A tool returning an empty list produces a CallToolResult with zero content blocks

Aperta
#3,305 1 commento 0 reazioni 0 assegnatari Vedi su GitHub

Nessuno ha ancora preso questa issue.

Valutazione

Difficoltà
2/5
Tempo stimato
1-3 ore
Idoneità per principianti
55/100
Tipo di issue
Bug
Chiarezza
Specificata chiaramente
Stato di attività
Tranquilla
Stack tecnologico
python
Ambito
api

Direzione di ricerca

Inizia con _convert_to_content in src/mcp/server/mcpserver/utilities/func_metadata.py:563 e confronta il suo comportamento con una lista vuota con il percorso documentato per i contenuti non strutturati. Usa le riproduzioni find_person e find_two dell’issue per verificare che i risultati non vuoti rimangano invariati e che il comportamento concordato per una lista vuota sia coperto.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

enhancement needs decision P2 v1 v2
Initial Checks
  • I confirm that I'm using the newest release of my line (mcp 2.0.0)
  • I confirm that I searched for my issue before opening this issue
Release line

2.x

Description

A tool that returns an empty list produces a CallToolResult with zero content blocks. For a client that reads unstructured content, "no matches" and "the call returned nothing" become the same thing.

_convert_to_content (src/mcp/server/mcpserver/utilities/func_metadata.py:563) flattens a list by concatenating the conversion of each item:

if isinstance(result, list | tuple):
    return list(chain.from_iterable(_convert_to_content(item) for item in result))

With zero items there is nothing to concatenate, so the result is []. That is a natural consequence of the flattening rule rather than an oversight, but it produces an asymmetry that is surprising in practice — the same "empty" answer behaves differently depending on the return type:

tool returns content blocks text a client sees
[] 0 ''
[{...}, {...}] 2 both items
"" 1 ''

structuredContent is populated correctly in all three cases ({'result': []} for the empty list), so a client that reads structured output is unaffected. The gap is specific to clients consuming unstructured content — which is the population _convert_to_content's own docstring says it exists to serve: "retained for purposes of backwards compatibility."

Why this matters in practice. We hit it with an LLM-facing directory search. A find_person tool that legitimately found nobody returned an empty content array, and from the model's side that is indistinguishable from a call that produced nothing — so it re-tried the same lookup with cosmetic variations instead of concluding the person did not exist. Observed in one turn: find_person("Martha") → nothing → find_person("Martha Highlander") → nothing → find_person("Martha") again. Three identical searches, no answer. We work around it today by patching _convert_to_content in our own server so an empty list serializes to one TextContent holding [].

Worth noting the SDK already states this rule for tool authors — the docs advise returning [] rather than "" for an empty result — but a tool that follows that advice is exactly the one whose content array comes back empty.

Possible fix. In the list branch, when the conversion yields no blocks, emit a single TextContent with the serialized empty collection rather than an empty list. That keeps every non-empty case byte-identical and changes only the currently-empty one. I have not opened a PR: it changes output for every list-returning tool on the unstructured path, so it seemed worth agreeing on the direction (and on whether the empty-content array is considered correct as-is) before writing code. Happy to put one up if you'd like it.

Example Code
"""A tool returning an empty list yields a CallToolResult with zero content blocks."""

import asyncio

from mcp import Client
from mcp.client._memory import InMemoryTransport
from mcp.server.mcpserver import MCPServer

server = MCPServer("repro")


@server.tool()
def find_person(name: str) -> list[dict]:
    """Return matching people; an empty list means no match."""
    return []


@server.tool()
def find_two(name: str) -> list[dict]:
    """Two matches, for contrast."""
    return [{"name": "a"}, {"name": "b"}]


@server.tool()
def find_person_str(name: str) -> str:
    """The same answer as a string, for comparison."""
    return ""


async def main() -> None:
    async with Client(InMemoryTransport(server)) as client:
        for tool in ("find_person", "find_two", "find_person_str"):
            result = await client.call_tool(tool, {"name": "Martha"})
            text = "".join(b.text for b in result.content if b.type == "text")
            print(f"{tool}:")
            print(f"  content blocks    = {len(result.content)}")
            print(f"  text seen by model= {text!r}")
            print(f"  structuredContent = {result.structured_content!r}")


asyncio.run(main())

Output:

find_person:
  content blocks    = 0
  text seen by model= ''
  structuredContent = {'result': []}
find_two:
  content blocks    = 2
  text seen by model= '{\n  "name": "a"\n}{\n  "name": "b"\n}'
  structuredContent = {'result': [{'name': 'a'}, {'name': 'b'}]}
find_person_str:
  content blocks    = 1
  text seen by model= ''
  structuredContent = {'result': ''}
Python & MCP Python SDK
python 3.14.3
mcp 2.0.0
platform macOS-15.6.1-arm64-arm-64bit-Mach-O

AI assistance disclosure, per CONTRIBUTING: this issue was investigated and drafted with Claude Code. The repro above was run and its output pasted verbatim, and I reviewed the whole thing before filing.

Lingua principale
Python
Stelle
24.3k
Fork
4k
Merge medio
1g 19m
PR unite (30g)
29

Guida per i contributori

Apri la guida per i contributori

Come iniziare

  1. Leggi tutta la issue e poi la guida ai contributi del progetto.
  2. Commenta sulla issue per dire che te ne occupi tu — evita che due persone facciano lo stesso lavoro.
  3. Fai un fork del repository e lavora su un branch.
  4. Apri una pull request che faccia riferimento al numero della issue.

Altre issue di modelcontextprotocol/python-sdk

Tutte le issue di modelcontextprotocol/python-sdk

Ricevi le nuove issue nella tua casella

Un breve riepilogo di issue GitHub adatte ai principianti.