Files
modelcontextprotocol--pytho…/tests/server/test_lowlevel_output_validation.py
2026-02-02 13:24:55 +01:00

495 lines
17 KiB
Python

"""Test output schema validation for lowlevel server.
NOTE: These tests are skipped because server-side output validation was removed
with the decorator-based API. The constructor-based API delegates validation
to the handler. The old decorator wrapped raw returns (list[TextContent], dict)
and validated against output_schema, which is no longer done automatically.
"""
import json
from collections.abc import Awaitable, Callable
from typing import Any
import anyio
import pytest
# Skip all tests in this file - output validation was removed with decorator-based API
pytestmark = pytest.mark.skip(
reason="Server-side output validation was removed with the decorator-based API. "
"The constructor-based API delegates validation to the handler."
)
import mcp.types as types
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.context import RequestContext
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 | None:
"""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
"""
async def on_list_tools(
ctx: RequestContext[ServerSession, Any, Any],
params: types.PaginatedRequestParams | None,
) -> types.ListToolsResult:
return types.ListToolsResult(tools=tools)
async def on_call_tool(
ctx: RequestContext[ServerSession, Any, Any],
params: types.CallToolRequestParams,
) -> Any:
return await call_tool_handler(params.name, params.arguments or {})
server = Server("test", on_list_tools=on_list_tools, on_call_tool=on_call_tool)
result = None
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( # pragma: no cover
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: # pragma: no branch
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",
input_schema={
"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: # pragma: no cover
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.is_error
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.structured_content 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",
input_schema={
"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: # pragma: no cover
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.is_error
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.structured_content == {"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",
input_schema={
"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: # pragma: no cover
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.is_error
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.structured_content == {"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",
input_schema={
"type": "object",
"properties": {},
},
output_schema={
"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.is_error
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",
input_schema={
"type": "object",
"properties": {
"x": {"type": "number"},
"y": {"type": "number"},
},
"required": ["x", "y"],
},
output_schema={
"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: # pragma: no cover
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.is_error
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.structured_content == {"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",
input_schema={
"type": "object",
"properties": {},
},
output_schema={
"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: # pragma: no cover
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.is_error
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",
input_schema={
"type": "object",
"properties": {
"text": {"type": "string"},
},
"required": ["text"],
},
output_schema={
"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: # pragma: no cover
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.is_error
assert len(result.content) == 1
assert result.content[0].type == "text"
assert result.content[0].text == "Analysis of: Great job!"
assert result.structured_content == {"sentiment": "positive", "confidence": 0.95}
@pytest.mark.anyio
async def test_tool_call_result():
"""Test returning ToolCallResult when no outputSchema is defined."""
tools = [
Tool(
name="get_info",
description="Get structured information",
input_schema={
"type": "object",
"properties": {},
},
# No outputSchema for direct return of tool call result
)
]
async def call_tool_handler(name: str, arguments: dict[str, Any]) -> CallToolResult:
if name == "get_info":
return CallToolResult(
content=[TextContent(type="text", text="Results calculated")],
structured_content={"status": "ok", "data": {"value": 42}},
_meta={"some": "metadata"},
)
else: # pragma: no cover
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.is_error
assert len(result.content) == 1
assert result.content[0].type == "text"
assert result.content[0].text == "Results calculated"
assert isinstance(result.content[0], TextContent)
assert result.structured_content == {"status": "ok", "data": {"value": 42}}
assert result.meta == {"some": "metadata"}
@pytest.mark.anyio
async def test_output_schema_type_validation():
"""Test outputSchema validates types correctly."""
tools = [
Tool(
name="stats",
description="Get statistics",
input_schema={
"type": "object",
"properties": {},
},
output_schema={
"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: # pragma: no cover
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.is_error
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