- Add Pre-built Handlers section to clients/sampling.mdx with Anthropic and OpenAI
- Simplify servers/sampling.mdx to reference client docs for handler details
- Add examples for Azure OpenAI and local model providers
* 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>
- 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
* Add manual initialization control to Client
- Add auto_initialize parameter (default True) to control automatic initialization
- Make initialize() method public with idempotent caching
- Add comprehensive test suite for initialization behavior
* Document client initialization control and server instructions
- Expand documentation to cover auto_initialize parameter
- Show manual initialization for advanced use cases
- Document accessing server instructions via initialize_result
* Update client.mdx
Add warning notes to documentation directing users to review
py-key-value documentation for backend maturity and limitations
before production use.
Co-authored-by: William Easton <strawgate@users.noreply.github.com>
* Update docs for required scopes
* add scopes
* Fix Azure scope validation
Azure returns unprefixed scopes in JWT tokens but requires prefixed scopes in authorization requests. The previous implementation incorrectly validated tokens against prefixed scopes, causing "invalid_token" errors.
Simplified AzureProvider to use standard JWTVerifier with unprefixed scopes for validation. Scopes are only prefixed when building the Azure authorization URL via _build_upstream_authorize_url() override.
Closes#2263
* Improve OAuth client token storage security documentation
Updated warning message and documentation to address security concerns
around storing OAuth credentials for multiple MCP servers.
Implements comprehensive notification system for tools, resources, and prompts with automatic client updates and flexible message handlers.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
