feat(mcp): deliver image content from MCP tools as artifacts

MCPToolWrapper.execute only handled TextContent; every other block was
rendered with str(block). An MCP ImageContent block therefore became a
large base64 string embedded in the tool result, which (a) was truncated
by max_tool_result_chars, corrupting the data, and (b) could never reach a
channel because it was plain text, not an image artifact.

Decode ImageContent (and EmbeddedResource blobs with an image/* MIME type)
and persist them via store_generated_image_artifact, returning the same
compact {artifacts, next_step} JSON the built-in image_generation tool
produces. The base64 stays out of the model context; the model delivers the
saved file via the message tool's media parameter.
This commit is contained in:
codedragon
2026-06-28 19:46:51 +08:00
committed by Xubin Ren
parent 194e9d5f5f
commit 67ce6822ca
2 changed files with 164 additions and 10 deletions
+101 -10
View File
@@ -1,6 +1,7 @@
"""MCP client: connects to MCP servers and wraps their tools as native nanobot tools."""
import asyncio
import json
import os
import re
import shutil
@@ -313,6 +314,52 @@ class _MCPWrapperBase(Tool):
return True
def _image_block_data_url(block: Any, types: Any) -> str | None:
"""Return a base64 ``data:`` URL for an MCP image-bearing content block.
Handles ``ImageContent`` directly and ``EmbeddedResource`` wrapping a binary
blob with an ``image/*`` MIME type. Returns ``None`` for anything else.
``getattr`` guards keep this safe when the installed/faked ``mcp`` SDK does
not expose a given type.
"""
image_cls = getattr(types, "ImageContent", None)
if image_cls is not None and isinstance(block, image_cls):
mime = getattr(block, "mimeType", None) or "image/png"
return f"data:{mime};base64,{block.data}"
embedded_cls = getattr(types, "EmbeddedResource", None)
blob_cls = getattr(types, "BlobResourceContents", None)
if embedded_cls is not None and isinstance(block, embedded_cls):
resource = getattr(block, "resource", None)
if blob_cls is not None and isinstance(resource, blob_cls):
mime = getattr(resource, "mimeType", None) or ""
if isinstance(mime, str) and mime.startswith("image/"):
return f"data:{mime};base64,{resource.blob}"
return None
def _mcp_image_tool_result(text_parts: list[str], artifacts: list[dict[str, Any]]) -> str:
"""Build the compact tool result for an MCP call that returned image(s).
The base64 stays out of the model context entirely — only artifact paths and
metadata are returned, so the result is small and the channel can deliver the
saved file via the message tool.
"""
payload: dict[str, Any] = {
"artifacts": artifacts,
"next_step": (
"These images were returned by an MCP tool and saved as local artifacts. "
"Call the message tool with the artifact 'path' values in the media "
"parameter to deliver the images to the user. Do not paste base64 or raw "
"paths into your reply unless the user asks for debug details."
),
}
text = "\n".join(part for part in text_parts if part)
if text:
payload["text"] = text
return json.dumps(payload, ensure_ascii=False)
class MCPToolWrapper(_MCPWrapperBase):
"""Wraps a single MCP server tool as a nanobot Tool."""
@@ -340,8 +387,6 @@ class MCPToolWrapper(_MCPWrapperBase):
return self._parameters
async def execute(self, **kwargs: Any) -> str:
from mcp import types
retried_transient = False
refreshed_session = False
while True:
@@ -396,17 +441,63 @@ class MCPToolWrapper(_MCPWrapperBase):
)
return f"(MCP tool call failed: {type(exc).__name__})"
else:
# Success — extract result
parts = []
for block in result.content:
if isinstance(block, types.TextContent):
parts.append(block.text)
else:
parts.append(str(block))
return "\n".join(parts) or "(no output)"
# Success — extract text and persist any image content as artifacts.
return self._render_call_result(result.content, kwargs)
return "(MCP tool call failed)" # Unreachable, but satisfies type checkers
def _render_call_result(self, content: Any, arguments: Mapping[str, Any]) -> str:
"""Turn MCP content blocks into a tool result string.
Text is concatenated as before. Image blocks are decoded and saved as
local artifacts (mirroring the built-in image generation tool) so the
model can deliver them via the message tool instead of trying to forward
base64 — which would be truncated and bloat the context window.
"""
from mcp import types
text_parts: list[str] = []
artifacts: list[dict[str, Any]] = []
for block in content:
if isinstance(block, types.TextContent):
text_parts.append(block.text)
continue
data_url = _image_block_data_url(block, types)
if data_url is not None:
stored = self._store_image_block(data_url, arguments)
if stored is not None:
artifacts.append(stored)
else:
text_parts.append("(MCP tool returned an image that could not be stored)")
continue
text_parts.append(str(block))
if artifacts:
return _mcp_image_tool_result(text_parts, artifacts)
return "\n".join(text_parts) or "(no output)"
def _store_image_block(
self, data_url: str, arguments: Mapping[str, Any]
) -> dict[str, Any] | None:
"""Persist one image data URL as an artifact; return its metadata or None."""
from nanobot.utils.artifacts import ArtifactError, store_generated_image_artifact
try:
return store_generated_image_artifact(
data_url,
prompt=str(arguments.get("prompt") or ""),
model=str(arguments.get("model") or ""),
save_dir="generated",
provider=f"mcp:{self._server_name}",
)
except (ArtifactError, OSError) as exc:
logger.warning(
"MCP tool '{}' returned an image that could not be stored: {}",
self._name,
exc,
)
return None
class MCPResourceWrapper(_MCPWrapperBase):
"""Wraps an MCP resource URI as a read-only nanobot Tool."""
+63
View File
@@ -1,8 +1,10 @@
from __future__ import annotations
import asyncio
import json
import sys
from contextlib import asynccontextmanager
from pathlib import Path
from types import ModuleType, SimpleNamespace
import httpx
@@ -36,6 +38,12 @@ class _FakeBlobResourceContents:
self.blob = blob
class _FakeImageContent:
def __init__(self, data: str, mime_type: str = "image/png") -> None:
self.data = data
self.mimeType = mime_type
@pytest.fixture
def fake_mcp_runtime() -> dict[str, object | None]:
return {"session": None}
@@ -50,6 +58,7 @@ def _fake_mcp_module(
TextContent=_FakeTextContent,
TextResourceContents=_FakeTextResourceContents,
BlobResourceContents=_FakeBlobResourceContents,
ImageContent=_FakeImageContent,
)
class _FakeStdioServerParameters:
@@ -295,6 +304,60 @@ async def test_execute_returns_text_blocks() -> None:
assert result == "hello\n42"
# Smallest valid 1x1 PNG, base64 without the data: prefix.
_PNG_B64 = (
"iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mP8"
"/x8AAwMCAO+/p9sAAAAASUVORK5CYII="
)
@pytest.mark.asyncio
async def test_execute_persists_image_block_as_artifact(tmp_path: Path) -> None:
from nanobot.config.loader import set_config_path
set_config_path(tmp_path / "config.json")
async def call_tool(_name: str, arguments: dict) -> object:
return SimpleNamespace(
content=[
_FakeTextContent("here you go"),
_FakeImageContent(_PNG_B64, "image/png"),
]
)
wrapper = _make_wrapper(SimpleNamespace(call_tool=call_tool))
result = await wrapper.execute(prompt="a cat", model="sdxl")
payload = json.loads(result)
assert payload["text"] == "here you go"
assert len(payload["artifacts"]) == 1
artifact = payload["artifacts"][0]
assert artifact["mime"] == "image/png"
assert artifact["prompt"] == "a cat"
assert artifact["provider"] == "mcp:test"
assert Path(artifact["path"]).is_file()
# The base64 payload must NOT leak into the model-facing result.
assert _PNG_B64 not in result
assert "message tool" in payload["next_step"]
@pytest.mark.asyncio
async def test_execute_notes_unstorable_image_block(tmp_path: Path) -> None:
from nanobot.config.loader import set_config_path
set_config_path(tmp_path / "config.json")
async def call_tool(_name: str, arguments: dict) -> object:
return SimpleNamespace(content=[_FakeImageContent("not-valid-base64!!", "image/png")])
wrapper = _make_wrapper(SimpleNamespace(call_tool=call_tool))
result = await wrapper.execute()
assert result == "(MCP tool returned an image that could not be stored)"
@pytest.mark.asyncio
async def test_execute_returns_timeout_message() -> None:
async def call_tool(_name: str, arguments: dict) -> object: