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Argument Completion

docs/servers/completions.mdx

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Argument completion lets a server suggest values while a user fills in a prompt argument or a resource template parameter. As the user types, the client sends a completion/complete request naming the prompt or template, the argument being completed, and the partial value so far. The server answers with candidate strings, which the client offers as autocomplete suggestions.

This is the server side of the feature. A client requests completions with Client.complete(); this page covers how a server answers.

Register a completion handler

A server has a single completion handler, registered with the @mcp.completion decorator. The handler receives every completion request and switches on which reference and argument is being completed.

python
from fastmcp import FastMCP
from mcp_types import PromptReference

mcp = FastMCP("Completion Server")


@mcp.prompt
def write_poem(theme: str) -> str:
    return f"Write a poem about {theme}"


@mcp.completion
def complete(ref, argument, context):
    if isinstance(ref, PromptReference) and ref.name == "write_poem":
        if argument.name == "theme":
            options = ["nature", "love", "adventure"]
            return [o for o in options if o.startswith(argument.value)]
    return None

The handler is called with three values:

  • ref: which component is being completed — a PromptReference (carrying the prompt name) or a ResourceTemplateReference (carrying the template uri).
  • argument: a CompletionArgument with the argument name and the partial value typed so far.
  • context: an optional CompletionContext carrying the values of arguments the user has already supplied (see Using already-supplied arguments).

Filter your candidates against argument.value so the suggestions narrow as the user types. Returning None means "I have no suggestions for this reference and argument" — the client receives an empty list, which is the correct answer for a reference the server does not recognize.

<Tip> Registering a completion handler declares the server's completions capability during the handshake. A server with no handler does not advertise the capability, and a client that checks capabilities before calling will skip completion requests entirely. This works the same way on both the handshake and modern protocol eras. </Tip>

Completing resource template parameters

The same handler answers completion for resource template parameters. A ResourceTemplateReference identifies the template by its URI template, and argument.name is the parameter being completed.

python
from fastmcp import FastMCP
from mcp_types import ResourceTemplateReference

mcp = FastMCP("Completion Server")

REPOS = ["fastmcp", "prefect", "marvin"]


@mcp.resource("github://{owner}/{repo}")
def repo_readme(owner: str, repo: str) -> str:
    return f"README for {owner}/{repo}"


@mcp.completion
def complete(ref, argument, context):
    if isinstance(ref, ResourceTemplateReference):
        if ref.uri == "github://{owner}/{repo}" and argument.name == "repo":
            return [r for r in REPOS if r.startswith(argument.value)]
    return None

Because a single handler answers for every prompt and template, a server that completes several components branches on ref first, then on argument.name. Grouping the branches by reference keeps the handler readable as it grows.

Using already-supplied arguments

Completions often depend on values the user has already entered. A repository suggestion, for example, depends on which owner was chosen. The client sends those resolved values in the completion context, and the handler reads them from context.arguments.

python
from fastmcp import FastMCP
from mcp_types import ResourceTemplateReference

mcp = FastMCP("Completion Server")

REPOS_BY_OWNER = {
    "prefecthq": ["fastmcp", "prefect", "marvin"],
    "python": ["cpython", "mypy"],
}


@mcp.resource("github://{owner}/{repo}")
def repo_readme(owner: str, repo: str) -> str:
    return f"README for {owner}/{repo}"


@mcp.completion
def complete(ref, argument, context):
    if isinstance(ref, ResourceTemplateReference) and argument.name == "repo":
        owner = context.arguments.get("owner") if context and context.arguments else None
        repos = REPOS_BY_OWNER.get(owner or "", [])
        return [r for r in repos if r.startswith(argument.value)]
    return None

Here the suggestions for repo are scoped to the owner the user already selected. The context is only present once at least one argument has been resolved, so guard against context being None.

Returning results

A handler may return any of three things:

  • A list of strings — the simplest form, wrapped into a completion response automatically.
  • None — treated as an empty completion, for references and arguments the handler does not recognize.
  • A Completion object — when you want to include pagination hints alongside the values.

The MCP protocol caps a single response at 100 values. When more candidates exist, return a Completion and set total (how many candidates match in all) and has_more (whether values were truncated) so the client can indicate that the list is partial.

python
from fastmcp import FastMCP
from mcp_types import Completion, PromptReference

mcp = FastMCP("Completion Server")

ALL_CITIES = ["Paris", "Prague", "Portland", "Phoenix", "Perth"]


@mcp.prompt
def pick_city(city: str) -> str:
    return f"Tell me about {city}"


def search_cities(prefix: str) -> list[str]:
    # A real lookup might return thousands of matches; ALL_CITIES stands in.
    return [c for c in ALL_CITIES if c.startswith(prefix)]


@mcp.completion
def complete(ref, argument, context):
    if isinstance(ref, PromptReference) and argument.name == "city":
        matches = search_cities(argument.value)
        return Completion(
            values=matches[:100],
            total=len(matches),
            has_more=len(matches) > 100,
        )
    return None

Accessing the request context

A completion handler may be sync or async, and it can reach the active request through FastMCP's dependency functions the same way any handler does. Use get_context() to access session information, authentication, or server state while computing suggestions.

python
from fastmcp import FastMCP
from fastmcp.server.dependencies import get_context
from mcp_types import PromptReference

mcp = FastMCP("Completion Server")


@mcp.completion
async def complete(ref, argument, context):
    ctx = get_context()
    await ctx.debug(f"Completing {argument.name!r} for {ref}")
    ...

Authorization

Completion runs behind the server's connection-level authentication: an unauthenticated client never reaches the handler. It is independent of per-component auth=, though. FastMCP does not resolve the referenced prompt or resource template, so a completion request is not filtered by that component's visibility the way prompts/get or a resource read is — the single handler answers for whatever reference the client names.

A completion response carries only candidate strings for one argument, never component content or schema, so this exposes nothing about a hidden component on its own. If a handler computes candidates that should themselves be restricted — matching a prompt hidden from unauthorized callers, say — check the auth context inside the handler (via get_context()) and return None when the caller is not permitted.