chore(deps): bump fastmcp from 2.13.2 to 2.14.1 in /modelcontextprotocol

[dependabot]

Bumps fastmcp from 2.13.2 to 2.14.1.

Release notes

Sourced from fastmcp's releases.

'Tis a Gift to Be Sample

FastMCP 2.14.1 adds support for sampling with tools (SEP-1577). This exciting new feature lets servers pass tools to ctx.sample(), enabling agentic workflows where the server borrows the client's LLM and controls tool execution automatically. Pass any callable as a tool and FastMCP handles the loop: calling the LLM, executing tools, and feeding results back until a final response is produced. For fine-grained control, ctx.sample_step() makes a single LLM call and returns a SampleStep, letting you inspect tool calls, add custom logic, or build your own execution loop. Structured output via result_type returns validated Pydantic models instead of raw text. This release also adds AnthropicSamplingHandler alongside the existing OpenAI handler (newly promoted out of the experimental module), so clients and servers can provide sampling capability across major providers with ease.

What's Changed

New Features 🎉

• SEP-1577: Sampling with tools by @​jlowin in jlowin/fastmcp#2551
• Add AnthropicSamplingHandler by @​jlowin in jlowin/fastmcp#2617

Enhancements 🔧

• Add Python 3.13 to Ubuntu CI tests by @​jlowin in jlowin/fastmcp#2606
• Remove legacy _task_capable_initialize() workaround by @​jlowin in jlowin/fastmcp#2612
• Consolidate session state reset logic and improve cancellation cleanup by @​jlowin in jlowin/fastmcp#2615
• Unify SamplingHandler and promote OpenAI handler by @​jlowin in jlowin/fastmcp#2616
• Add tool_names parameter to mount() for name overrides by @​jlowin in jlowin/fastmcp#2619
• Adopt streamable_http_client API from MCP SDK by @​jlowin in jlowin/fastmcp#2620
• Deprecate exclude_args in favor of Depends() by @​jlowin in jlowin/fastmcp#2621

Fixes 🐞

• fix: prompt tasks returning mcp.types.PromptMessage now work by @​chrisguidry in jlowin/fastmcp#2603
• Use WindowsSelectorEventLoopPolicy to fix Windows test warnings by @​jlowin in jlowin/fastmcp#2607
• Clean up cancelled connection startup by @​shawnthapa in jlowin/fastmcp#2614
• Consolidate sampling examples and fix tool_choice bug by @​jlowin in jlowin/fastmcp#2618

Docs 📚

• docs: simplify Docket tip wording by @​jlowin in jlowin/fastmcp#2599

Dependencies 📦

• chore: bump pydocket to >=0.15.5 by @​chrisguidry in jlowin/fastmcp#2605

New Contributors

• @​shawnthapa made their first contribution in jlowin/fastmcp#2614

Full Changelog: jlowin/fastmcp@v2.14.0...v2.14.1

v2.14.0: Task and You Shall Receive

FastMCP 2.14 begins adopting the MCP 2025-11-25 specification, headlined by protocol-native background tasks that let long-running operations report progress without blocking clients. This release also graduates the OpenAPI parser to standard, adds first-class support for several new spec features, and removes deprecated APIs accumulated across the 2.x series.

Background Tasks (SEP-1686)

Long-running operations (like tool calls) normally block MCP clients until they complete. The new MCP background task protocol (SEP-1686) lets clients start operations, track progress, and retrieve results without blocking. For FastMCP users, taking advantage of this new functionality is as easy as adding task=True to any async decorator. Under the hood, it's powered by Docket, the enterprise task scheduler at the heart of Prefect Cloud that handles millions of concurrent tasks every day.

from fastmcp import FastMCP
from fastmcp.dependencies import Progress
mcp = FastMCP("MyServer")
@​mcp.tool(task=True)
async def train_model(dataset: str, progress: Progress = Progress()) -> str:
await progress.set_total(100)
for epoch in range(100):
# ... training work ...
</tr></table>

... (truncated)

Commits

• 2f561ec Deprecate exclude_args in favor of Depends() (#2621)
• 076ec0c Adopt streamable_http_client API from MCP SDK (#2620)
• b8ae95a Add tool_names parameter to mount() for name overrides (#2619)
• 577f4d1 Consolidate sampling examples and fix tool_choice bug (#2618)
• c91c43e Add AnthropicSamplingHandler (#2617)
• da77cfa Unify SamplingHandler and promote OpenAI handler (#2616)
• 41ec7ee SEP-1577: Sampling with tools (#2551)
• 0cd3690 Consolidate session state reset logic and improve cancellation cleanup (#2615)
• d26b04f Clean up cancelled connection startup (#2614)
• 08d092b Use WindowsSelectorEventLoopPolicy to fix Windows test warnings (#2607)
• Additional commits viewable in compare view

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

---

Dependabot commands and options

You can trigger Dependabot actions by commenting on this PR:

• @dependabot rebase will rebase this PR
• @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
• @dependabot merge will merge this PR after your CI passes on it
• @dependabot squash and merge will squash and merge this PR after your CI passes on it
• @dependabot cancel merge will cancel a previously requested merge and block automerging
• @dependabot reopen will reopen this PR if it is closed
• @dependabot close will close this PR and stop Dependabot recreating it. You can achieve the same result by closing it manually
• @dependabot show <dependency name> ignore conditions will show all of the ignore conditions of the specified dependency
• @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
• @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
• @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)