Points pydocket to the fix-cancellation-handling branch to validate
asyncio cancellation handling works correctly on the 3.x branch.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Adds opt-in distributed tracing via OpenTelemetry for observability into
FastMCP server and client operations.
Server spans are created for tool calls, resource reads, and prompt
renders with attributes like component key, component type, provider
type, session ID, and auth context. Client spans wrap outgoing calls
with trace context propagation via W3C headers in request meta.
Components provide their own span attributes through a `get_span_attributes()`
method that subclasses override - this lets LocalProvider, FastMCPProvider,
and ProxyProvider each include relevant context (original names, backend URIs).
To enable: configure an OpenTelemetry SDK with a TracerProvider before
importing fastmcp. Traces export to any OTLP-compatible backend.
Closes ENG-2813
🤖 Generated with Claude Code
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
pydocket 0.16.3 fixes a race condition in `_worker_loop` where cancellation
arriving between `_worker_done.clear()` and the try block would cause
`_worker_done.set()` to never run, blocking `Worker.__aexit__` forever.
Also fixes:
- Simplified `_docket_lifespan` cleanup (timeout wrapper no longer needed)
- Fixed `nested_server` test fixture to use graceful uvicorn shutdown
- Fixed uv transport tests to use local fastmcp in dev mode
Closes#2679🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Adds a test that verifies task cancellation actually interrupts running
coroutines (they receive CancelledError) rather than just marking the task
as cancelled in Redis while the coroutine continues to completion.
This requires pydocket >= 0.16.2 which added best-effort cancellation via
Redis pub/sub signaling to workers.
Closes#2679🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
When a tool was registered with a custom name different from its function
name, task execution would fail because Docket registered the function by
its `__name__` but the handler looked it up by the tool's configured name.
This switches to using Docket's new `names=` parameter (pydocket 0.16.0)
to register functions with their proper lookup keys, and removes the
`_create_named_fn_wrapper` hack that was used for mounted servers.
Closes#2642🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
* Add AnthropicSamplingHandler
Adds a sampling handler for the Anthropic API at
fastmcp.client.sampling.handlers.anthropic, alongside the existing
OpenAI handler. Includes full support for tool calling.
Install with: pip install fastmcp[anthropic]
* Update default model
* Update sampling docs to cover both OpenAI and Anthropic handlers
* Use AsyncAnthropic, fix falsy value handling, handle tool_choice none
* Propagate isError to Anthropic, join multiple text blocks, fix docs
* 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>
Simplifies the task support story for proxies and mounts:
- Mounts get full SEP-1686 task support (unchanged)
- Proxies explicitly forbid task execution
The cross-session task forwarding for proxies turned out to be complex
since each client connection creates a new server lifespan with a new
Docket context, and task keys include session_id. Rather than introduce
that complexity, proxies now explicitly refuse task-augmented execution.
Key changes:
- All proxy components (ProxyTool, ProxyPrompt, ProxyResource,
ProxyTemplate) now have task_config.mode="forbidden"
- Proxy tests verify forbidden behavior (sync execution works,
task=True returns error/raises McpError)
- Fixed prompt task handler to check hasattr(prompt, "task_config")
instead of isinstance(prompt, FunctionPrompt) so it applies to
ProxyPrompt too
- Added test suites for both proxy and mount task behavior
Also includes minor fixes:
- Fixed result.meta_ -> result.meta in ProxyTool.run()
- Fixed client handling of returned_immediately without taskId
- Bumped pydocket>=0.15.2
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
* Fix type errors for ty 0.0.1-alpha.31 upgrade
Add type ignores and fixes for ty's stricter checking:
- Path(None) guards in cli.py
- isinstance checks for ElicitRequestFormParams (URL elicitation support)
- TODO(ty) comments for match/isinstance narrowing bugs
- Method override type ignores for generic covariance
- Starlette Middleware typing workarounds
- Dynamic type construction ignores in json_schema_type.py
* Fix remaining type errors for ty 0.0.1-alpha.31
- Add asserts for optional attribute access in tests
- Add type ignores for dynamic httpx transport internals
- Add TODO(ty) comments for `in` operator on str|bytes
- Add TODO(ty) comments for Starlette Middleware typing
- Use cast for prompt.fn async validation in server.py
* Upgrade ty to 0.0.1-alpha.31
Fixes additional test file type errors discovered after upgrade.
* Implement MCP background tasks (SEP-1686) using Docket
Adds support for background task execution via the MCP task protocol,
powered by Docket for task queue management.
- Tools, resources, and prompts can be marked with `task=True` to run async
- Progress dependency for tracking task progress
- CurrentDocket and CurrentWorker dependencies for advanced use cases
- Client API with `.call_tool(..., task=True)` returns task handles
- Task status notifications via subscriptions
- CLI worker command for distributed task processing
Configuration via environment:
- FASTMCP_ENABLE_DOCKET=true
- FASTMCP_ENABLE_TASKS=true
- FASTMCP_DOCKET_URL=redis://... (or memory:// for single-process)
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
* Fix tasks example import (TaskStatusResponse → GetTaskResult)
The example was using a non-existent TaskStatusResponse type.
Updated to use mcp.types.GetTaskResult which is what the
on_status_change callback actually receives.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
* Fix env var name in Docket error messages
The error messages referenced FASTMCP_EXPERIMENTAL_ENABLE_DOCKET but the
actual setting is FASTMCP_ENABLE_DOCKET.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
* Remove deprecated code re-added from pre-#2329 branch
- Remove ExtendedEnvSettingsSource (FASTMCP_SERVER_ prefix support)
- Remove dependencies parameter from FastMCP.__init__
* Replace fakeredis git pin with PyPI release
* Remove redundant fakeredis dev dep (pulled via pydocket)
---------
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: Jeremiah Lowin <153965+jlowin@users.noreply.github.com>
- Bump mcp SDK to >=1.23.1
- Add `client_secret_basic` authentication support (SDK PR #1334)
- TokenHandler now wraps SDK's handle() to transform `unauthorized_client`
to `invalid_client` on 401 responses per OAuth 2.1 spec
- Update `sample()` return type to use SDK's SamplingMessageContentBlock
- Update test expectations for new SDK fields (`task`, `_meta`)
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
* Bump ty to >=0.0.1a25 with type fixes
Follow-up to #2295. Updates ty and fixes compatibility issues with alpha 25, including:
- Updated ignore comment syntax (possibly-unbound-attribute → possibly-missing-attribute)
- Fixed async generator type handling with anext()
- Fixed type narrowing for timeout parameters
- Converted base_url assignments to AnyHttpUrl after string manipulation
- Added CallToolResult to return type annotations
- Removed redundant type casts
- Fixed test form data to use strings instead of bytes
ty alpha 25 has limitations with isinstance() narrowing on unions (see pyproject.toml for details), requiring some targeted type ignores.
* Pin ty to ==0.0.1a25
Alpha releases can have breaking changes, so pin to the tested version.
* switch from pre-commit to prek
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
* fix prek tools list in contributing.mdx - include prettier, not pytest
* Use prek-action for caching
---------
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: Jeremiah Lowin <153965+jlowin@users.noreply.github.com>
* Add meta to ToolResult
* add this at the client level and test the full integration
* add example
* slipped through linting somehow
---------
Co-authored-by: Jeremiah Lowin <153965+jlowin@users.noreply.github.com>
