* pin pydantic-monty to 0.0.8
* rename tool/prompt/resource base modules to avoid decorator name shadow
* add sys.modules shims for old submodule import paths
* preserve original module paths in deprecation warnings
* clarify when sys.modules shims can be removed
* Replace vendored DI with uncalled-for
FastMCP vendored a minimal DI engine extracted from Docket (~164 lines)
with try/except fallback patterns everywhere. The `uncalled-for` package
is a clean, typed extraction of this same system, and since Docket will
also depend on it (chrisguidry/docket#353), `uncalled_for.Dependency`
becomes the single canonical base class.
This deletes the `_vendor/docket_di/` directory, replaces all the
try/except import patterns with direct `uncalled_for` imports, and
updates the `Dependency.execution` → `current_execution` ContextVar
references to match the Docket branch. The `Progress` class now
delegates to an internal impl and returns `self` from `__aenter__`
(matching Docket's pattern) so that ty's generic resolution works
without `type: ignore` suppressions.
Temporarily points pydocket at the `use-uncalled-for` branch so both
sides can be validated together in CI.
🤖 Generated with Claude Code
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* Re-export Dependency from fastmcp.dependencies
Internal code like azure.py should import from the fastmcp namespace
rather than reaching into uncalled_for directly.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* Import Dependency from fastmcp namespace in tests
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* Add generic type parameters to Dependency subclasses
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* Mention uncalled-for in DI docs
The DI engine now comes from uncalled-for, so the docs should credit
it alongside Docket. Also updates the Docket docs link to docket.lol.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* Point docket dependency at main
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* Bump uncalled-for pin to >=0.2.0
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* Fix uncalled-for imports for 0.2.0 API changes
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* Support Shared() dependencies without docket
Enters a SharedContext at server lifetime so that Shared() dependencies
from uncalled-for resolve once and are cached across tool/resource/prompt
calls. When running with docket, the Worker already handles this; this
covers the non-docket path and direct call_tool() usage.
Also re-exports Shared from fastmcp.dependencies.
Closes#3251
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* Bump docket lockfile to latest main
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* Remove duplicate test classes from rebase conflict resolution
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* Point docket dependency at pydocket>=0.18.0 release
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* Pair SharedContext __aenter__ with __aexit__ in Context lifecycle
The old `_ensure_shared_context` on the server called `__aenter__()` on a
lazy `SharedContext` but never `__aexit__()`, leaking the exit stack and
its resources. Moved the SharedContext management into Context's own
enter/exit so it's properly paired: when docket is available the lifespan
handles it, otherwise Context creates and cleans up a per-request one.
Updated Shared() tests to use Client (which runs the lifespan) rather
than calling server methods directly, since cross-request sharing
requires a lifespan.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* Hoist SharedContext import to module level
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* Fix ty 0.0.19 type errors
🤖 Generated with Claude Code
* Fix ruff formatting in sampling/run.py
🤖 Generated with Claude Code
https://claude.ai/code/session_01GWzbyF1vHvVeS4yJ5bhScf
---------
Co-authored-by: Claude <noreply@anthropic.com>
* Fix ty ignore syntax in OpenAPI provider
* Fix flaky rate limiting and ping timing tests
* Assert rate limit error message in flaky test fix
* Catch only ToolError in rate limiting test
* Fix non-serializable state lost between middleware and tools
Inherit _request_state dict from parent Context in __aenter__ so
middleware and tool contexts share the same in-memory state.
Closes#3228
* chore: Update SDK documentation
---------
Co-authored-by: marvin-context-protocol[bot] <225465937+marvin-context-protocol[bot]@users.noreply.github.com>
* Update repository references from jlowin/fastmcp to prefecthq/fastmcp
* Retrigger CI after repo transfer
* chore: Update SDK documentation
* Only run deep triage on bug issues for jlowin
---------
Co-authored-by: marvin-context-protocol[bot] <225465937+marvin-context-protocol[bot]@users.noreply.github.com>
* Add poll_interval to TaskConfig
Allow users to configure polling interval per component via
TaskConfig(poll_interval=timedelta(...)). Default is 5 seconds.
* Update snapshots for poll_interval field
* Add version badge to poll_interval docs
* Add defensive handling for Redis data and align default poll intervals
* Replace type: ignore[attr-defined] with isinstance assertions in tests
* Fix isinstance assertions in failing tests
- Fix enum test to check for ResponseEnum instead of str
- Fix binary resource test to check for BlobResourceContents instead of TextResourceContents
- Fix Root type tests to check attributes directly instead of isinstance checks
* Fix type errors without using type: ignore
- Remove execution methods from TransformingProvider (only handles transformations)
- Add execution methods to base Provider class with default implementations
- Fix type narrowing in tests using cast() instead of type: ignore
- Fix PromptResult type handling in prompt render tests
- Fix type narrowing in middleware test for arguments and structured_content
* Add test_custom_subclass_tasks.py
* Refactor provider execution: delegate to middleware via wrapper components
- Remove execution methods (call_tool, read_resource, etc.) from Provider base
- Add FastMCPProvider* wrapper classes that delegate to child server middleware
- Move task routing to Tool._run() using contextvars (_task_metadata, _tool_call_key)
- Add convert_to_tool_result(result, output_schema) utility for Docket results
- Add convert_to_prompt_result() utility for prompt task results
- Pass namespaced key via add_to_docket(name=) for mounted tool lookup
* Standardize add_to_docket() with fn_key/task_key parameters
All components now use explicit fn_key (function lookup) and task_key
(result storage) parameters instead of relying on implicit key handling.
This fixes mounted component task execution where the MCP-visible key
differs from the Docket-registered function name.
* Add middleware chain tests for three-level mount hierarchy
Tests verify middleware runs at parent, child, and grandchild levels
for tools, resources, prompts, and resource templates.
* WIP: Provider refactor - unified submit_to_docket, template _read() in progress
Work in progress on refactoring execution to use component _read()/_run()/_render() methods.
Template background tasks not yet working - needs fix for Docket key lookup.
* Fix conversion functions to take full component for attribute access
Pass Tool/Prompt/Resource/Template to conversion functions instead of
individual attributes, ensuring access to serializer, output_schema,
mime_type, etc. Also fixes mixed-content output schema validation.
* Refactor: unified convert_result() methods and check_background_task helper
- Add convert_result() instance methods to all component types (Tool, Prompt, Resource, ResourceTemplate)
- Extract duplicated task routing logic into check_background_task() helper
- Fix type annotations on FastMCPProviderResource.read() and FastMCPProviderPrompt.render()
- Update protocol.py to use component.convert_result() uniformly
* Update tests to use namespace= instead of deprecated prefix= parameter
Refactors docket/background task support to be encapsulated within each
component rather than requiring external coordination:
- Move task_config to FastMCPComponent base class (default: forbidden)
- Add register_with_docket(docket) method that components use to register
themselves, checking task_config internally
- Add add_to_docket() method that handles component-specific calling
conventions (splatted kwargs vs positional dict)
- Simplify server registration to just call component.register_with_docket()
- Update task handlers to use component.add_to_docket()
This enables custom Tool/Resource/Prompt subclasses to support background
tasks by setting task_config and optionally overriding the docket methods.
* MCP → SDK (vocab change only)
* WIP: Sampling API with SamplingResult[T] and result_type
* SEP-1577: Sampling with tools
- Add tools and result_type parameters to ctx.sample()
- Update OpenAI handler for tool content types
- Client advertises sampling.tools capability by default
- Collect tool results into single message with list content
* Fix tool result content handling in OpenAI handler
* Remove @sampling_tool decorator - pass functions directly to sample()
Functions passed to ctx.sample(tools=[...]) are now auto-converted
via SamplingTool.from_function(). Users can still use that method
directly for custom name/description overrides.
* Remove auto-conversion of MCP tools to sampling tools
Users want MCP tools passed to ctx.sample() to go through the full MCP
machinery (middleware, native responses) rather than being auto-converted
to direct function calls. Now only SamplingTool and plain callables are
accepted - passing a FastMCP Tool raises a clear TypeError.
Also bumps mcp dependency to >=1.24.0 for required sampling features.
* Refactor sampling API: replace sample_iter() with sample_step()
Replace the mutable SampleRun/sample_iter() pattern with a simpler stateless
sample_step() function. sample_step() makes a single LLM call and returns a
SampleStep with the response and history. sample() now loops sample_step()
internally.
Key changes:
- Add sample_step() for fine-grained control over the sampling loop
- Remove SampleRun class and sample_iter() method
- Structured output uses tool description only (no prompt modification)
- execute_tools parameter controls automatic vs manual tool execution
* Address CodeRabbit nitpicks
* Address CodeRabbit review feedback for sampling tools
- Fix temperature=0.0 being dropped due to falsy evaluation
- Add ToolChoice.name support for forcing specific tools
- Replace assert statements with explicit RuntimeError checks
- Add mask_error_details parameter to sample()/sample_step() with ToolError escape hatch
- Fix hasattr patterns with proper isinstance checks
- Document mask_error_details and add OpenAI prerequisites to docs
* Address additional CodeRabbit review feedback
- Catch ValidationError specifically instead of bare Exception
- Update result_type docs to mention dataclasses and basic types
- Raise ValueError for unknown tool_choice modes
- Validate sampling_handler_behavior to catch typos
- Remove ToolChoice.name handling (not part of MCP spec)
- Validate tool_choice string in sample_step()
* Review fixes for sampling tools PR
- Remove internal functions from sampling __init__.py exports
- Remove fragile is_text property, use not is_tool_use instead
- Inline call_client into context.py, remove from run.py
- Fix SamplingMessage docs to use TextContent
- Handle result.text being None in doc examples
- Simplify client sampling docs to recommend OpenAISamplingHandler
- Add sampling_capabilities override documentation
- Raise iteration limit from 50 to 100
- Remove _parse_model_preferences duplication
- Use AsyncOpenAI in OpenAISamplingHandler
- Fix tool_choice docstring
* Fix OpenAI handler tests to use AsyncOpenAI
* Address remaining CodeRabbit review comments
- Fix message ordering in OpenAI handler: tool results now correctly
follow assistant message with tool_calls
- sample_step() now always includes assistant message in history
- Raise ValueError on JSON parse errors instead of silent {}
- Add has_sampling capability check when behavior is None
- Raise RuntimeError when structured output receives text response
- Wrap primitive result_type schemas in object wrapper
- Fix docs example using invalid SamplingMessage construction
- Add comprehensive client_sampling_test.py example
* Add return type annotation to OpenAISamplingHandler.__init__
* Use explicit 'is not None' check for sampling_capabilities defaulting
---------
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: Bill Easton <strawgate@users.noreply.github.com>
