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Images returned from MCP tool results are silently dropped when using a BYOK provider #4600

Description

@jsmith13

Describe the bug

When a session uses a bring-your-own-key (BYOK) provider, image content returned from an MCP tool result is silently dropped before it reaches the model. The tool executes and its result is returned, but the pixels never arrive.

The failure is silent: there is no error, no warning, and no empty response. The model simply answers as if it had seen an image, confabulating a plausible description. This makes the bug easy to ship without noticing — a test that returns a predictable image (a red square, colours in a canonical order) will appear to pass.

Isolation, from the reproducer below — identical script, server, tool, question and machine, with only the provider changing:

Provider Image via blob attachment on a user turn Image via MCP tool result
Default Copilot provider ✅ correct ✅ correct
BYOK (provider={"type": "azure", ...}) ✅ correct wrong — confabulated

The attachment control passes under BYOK, so the deployment is multimodal and reading images fine. Only the tool-result path is affected. Both wire_api values (responses and completions) fail identically.

The Python SDK side looks correct: proxying the same MCP call through a custom tool and converting it with convert_mcp_call_tool_result produces a well-formed binary_results_for_llm[0] with type="image", mime_type="image/png" and intact base64 — and the model still doesn't see it. So the content appears to be lost below the Python SDK, in the request assembly for BYOK providers.

Affected version

GitHub Copilot CLI 1.0.81-9.

github-copilot-sdk 1.0.9, fastmcp 3.4.2, mcp 1.28.1.

Steps to reproduce the behavior

The script below is self-contained. It starts a small MCP server exposing one tool that returns a PNG, then asks the model a question that can only be answered by looking at the pixels.

The image is four solid-colour quadrants in a random arrangement drawn from a six-colour palette — 360 possibilities. This matters: a model that never receives the image cannot guess correctly, so confabulation is distinguishable from success. (In every failing run here, the answer came back as the canonical red green blue yellow.)

  1. pip install github-copilot-sdk fastmcp uvicorn
  2. Run python repro_mcp_image.py with no extra environment — both variants pass.
  3. Set a BYOK provider and run again — the control still passes, the MCP variant fails:
export REPRO_AZURE_BASE_URL=https://<resource>.openai.azure.com/openai/v1
export REPRO_AZURE_MODEL=<deployment-name>
export REPRO_AZURE_TOKEN=<bearer token>
export REPRO_WIRE_API=responses     # also fails with: completions
python repro_mcp_image.py

Observed output under BYOK:

Random arrangement (1 of 360): yellow orange blue green
PNG: 3,301 bytes

control -- PNG as a blob attachment on the user turn
  -> 'yellow orange blue green'  CORRECT

mcp -- PNG returned from an MCP tool result
  -> 'red green blue yellow'  tool_called=True  WRONG
repro_mcp_image.py
"""Minimal reproducer: images returned from an MCP tool result never reach the model."""

from __future__ import annotations

import asyncio
import base64
import os
import random
import struct
import sys
import zlib

import copilot
import uvicorn
from copilot.generated import rpc
from fastmcp import FastMCP
from fastmcp.utilities.types import Image

PORT = int(os.environ.get("REPRO_PORT", "8899"))

PALETTE = {
    "red": (220, 30, 30),
    "green": (30, 180, 60),
    "blue": (40, 70, 220),
    "yellow": (240, 220, 40),
    "purple": (140, 40, 180),
    "orange": (245, 140, 20),
}


def make_quadrant_png(colors: list[tuple[int, int, int]], size: int = 512) -> bytes:
    """A PNG split into four solid quadrants: TL, TR, BL, BR. No image library needed."""

    def chunk(tag: bytes, data: bytes) -> bytes:
        return (
            struct.pack(">I", len(data))
            + tag
            + data
            + struct.pack(">I", zlib.crc32(tag + data) & 0xFFFFFFFF)
        )

    half = size // 2
    raw = bytearray()
    for y in range(size):
        raw.append(0)
        top = y < half
        for x in range(size):
            left = x < half
            idx = 0 if (top and left) else 1 if top else 2 if left else 3
            raw += bytes(colors[idx])

    return (
        b"\x89PNG\r\n\x1a\n"
        + chunk(b"IHDR", struct.pack(">IIBBBBB", size, size, 8, 2, 0, 0, 0))
        + chunk(b"IDAT", zlib.compress(bytes(raw), 6))
        + chunk(b"IEND", b"")
    )


IMAGE: bytes = b""
TOOL_CALLED = False

mcp = FastMCP("repro")


@mcp.tool
async def get_test_image() -> Image:
    """Return a test image for visual analysis."""
    global TOOL_CALLED
    TOOL_CALLED = True
    return Image(data=IMAGE, format="png")


app = mcp.http_app(transport="streamable-http", path="/mcp/")

SYSTEM = (
    "You are a visual analysis assistant. When asked about an image, you MUST "
    "look at the actual image. Never guess. Answer exactly as instructed."
)

INSTRUCTION = (
    "The image is divided into four solid-colour quadrants. Report the colour of "
    "each quadrant, choosing from: red, green, blue, yellow, purple, orange.\n\n"
    "Reply with EXACTLY four lowercase words separated by single spaces, in this "
    "order: top-left, top-right, bottom-left, bottom-right. No punctuation, no "
    "explanation, no other text."
)

MCP_QUESTION = "Call the get_test_image tool, then look at the image it returns. " + INSTRUCTION


def session_kwargs() -> dict:
    """Default Copilot provider, or BYOK if REPRO_AZURE_* are set."""
    base_url = os.environ.get("REPRO_AZURE_BASE_URL")
    if not base_url:
        return {}
    model = os.environ["REPRO_AZURE_MODEL"]
    token = os.environ["REPRO_AZURE_TOKEN"]
    return {
        "model": model,
        "provider": {
            "type": "azure",
            "wire_api": os.environ.get("REPRO_WIRE_API", "responses"),
            "base_url": base_url,
            "bearer_token_provider": lambda _a: token,
            "model_id": model,
        },
    }


async def ask(*, mcp_servers=None, attachments=None, question: str) -> str:
    client = copilot.CopilotClient(log_level="error")
    await client.start()
    try:
        extra = {}
        if mcp_servers:
            extra["mcp_servers"] = mcp_servers
            extra["available_tools"] = copilot.ToolSet().add_mcp("*")
        session = await client.create_session(
            system_message={"mode": "replace", "content": SYSTEM},
            on_permission_request=lambda *_a: rpc.PermissionDecisionApproveOnce(),
            streaming=False,
            **session_kwargs(),
            **extra,
        )
        if mcp_servers:
            await asyncio.sleep(2.0)  # allow MCP negotiation to finish
        send = session.send_and_wait(question, attachments=attachments) if attachments \
            else session.send_and_wait(question)
        response = await asyncio.wait_for(send, timeout=180)
    finally:
        await client.stop()
    data = getattr(response, "data", None)
    return (getattr(data, "content", "") or "").strip().lower()


async def main() -> None:
    global IMAGE

    names = random.sample(list(PALETTE), 4)
    IMAGE = make_quadrant_png([PALETTE[n] for n in names])

    print(f"\nRandom arrangement (1 of 360): {' '.join(names)}")
    print(f"PNG: {len(IMAGE):,} bytes\n")

    server = uvicorn.Server(
        uvicorn.Config(app, host="127.0.0.1", port=PORT, log_level="warning")
    )
    server_task = asyncio.create_task(server.serve())
    for _ in range(100):
        if getattr(server, "started", False):
            break
        await asyncio.sleep(0.1)

    results = {}
    try:
        print("control -- PNG as a blob attachment on the user turn")
        answer = await ask(
            question=INSTRUCTION,
            attachments=[
                {
                    "type": "blob",
                    "data": base64.b64encode(IMAGE).decode("ascii"),
                    "mimeType": "image/png",
                    "displayName": "test.png",
                }
            ],
        )
        ok = answer.split()[:4] == names
        results["control (attachment)"] = (ok, answer)
        print(f"  -> {answer[:60]!r}  {'CORRECT' if ok else 'WRONG'}\n")

        print("mcp -- PNG returned from an MCP tool result")
        answer = await ask(
            question=MCP_QUESTION,
            mcp_servers={
                "repro": {
                    "type": "http",
                    "url": f"http://127.0.0.1:{PORT}/mcp/",
                    "tools": ["*"],
                }
            },
        )
        ok = answer.split()[:4] == names
        results["mcp (tool result)"] = (ok, answer)
        print(f"  -> {answer[:60]!r}  tool_called={TOOL_CALLED}  "
              f"{'CORRECT' if ok else 'WRONG'}\n")
    finally:
        server.should_exit = True
        await asyncio.sleep(0.3)
        server_task.cancel()

    print(f"expected: {' '.join(names)}")
    for name, (ok, answer) in results.items():
        print(f"  {name}: {'PASS' if ok else 'FAIL'} -- {answer[:60]!r}")
    sys.exit(0 if all(ok for ok, _ in results.values()) else 1)


if __name__ == "__main__":
    asyncio.run(main())

Expected behavior

An image returned from an MCP tool result should reach the model under a BYOK provider, exactly as it does under the default provider — or, if that is not supported, the CLI should surface a clear error or warning rather than silently discarding the content and letting the model answer from priors.

Additional context

  • OS: Linux x86_64 (WSL2), bash.
  • Both wire_api: "responses" and wire_api: "completions" reproduce.
  • Reproduces both with native mcp_servers= configuration and with a custom tool that proxies the MCP call and converts it via convert_mcp_call_tool_result — which suggests the loss is in BYOK request assembly rather than in MCP handling.
  • The silent-confabulation failure mode is the most costly part of this: without a randomised image, the bug looks like success.

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    area:mcpMCP server configuration, discovery, connectivity, OAuth, policy, and registryarea:modelsModel selection, availability, switching, rate limits, and model-specific behavior

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