- Lead with opentelemetry-instrument as the default approach
- Move programmatic configuration lower in the page
- Remove unimplemented metrics section
- Fix attribute values (resource_template not template)
- Add auth attributes (enduser.id, enduser.scope)
- Add provider-specific delegation attributes
- Link to OpenTelemetry Python docs
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>
* Consolidate tool transformation logic into TransformingProvider
Tool transformations were previously scattered across LocalProvider,
ProxyProvider, and MCPConfig. This consolidates all transformation
logic into TransformingProvider via with_transforms(tool_transforms={...}).
- Add tool_transforms parameter to TransformingProvider
- Add tool_transforms to Provider.with_transforms()
- Remove transformation storage from LocalProvider and ProxyProvider
- Remove add_tool_transformation() and remove_tool_transformation() from FastMCP
- Add tool_transforms parameter to factory methods (from_openapi, from_fastapi, create_proxy)
- Update tests to use new patterns
* Fix: reject tool lookups by pre-transform name
* Add collision validation for tool_transforms and fix docstring examples
- Validate duplicate target names in tool_transforms raise ValueError
- Fix docstring examples to use arguments/ArgTransformConfig (not args/ArgTransform)
- Add test for collision validation
* Add server-level tool transform APIs and fix task registration
- Add AggregateProvider to present multiple providers as one
- Add _get_root_provider() to apply server-level transforms uniformly
- Fix _docket_lifespan to use root provider (ensures renamed tools
register with correct keys for background execution)
- Add tool_transforms kwarg to __init__ (non-deprecated)
- Add add_tool_transform(), remove_tool_transform(), tool_transforms property
- Deprecate old API names (tool_transformations, add_tool_transformation, etc.)
- Update tests to use new API
* Add graceful degradation for provider errors in AggregateProvider
* Match original behavior: parallel queries with DEBUG logging
* Refactor transforms to middleware-style call_next pattern
Replaces the ad-hoc transformation system with a unified Transform
abstraction using the same call_next pattern as server middleware.
Key changes:
- New src/fastmcp/server/transforms/ module with Transform base class
- Namespace, ToolTransform, Visibility all implement the same interface
- Transforms compose via functools.partial chain building
- Visibility is now just the first transform in provider._transforms
- Server-level transforms apply after provider aggregation
- Task registration now applies full transform chain
Removes TransformingProvider, _BoundTransform, ComponentSource protocol.
User-facing API unchanged: mount(), add_transform(), enable/disable all
work as before.
* Add comprehensive transforms and visibility documentation
New docs/servers/providers/transforms.mdx covering:
- Mental model for middleware-style transform pattern
- Built-in transforms (Namespace, ToolTransform)
- Server vs provider-level transforms and ordering
- Tool modification (immediate vs deferred)
- Custom transform creation
New docs/servers/visibility.mdx covering:
- Enable/disable API for runtime visibility control
- Keys and tags for targeting components
- Allowlist mode with only=True
- Server vs provider visibility layering
Updates existing docs to reference new pages and simplifies
redundant content. Visibility is documented as a user feature,
not as an implementation detail.
* Restructure transforms docs and delete tool-transformation pattern
* Cleanup: simplify get_tasks and remove unused Provider.get_component
* Update loq
* Update loq limits and add loq note to AGENTS.md
* Deprecate add_tool_transformation and tool_transformations param
* Address PR review feedback: remove redundant imports, fix path reference
* Add missing imports to code examples in v3-features.mdx
* 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
* 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
* Unify SamplingHandler and promote OpenAI handler
Consolidates ServerSamplingHandler and ClientSamplingHandler into a single
SamplingHandler type alias. Moves OpenAISamplingHandler from experimental
to fastmcp.client.sampling.handlers.openai as the canonical location.
Backwards compatibility maintained for imports from experimental.
* Remove unreachable code paths in OpenAI handler
* Fix docstring and use elif for mutually exclusive branches
* 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>
* feat: add PromptResult as canonical internal type for prompts
Applies the same pattern as ResourceContent to prompts. PromptResult
wraps messages with description and meta. Public render() can return
either list[PromptMessage] or PromptResult (backwards compatible),
while private _render() always returns PromptResult.
* docs: fix incorrect PromptResult return type in example
* feat: add PromptResult canonical type with meta support
* fix: address PR #2600 review comments
Fixes test failures and code quality issues identified in PR review:
- Update 3 tests in test_server_interactions.py to access PromptResult.messages[0] instead of indexing directly
- Fix ProxyPromptManager to preserve meta field when converting GetPromptResult to PromptResult
- Fix ProxyPrompt.render() to return PromptResult instead of deprecated list[PromptMessage], preventing fastmcp tags from leaking into runtime meta
- Fix mask_error_details initialization to respect explicit False values
- Fix exception re-raising to preserve tracebacks (use bare raise instead of raise e)
- Update testing documentation to use pytest -n auto for parallel execution
* feat: make ResourceContent the canonical internal type for resources
Add Resource._read() private method that always returns ResourceContent,
maintaining backwards compatibility for custom resources returning str/bytes
from read(). Includes deprecation warning when str/bytes is returned.
* fix: address review feedback for ResourceContent
- Remove ResourceContent from root exports (import from fastmcp.resources)
- Fix FunctionResource.read() return type to str | bytes | ResourceContent
- Decode base64 blobs in proxy when receiving from remote servers
- Preserve meta in ProxyResource cached content
* fix: add empty result guards in proxy resource reads
* feat: handle error from the initialize middleware
In some situation, the initialize middleware can check the status of the
server and decide to raise an error.
Example use case: in a FastMCPProxy, an initialization middleware
overrides the on_initialize method and connect to the underlying proxied
client. When client respond with error, I want to pass this error to the
client.
* docs update
* test: use McpError assertions now that exception propagation is fixed
- Update tests to catch McpError specifically instead of generic Exception
- Remove commented-out code in low_level.py
---------
Co-authored-by: Jeremiah Lowin <153965+jlowin@users.noreply.github.com>
* Add comprehensive documentation for read-only tool patterns
Created new patterns guide explaining readOnlyHint annotation usage,
including practical examples, client-specific behavior, and best
practices for marking tools as read-only.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-authored-by: William Easton <strawgate@users.noreply.github.com>
* Reorganize read-only tools docs into tools section
Moved read-only tools documentation from standalone patterns page into the tools.mdx file as a "Using Annotation Hints" subsection. Condensed from 218 lines to ~50 lines focusing on practical usage while maintaining essential information about readOnlyHint and other annotations.
Changes:
- Added "Using Annotation Hints" subsection in tools.mdx after MCP Annotations
- Removed docs/patterns/read-only-tools.mdx
- Updated docs.json navigation to remove patterns entry
- Content now positioned as core tool feature rather than advanced pattern
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-authored-by: Bill Easton <strawgate@users.noreply.github.com>
---------
Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: William Easton <strawgate@users.noreply.github.com>
* SEP-1330 enum schema support for elicitation
* Add version badges for 2.14.0 elicitation features
* Fix Context.elicit() to handle SEP-1330 enum syntaxes
* Guard against empty list in elicit response_type
* Add guards for empty dict/list edge cases in elicit
* Refactor elicit: extract parsing and response handling to elicitation.py
The task protocol (SEP-1686) is now always enabled - server always
registers task handlers and advertises task capabilities. Users still
opt into background execution at the server level (tasks=True) or
component level (task=True on tools, prompts, resources).
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Lead with concepts instead of code
- Explain MCP background tasks vs general Python concurrency
- Document Docket's Prefect origins and battle-tested infrastructure
- Add sections on graceful degradation and embedded workers
- Fix version badge to 2.14.0
- Link to SEP-1686 spec
Docket provides background task execution and is now always available
for all FastMCP servers. Only `enable_tasks` remains to control the
SEP-1686 task protocol support.
Changes:
- Remove `enable_docket` setting and related validation
- Docket/Worker lifecycle is always active in server lifespan
- CurrentDocket and CurrentWorker dependencies work without config
- Add server readiness signaling via `_started` event
- Fix test timing issues with proper port probing
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
* 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>
* Fix RFC 8414 path-aware authorization server metadata discovery
Override get_well_known_routes() in OAuthProvider to rewrite the
authorization server metadata route to be path-aware based on issuer_url,
matching how protected resource metadata already works.
Closes#2527
* Update readme
* Initialize 2.14 deprecation removal branch
* Remove deprecated FASTMCP_SERVER_ environment variable prefix (#2330)
* Remove deprecated Context.get_http_request method (#2332)
* Remove fastmcp.Image top-level import (deprecated 2.8.1) (#2334)
* Remove test warnings (#2331)
* Create new branch and fix issue
* Remove deprecated client parameter from FastMCPProxy (#2333)
* Remove deprecated run_streamable_http_async method (#2338)
* Remove deprecated sse_app method (#2337)
* Remove deprecated run_sse_async method (#2335)
* Remove deprecated run_sse_async method
* Update CLI and tests to use run_http_async(transport="sse")
- Change CLI to call run_http_async with transport="sse" instead of run_sse_async
- Update test to mock run_http_async with create=True for v1 servers
* Revert CLI changes - v1 servers do have run_sse_async
- Keep CLI calling run_sse_async() for v1 compatibility
- Update test to mock run_sse_async (which exists on v1)
* Remove unnecessary type ignore for run_sse_async
Method exists on v1 FastMCP class, no type error
* Remove unused imports after test deletion
* Remove deprecated streamable_http_app method (#2336)
* Remove deprecated dependencies parameter from FastMCP constructor (#2340)
* Remove output_schema=False support (deprecated 2.11.4) (#2339)
* Remove deprecated client parameter from FastMCPProxy (#2333)
* Delete deprecated test_output_schema_false.py
Tests functionality that has been removed
* Remove deprecated BearerAuthProvider module (#2341)
* Remove resource_prefix_format="protocol" support (deprecated 2.4.0) (#2342)
* Remove resource_prefix_format="protocol" support (fixes#2195)
Removes deprecated protocol format (prefix+resource://path) and keeps only
path format (resource://prefix/path). Since only one format remains:
- Removed resource_prefix_format from settings, FastMCP.__init__, and helpers
- Simplified add_resource_prefix, remove_resource_prefix, has_resource_prefix
- Removed MountedServer.resource_prefix_format field
- Deleted tests for protocol format
All resource prefixes now use path format exclusively.
* Clean up resource_prefix_format references
- Remove from test files
- Update documentation to remove protocol format section
- Move custom HTTP routes note to mounting section
- Remove resource_prefix_format from settings docs
* Use inline version note instead of badge for prefix format
* Remove obsolete test functions and update docs
- Delete test functions that no longer assert anything
- Remove proxy.mdx reference to deleted prefix format section
* Format error messages per ruff
* Remove from_client classmethod (deprecated 2.8.0) (#2343)
* Remove deprecated from_client classmethod (fixes#2192)
* Remove unused Client import
* Remove add_resource_fn method (deprecated 2.7.0) (#2345)
* Update SDK
* Add missing imports for exclude_args deprecation warning
