": ["city"],
},
outputSchema={
"type": "object",
"properties": {
"temperature": {"type": "number"},
"conditions": {"type": "string"},
"humidity": {"type": "integer", "minimum": 0, "maximum": 100},
"wind_speed": {"type": "number"},
"timestamp": {"type": "string", "format": "date-time"},
},
"required": ["temperature", "conditions", "humidity", "wind_speed", "timestamp"],
},
),
]
@server.call_tool()
async def call_tool(name: str, arguments: dict[str, Any]) -> Any:
"""
Handle tool call with structured output.
"""
if name == "get_weather":
# city = arguments["city"] # Would be used with real weather API
# Simulate weather data (in production, call a real weather API)
import random
weather_conditions = ["sunny", "cloudy", "rainy", "partly cloudy", "foggy"]
weather_data = {
"temperature": round(random.uniform(0, 35), 1),
"conditions": random.choice(weather_conditions),
"humidity": random.randint(30, 90),
"wind_speed": round(random.uniform(0, 30), 1),
"timestamp": datetime.now().isoformat(),
}
# Return structured data only
# The low-level server will serialize this to JSON content automatically
return weather_data
else:
raise ValueError(f"Unknown tool: {name}")
async def run():
"""Run the low-level server using stdio transport."""
async with mcp.server.stdio.stdio_server() as (read_stream, write_stream):
await server.run(
read_stream,
write_stream,
InitializationOptions(
server_name="structured-output-lowlevel-example",
server_version="0.1.0",
capabilities=server.get_capabilities(
notification_options=NotificationOptions(),
experimental_capabilities={},
),
),
)
if __name__ == "__main__":
asyncio.run(run())
pyproject.toml
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@@ -31,6 +31,7 @@ dependencies = [
"sse-starlette>=1.6.1",
"pydantic-settings>=2.5.2",
"uvicorn>=0.23.1; sys_platform != 'emscripten'",
"jsonschema==4.20.0",
]
[project.optional-dependencies]
src/mcp/server/lowlevel/server.py
+103 -8
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@@ -68,13 +68,15 @@ messages from the client.
from __future__ import annotations as _annotations
import contextvars
import json
import logging
import warnings
from collections.abc import AsyncIterator, Awaitable, Callable, Iterable
from contextlib import AbstractAsyncContextManager, AsyncExitStack, asynccontextmanager
from typing import Any, Generic
from typing import Any, Generic, TypeAlias, cast
import anyio
import jsonschema
from anyio.streams.memory import MemoryObjectReceiveStream, MemoryObjectSendStream
from pydantic import AnyUrl
from typing_extensions import TypeVar
@@ -94,6 +96,11 @@ logger = logging.getLogger(__name__)
LifespanResultT = TypeVar("LifespanResultT")
RequestT = TypeVar("RequestT", default=Any)
# type aliases for tool call results
StructuredContent: TypeAlias = dict[str, Any]
UnstructuredContent: TypeAlias = Iterable[types.ContentBlock]
CombinationContent: TypeAlias = tuple[UnstructuredContent, StructuredContent]
# This will be properly typed in each Server instance's context
request_ctx: contextvars.ContextVar[RequestContext[ServerSession, Any, Any]] = contextvars.ContextVar("request_ctx")
@@ -143,6 +150,7 @@ class Server(Generic[LifespanResultT, RequestT]):
}
self.notification_handlers: dict[type, Callable[..., Awaitable[None]]] = {}
self.notification_options = NotificationOptions()
self._tool_cache: dict[str, types.Tool] = {}
logger.debug("Initializing server %r", name)
def create_initialization_options(
@@ -373,6 +381,10 @@ class Server(Generic[LifespanResultT, RequestT]):
async def handler(_: Any):
tools = await func()
# Refresh the tool cache
self._tool_cache.clear()
for tool in tools:
self._tool_cache[tool.name] = tool
return types.ServerResult(types.ListToolsResult(tools=tools))
self.request_handlers[types.ListToolsRequest] = handler
@@ -380,26 +392,109 @@ class Server(Generic[LifespanResultT, RequestT]):
return decorator
def call_tool(self):
def _make_error_result(self, error_message: str) -> types.ServerResult:
"""Create a ServerResult with an error CallToolResult."""
return types.ServerResult(
types.CallToolResult(
content=[types.TextContent(type="text", text=error_message)],
isError=True,
)
)
async def _get_cached_tool_definition(self, tool_name: str) -> types.Tool | None:
"""Get tool definition from cache, refreshing if necessary.
Returns the Tool object if found, None otherwise.
"""
if tool_name not in self._tool_cache:
if types.ListToolsRequest in self.request_handlers:
logger.debug("Tool cache miss for %s, refreshing cache", tool_name)
await self.request_handlers[types.ListToolsRequest](None)
tool = self._tool_cache.get(tool_name)
if tool is None:
logger.warning("Tool '%s' not listed, no validation will be performed", tool_name)
return tool
def call_tool(self, *, validate_input: bool = True):
"""Register a tool call handler.
Args:
validate_input: If True, validates input against inputSchema. Default is True.
The handler validates input against inputSchema (if validate_input=True), calls the tool function,
and builds a CallToolResult with the results:
- Unstructured content (iterable of ContentBlock): returned in content
- Structured content (dict): returned in structuredContent, serialized JSON text returned in content
- Both: returned in content and structuredContent
If outputSchema is defined, validates structuredContent or errors if missing.
"""
def decorator(
func: Callable[
...,
Awaitable[Iterable[types.ContentBlock]],
Awaitable[UnstructuredContent | StructuredContent | CombinationContent],
],
):
logger.debug("Registering handler for CallToolRequest")
async def handler(req: types.CallToolRequest):
try:
results = await func(req.params.name, (req.params.arguments or {}))
return types.ServerResult(types.CallToolResult(content=list(results), isError=False))
except Exception as e:
tool_name = req.params.name
arguments = req.params.arguments or {}
tool = await self._get_cached_tool_definition(tool_name)
# input validation
if validate_input and tool:
try:
jsonschema.validate(instance=arguments, schema=tool.inputSchema)
except jsonschema.ValidationError as e:
return self._make_error_result(f"Input validation error: {e.message}")
# tool call
results = await func(tool_name, arguments)
# output normalization
unstructured_content: UnstructuredContent
maybe_structured_content: StructuredContent | None
if isinstance(results, tuple) and len(results) == 2:
# tool returned both structured and unstructured content
unstructured_content, maybe_structured_content = cast(CombinationContent, results)
elif isinstance(results, dict):
# tool returned structured content only
maybe_structured_content = cast(StructuredContent, results)
unstructured_content = [types.TextContent(type="text", text=json.dumps(results, indent=2))]
elif hasattr(results, "__iter__"):
# tool returned unstructured content only
unstructured_content = cast(UnstructuredContent, results)
maybe_structured_content = None
else:
return self._make_error_result(f"Unexpected return type from tool: {type(results).__name__}")
# output validation
if tool and tool.outputSchema is not None:
if maybe_structured_content is None:
return self._make_error_result(
"Output validation error: outputSchema defined but no structured output returned"
)
else:
try:
jsonschema.validate(instance=maybe_structured_content, schema=tool.outputSchema)
except jsonschema.ValidationError as e:
return self._make_error_result(f"Output validation error: {e.message}")
# result
return types.ServerResult(
types.CallToolResult(
content=[types.TextContent(type="text", text=str(e))],
isError=True,
content=list(unstructured_content),
structuredContent=maybe_structured_content,
isError=False,
)
)
except Exception as e:
return self._make_error_result(str(e))
self.request_handlers[types.CallToolRequest] = handler
return func
src/mcp/types.py
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@@ -839,6 +839,11 @@ class Tool(BaseMetadata):
"""A human-readable description of the tool."""
inputSchema: dict[str, Any]
"""A JSON Schema object defining the expected parameters for the tool."""
outputSchema: dict[str, Any] | None = None
"""
An optional JSON Schema object defining the structure of the tool's output
returned in the structuredContent field of a CallToolResult.
"""
annotations: ToolAnnotations | None = None
"""Optional additional tool information."""
meta: dict[str, Any] | None = Field(alias="_meta", default=None)
@@ -874,6 +879,8 @@ class CallToolResult(Result):
"""The server's response to a tool call."""
content: list[ContentBlock]
structuredContent: dict[str, Any] | None = None
"""An optional JSON object that represents the structured result of the tool call."""
isError: bool = False
tests/server/test_lowlevel_input_validation.py
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@@ -0,0 +1,310 @@
"""Test input schema validation for lowlevel server."""
import logging
from collections.abc import Awaitable, Callable
from typing import Any
import anyio
import pytest
from mcp.client.session import ClientSession
from mcp.server import Server
from mcp.server.lowlevel import NotificationOptions
from mcp.server.models import InitializationOptions
from mcp.server.session import ServerSession
from mcp.shared.message import SessionMessage
from mcp.shared.session import RequestResponder
from mcp.types import CallToolResult, ClientResult, ServerNotification, ServerRequest, TextContent, Tool
async def run_tool_test(
tools: list[Tool],
call_tool_handler: Callable[[str, dict[str, Any]], Awaitable[list[TextContent]]],
test_callback: Callable[[ClientSession], Awaitable[CallToolResult]],
) -> CallToolResult:
"""Helper to run a tool test with minimal boilerplate.
Args:
tools: List of tools to register
call_tool_handler: Handler function for tool calls
test_callback: Async function that performs the test using the client session
Returns:
The result of the tool call
"""
server = Server("test")
@server.list_tools()
async def list_tools():
return tools
@server.call_tool()
async def call_tool(name: str, arguments: dict[str, Any]) -> list[TextContent]:
return await call_tool_handler(name, arguments)
server_to_client_send, server_to_client_receive = anyio.create_memory_object_stream[SessionMessage](10)
client_to_server_send, client_to_server_receive = anyio.create_memory_object_stream[SessionMessage](10)
# Message handler for client
async def message_handler(
message: RequestResponder[ServerRequest, ClientResult] | ServerNotification | Exception,
) -> None:
if isinstance(message, Exception):
raise message
# Server task
async def run_server():
async with ServerSession(
client_to_server_receive,
server_to_client_send,
InitializationOptions(
server_name="test-server",
server_version="1.0.0",
capabilities=server.get_capabilities(
notification_options=NotificationOptions(),
experimental_capabilities={},
),
),
) as server_session:
async with anyio.create_task_group() as tg:
async def handle_messages():
async for message in server_session.incoming_messages:
await server._handle_message(message, server_session, {}, False)
tg.start_soon(handle_messages)
await anyio.sleep_forever()
# Run the test
async with anyio.create_task_group() as tg:
tg.start_soon(run_server)
async with ClientSession(
server_to_client_receive,
client_to_server_send,
message_handler=message_handler,
) as client_session:
# Initialize the session
await client_session.initialize()
# Run the test callback
result = await test_callback(client_session)
# Cancel the server task
tg.cancel_scope.cancel()
return result
def create_add_tool() -> Tool:
"""Create a standard 'add' tool for testing."""
return Tool(
name="add",
description="Add two numbers",
inputSchema={
"type": "object",
"properties": {
"a": {"type": "number"},
"b": {"type": "number"},
},
"required": ["a", "b"],
"additionalProperties": False,
},
)
@pytest.mark.anyio
async def test_valid_tool_call():
"""Test that valid arguments pass validation."""
async def call_tool_handler(name: str, arguments: dict[str, Any]) -> list[TextContent]:
if name == "add":
result = arguments["a"] + arguments["b"]
return [TextContent(type="text", text=f"Result: {result}")]
else:
raise ValueError(f"Unknown tool: {name}")
async def test_callback(client_session: ClientSession) -> CallToolResult:
return await client_session.call_tool("add", {"a": 5, "b": 3})
result = await run_tool_test([create_add_tool()], call_tool_handler, test_callback)
# Verify results
assert result is not None
assert not result.isError
assert len(result.content) == 1
assert result.content[0].type == "text"
assert isinstance(result.content[0], TextContent)
assert result.content[0].text == "Result: 8"
@pytest.mark.anyio
async def test_invalid_tool_call_missing_required():
"""Test that missing required arguments fail validation."""
async def call_tool_handler(name: str, arguments: dict[str, Any]) -> list[TextContent]:
# This should not be reached due to validation
raise RuntimeError("Should not reach here")
async def test_callback(client_session: ClientSession) -> CallToolResult:
return await client_session.call_tool("add", {"a": 5}) # missing 'b'
result = await run_tool_test([create_add_tool()], call_tool_handler, test_callback)
# Verify results
assert result is not None
assert result.isError
assert len(result.content) == 1
assert result.content[0].type == "text"
assert isinstance(result.content[0], TextContent)
assert "Input validation error" in result.content[0].text
assert "'b' is a required property" in result.content[0].text
@pytest.mark.anyio
async def test_invalid_tool_call_wrong_type():
"""Test that wrong argument types fail validation."""
async def call_tool_handler(name: str, arguments: dict[str, Any]) -> list[TextContent]:
# This should not be reached due to validation
raise RuntimeError("Should not reach here")
async def test_callback(client_session: ClientSession) -> CallToolResult:
return await client_session.call_tool("add", {"a": "five", "b": 3}) # 'a' should be number
result = await run_tool_test([create_add_tool()], call_tool_handler, test_callback)
# Verify results
assert result is not None
assert result.isError
assert len(result.content) == 1
assert result.content[0].type == "text"
assert isinstance(result.content[0], TextContent)
assert "Input validation error" in result.content[0].text
assert "'five' is not of type 'number'" in result.content[0].text
@pytest.mark.anyio
async def test_cache_refresh_on_missing_tool():
"""Test that tool cache is refreshed when tool is not found."""
tools = [
Tool(
name="multiply",
description="Multiply two numbers",
inputSchema={
"type": "object",
"properties": {
"x": {"type": "number"},
"y": {"type": "number"},
},
"required": ["x", "y"],
},
)
]
async def call_tool_handler(name: str, arguments: dict[str, Any]) -> list[TextContent]:
if name == "multiply":
result = arguments["x"] * arguments["y"]
return [TextContent(type="text", text=f"Result: {result}")]
else:
raise ValueError(f"Unknown tool: {name}")
async def test_callback(client_session: ClientSession) -> CallToolResult:
# Call tool without first listing tools (cache should be empty)
# The cache should be refreshed automatically
return await client_session.call_tool("multiply", {"x": 10, "y": 20})
result = await run_tool_test(tools, call_tool_handler, test_callback)
# Verify results - should work because cache will be refreshed
assert result is not None
assert not result.isError
assert len(result.content) == 1
assert result.content[0].type == "text"
assert isinstance(result.content[0], TextContent)
assert result.content[0].text == "Result: 200"
@pytest.mark.anyio
async def test_enum_constraint_validation():
"""Test that enum constraints are validated."""
tools = [
Tool(
name="greet",
description="Greet someone",
inputSchema={
"type": "object",
"properties": {
"name": {"type": "string"},
"title": {"type": "string", "enum": ["Mr", "Ms", "Dr"]},
},
"required": ["name"],
},
)
]
async def call_tool_handler(name: str, arguments: dict[str, Any]) -> list[TextContent]:
# This should not be reached due to validation failure
raise RuntimeError("Should not reach here")
async def test_callback(client_session: ClientSession) -> CallToolResult:
return await client_session.call_tool("greet", {"name": "Smith", "title": "Prof"}) # Invalid title
result = await run_tool_test(tools, call_tool_handler, test_callback)
# Verify results
assert result is not None
assert result.isError
assert len(result.content) == 1
assert result.content[0].type == "text"
assert isinstance(result.content[0], TextContent)
assert "Input validation error" in result.content[0].text
assert "'Prof' is not one of" in result.content[0].text
@pytest.mark.anyio
async def test_tool_not_in_list_logs_warning(caplog):
"""Test that calling a tool not in list_tools logs a warning and skips validation."""
tools = [
Tool(
name="add",
description="Add two numbers",
inputSchema={
"type": "object",
"properties": {
"a": {"type": "number"},
"b": {"type": "number"},
},
"required": ["a", "b"],
},
)
]
async def call_tool_handler(name: str, arguments: dict[str, Any]) -> list[TextContent]:
# This should be reached since validation is skipped for unknown tools
if name == "unknown_tool":
# Even with invalid arguments, this should execute since validation is skipped
return [TextContent(type="text", text="Unknown tool executed without validation")]
else:
raise ValueError(f"Unknown tool: {name}")
async def test_callback(client_session: ClientSession) -> CallToolResult:
# Call a tool that's not in the list with invalid arguments
# This should trigger the warning about validation not being performed
return await client_session.call_tool("unknown_tool", {"invalid": "args"})
with caplog.at_level(logging.WARNING):
result = await run_tool_test(tools, call_tool_handler, test_callback)
# Verify results - should succeed because validation is skipped for unknown tools
assert result is not None
assert not result.isError
assert len(result.content) == 1
assert result.content[0].type == "text"
assert isinstance(result.content[0], TextContent)
assert result.content[0].text == "Unknown tool executed without validation"
# Verify warning was logged
assert any(
"Tool 'unknown_tool' not listed, no validation will be performed" in record.message for record in caplog.records
)
tests/server/test_lowlevel_output_validation.py
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@@ -0,0 +1,433 @@
"""Test output schema validation for lowlevel server."""
import json
from collections.abc import Awaitable, Callable
from typing import Any
import anyio
import pytest
from mcp.client.session import ClientSession
from mcp.server import Server
from mcp.server.lowlevel import NotificationOptions
from mcp.server.models import InitializationOptions
from mcp.server.session import ServerSession
from mcp.shared.message import SessionMessage
from mcp.shared.session import RequestResponder
from mcp.types import CallToolResult, ClientResult, ServerNotification, ServerRequest, TextContent, Tool
async def run_tool_test(
tools: list[Tool],
call_tool_handler: Callable[[str, dict[str, Any]], Awaitable[Any]],
test_callback: Callable[[ClientSession], Awaitable[CallToolResult]],
) -> CallToolResult:
"""Helper to run a tool test with minimal boilerplate.
Args:
tools: List of tools to register
call_tool_handler: Handler function for tool calls
test_callback: Async function that performs the test using the client session
Returns:
The result of the tool call
"""
server = Server("test")
@server.list_tools()
async def list_tools():
return tools
@server.call_tool()
async def call_tool(name: str, arguments: dict[str, Any]):
return await call_tool_handler(name, arguments)
server_to_client_send, server_to_client_receive = anyio.create_memory_object_stream[SessionMessage](10)
client_to_server_send, client_to_server_receive = anyio.create_memory_object_stream[SessionMessage](10)
# Message handler for client
async def message_handler(
message: RequestResponder[ServerRequest, ClientResult] | ServerNotification | Exception,
) -> None:
if isinstance(message, Exception):
raise message
# Server task
async def run_server():
async with ServerSession(
client_to_server_receive,
server_to_client_send,
InitializationOptions(
server_name="test-server",
server_version="1.0.0",
capabilities=server.get_capabilities(
notification_options=NotificationOptions(),
experimental_capabilities={},
),
),
) as server_session:
async with anyio.create_task_group() as tg:
async def handle_messages():
async for message in server_session.incoming_messages:
await server._handle_message(message, server_session, {}, False)
tg.start_soon(handle_messages)
await anyio.sleep_forever()
# Run the test
async with anyio.create_task_group() as tg:
tg.start_soon(run_server)
async with ClientSession(
server_to_client_receive,
client_to_server_send,
message_handler=message_handler,
) as client_session:
# Initialize the session
await client_session.initialize()
# Run the test callback
result = await test_callback(client_session)
# Cancel the server task
tg.cancel_scope.cancel()
return result
@pytest.mark.anyio
async def test_content_only_without_output_schema():
"""Test returning content only when no outputSchema is defined."""
tools = [
Tool(
name="echo",
description="Echo a message",
inputSchema={
"type": "object",
"properties": {
"message": {"type": "string"},
},
"required": ["message"],
},
# No outputSchema defined
)
]
async def call_tool_handler(name: str, arguments: dict[str, Any]) -> list[TextContent]:
if name == "echo":
return [TextContent(type="text", text=f"Echo: {arguments['message']}")]
else:
raise ValueError(f"Unknown tool: {name}")
async def test_callback(client_session: ClientSession) -> CallToolResult:
return await client_session.call_tool("echo", {"message": "Hello"})
result = await run_tool_test(tools, call_tool_handler, test_callback)
# Verify results
assert result is not None
assert not result.isError
assert len(result.content) == 1
assert result.content[0].type == "text"
assert isinstance(result.content[0], TextContent)
assert result.content[0].text == "Echo: Hello"
assert result.structuredContent is None
@pytest.mark.anyio
async def test_dict_only_without_output_schema():
"""Test returning dict only when no outputSchema is defined."""
tools = [
Tool(
name="get_info",
description="Get structured information",
inputSchema={
"type": "object",
"properties": {},
},
# No outputSchema defined
)
]
async def call_tool_handler(name: str, arguments: dict[str, Any]) -> dict[str, Any]:
if name == "get_info":
return {"status": "ok", "data": {"value": 42}}
else:
raise ValueError(f"Unknown tool: {name}")
async def test_callback(client_session: ClientSession) -> CallToolResult:
return await client_session.call_tool("get_info", {})
result = await run_tool_test(tools, call_tool_handler, test_callback)
# Verify results
assert result is not None
assert not result.isError
assert len(result.content) == 1
assert result.content[0].type == "text"
assert isinstance(result.content[0], TextContent)
# Check that the content is the JSON serialization
assert json.loads(result.content[0].text) == {"status": "ok", "data": {"value": 42}}
assert result.structuredContent == {"status": "ok", "data": {"value": 42}}
@pytest.mark.anyio
async def test_both_content_and_dict_without_output_schema():
"""Test returning both content and dict when no outputSchema is defined."""
tools = [
Tool(
name="process",
description="Process data",
inputSchema={
"type": "object",
"properties": {},
},
# No outputSchema defined
)
]
async def call_tool_handler(name: str, arguments: dict[str, Any]) -> tuple[list[TextContent], dict[str, Any]]:
if name == "process":
content = [TextContent(type="text", text="Processing complete")]
data = {"result": "success", "count": 10}
return (content, data)
else:
raise ValueError(f"Unknown tool: {name}")
async def test_callback(client_session: ClientSession) -> CallToolResult:
return await client_session.call_tool("process", {})
result = await run_tool_test(tools, call_tool_handler, test_callback)
# Verify results
assert result is not None
assert not result.isError
assert len(result.content) == 1
assert result.content[0].type == "text"
assert isinstance(result.content[0], TextContent)
assert result.content[0].text == "Processing complete"
assert result.structuredContent == {"result": "success", "count": 10}
@pytest.mark.anyio
async def test_content_only_with_output_schema_error():
"""Test error when outputSchema is defined but only content is returned."""
tools = [
Tool(
name="structured_tool",
description="Tool expecting structured output",
inputSchema={
"type": "object",
"properties": {},
},
outputSchema={
"type": "object",
"properties": {
"result": {"type": "string"},
},
"required": ["result"],
},
)
]
async def call_tool_handler(name: str, arguments: dict[str, Any]) -> list[TextContent]:
# This returns only content, but outputSchema expects structured data
return [TextContent(type="text", text="This is not structured")]
async def test_callback(client_session: ClientSession) -> CallToolResult:
return await client_session.call_tool("structured_tool", {})
result = await run_tool_test(tools, call_tool_handler, test_callback)
# Verify error
assert result is not None
assert result.isError
assert len(result.content) == 1
assert result.content[0].type == "text"
assert isinstance(result.content[0], TextContent)
assert "Output validation error: outputSchema defined but no structured output returned" in result.content[0].text
@pytest.mark.anyio
async def test_valid_dict_with_output_schema():
"""Test valid dict output matching outputSchema."""
tools = [
Tool(
name="calc",
description="Calculate result",
inputSchema={
"type": "object",
"properties": {
"x": {"type": "number"},
"y": {"type": "number"},
},
"required": ["x", "y"],
},
outputSchema={
"type": "object",
"properties": {
"sum": {"type": "number"},
"product": {"type": "number"},
},
"required": ["sum", "product"],
},
)
]
async def call_tool_handler(name: str, arguments: dict[str, Any]) -> dict[str, Any]:
if name == "calc":
x = arguments["x"]
y = arguments["y"]
return {"sum": x + y, "product": x * y}
else:
raise ValueError(f"Unknown tool: {name}")
async def test_callback(client_session: ClientSession) -> CallToolResult:
return await client_session.call_tool("calc", {"x": 3, "y": 4})
result = await run_tool_test(tools, call_tool_handler, test_callback)
# Verify results
assert result is not None
assert not result.isError
assert len(result.content) == 1
assert result.content[0].type == "text"
# Check JSON serialization
assert json.loads(result.content[0].text) == {"sum": 7, "product": 12}
assert result.structuredContent == {"sum": 7, "product": 12}
@pytest.mark.anyio
async def test_invalid_dict_with_output_schema():
"""Test dict output that doesn't match outputSchema."""
tools = [
Tool(
name="user_info",
description="Get user information",
inputSchema={
"type": "object",
"properties": {},
},
outputSchema={
"type": "object",
"properties": {
"name": {"type": "string"},
"age": {"type": "integer"},
},
"required": ["name", "age"],
},
)
]
async def call_tool_handler(name: str, arguments: dict[str, Any]) -> dict[str, Any]:
if name == "user_info":
# Missing required 'age' field
return {"name": "Alice"}
else:
raise ValueError(f"Unknown tool: {name}")
async def test_callback(client_session: ClientSession) -> CallToolResult:
return await client_session.call_tool("user_info", {})
result = await run_tool_test(tools, call_tool_handler, test_callback)
# Verify error
assert result is not None
assert result.isError
assert len(result.content) == 1
assert result.content[0].type == "text"
assert isinstance(result.content[0], TextContent)
assert "Output validation error:" in result.content[0].text
assert "'age' is a required property" in result.content[0].text
@pytest.mark.anyio
async def test_both_content_and_valid_dict_with_output_schema():
"""Test returning both content and valid dict with outputSchema."""
tools = [
Tool(
name="analyze",
description="Analyze data",
inputSchema={
"type": "object",
"properties": {
"text": {"type": "string"},
},
"required": ["text"],
},
outputSchema={
"type": "object",
"properties": {
"sentiment": {"type": "string", "enum": ["positive", "negative", "neutral"]},
"confidence": {"type": "number", "minimum": 0, "maximum": 1},
},
"required": ["sentiment", "confidence"],
},
)
]
async def call_tool_handler(name: str, arguments: dict[str, Any]) -> tuple[list[TextContent], dict[str, Any]]:
if name == "analyze":
content = [TextContent(type="text", text=f"Analysis of: {arguments['text']}")]
data = {"sentiment": "positive", "confidence": 0.95}
return (content, data)
else:
raise ValueError(f"Unknown tool: {name}")
async def test_callback(client_session: ClientSession) -> CallToolResult:
return await client_session.call_tool("analyze", {"text": "Great job!"})
result = await run_tool_test(tools, call_tool_handler, test_callback)
# Verify results
assert result is not None
assert not result.isError
assert len(result.content) == 1
assert result.content[0].type == "text"
assert result.content[0].text == "Analysis of: Great job!"
assert result.structuredContent == {"sentiment": "positive", "confidence": 0.95}
@pytest.mark.anyio
async def test_output_schema_type_validation():
"""Test outputSchema validates types correctly."""
tools = [
Tool(
name="stats",
description="Get statistics",
inputSchema={
"type": "object",
"properties": {},
},
outputSchema={
"type": "object",
"properties": {
"count": {"type": "integer"},
"average": {"type": "number"},
"items": {"type": "array", "items": {"type": "string"}},
},
"required": ["count", "average", "items"],
},
)
]
async def call_tool_handler(name: str, arguments: dict[str, Any]) -> dict[str, Any]:
if name == "stats":
# Wrong type for 'count' - should be integer
return {"count": "five", "average": 2.5, "items": ["a", "b"]}
else:
raise ValueError(f"Unknown tool: {name}")
async def test_callback(client_session: ClientSession) -> CallToolResult:
return await client_session.call_tool("stats", {})
result = await run_tool_test(tools, call_tool_handler, test_callback)
# Verify error
assert result is not None
assert result.isError
assert len(result.content) == 1
assert result.content[0].type == "text"
assert "Output validation error:" in result.content[0].text
assert "'five' is not of type 'integer'" in result.content[0].text
uv.lock
Generated
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