Bug Description

When an MCP tool returns type: "resource" in its content array, OpenClaw incorrectly converts it to a (see attached image) placeholder instead of extracting the resource.text field.

Reproduction Steps

1. Configure QMD as the memory backend ("memory": { "backend": "qmd" })
2. Call the qmd__get tool via OpenClaw:

   {"name": "get", "arguments": {"file": "memory/2026-05-01.md"}}

3. The MCP server returns a valid EmbeddedResource:

   {
     "content": [
       {
         "type": "resource",
         "resource": {
           "uri": "qmd://memory-root-main/memory/2026-05-01.md",
           "mimeType": "text/markdown",
           "text": "# 2026-05-01\n\nSome markdown content here..."
         }
       }
     ]
   }

4. OpenClaw displays (see attached image) in the tool output instead of the markdown text.

Expected vs Actual Behavior

Root Cause Analysis (Source Code Level)

I traced the issue through the OpenClaw distribution bundle (2026.4.27). The problem is that the entire content pipeline lacks support for the MCP EmbeddedResource type.

1. contentToText ignores resource

File: dist/compaction-successor-transcript-BwDunTlM.js:581-585

function contentToText(content) {
  // ...
  return content.filter((part) => Boolean(part) && typeof part === "object")
    .filter((part) => (part.type === "text" || part.type === "input_text" || part.type === "output_text") && typeof part.text === "string")
    .map((part) => part.text).join("");
}

Only text / input_text / output_text are recognized. type: "resource" is silently filtered out, returning an empty string.

2. contentToOpenAIParts ignores resource

File: dist/compaction-successor-transcript-BwDunTlM.js:586-644

for (const part of content) {
  if ((part.type === "text" || part.type === "input_text" || part.type === "output_text") && typeof part.text === "string") {
    parts.push({ type: "input_text", text: part.text });
    continue;
  }
  if (!includeImages) continue;
  if (part.type === "image" && typeof part.data === "string") { /* ... */ }
  if (part.type === "input_image" && part.source && ...) { /* ... */ }
}

Only text and image/input_image are handled. resource is skipped, producing an empty parts array.

3. OpenAI transport falls back to placeholder

File: dist/openai-transport-stream-DwlW8wDu.js:634-649

} else if (msg.role === "toolResult") {
  const textResult = msg.content.filter((item) => item.type === "text").map((item) => item.text).join("\n");
  const hasImages = msg.content.some((item) => item.type === "image");
  // ...
  output: hasImages && model.input.includes("image")
    ? [...]
    : sanitizeTransportPayloadText(textResult || "(see attached image)")
}

• textResult is empty (resource is not text)
• hasImages is false (resource is not image)
• Falls through to sanitizeTransportPayloadText("" || "(see attached image)")

4. Anthropic transport has the same issue

File: dist/provider-stream-CQzDRxyR.js:104-126

function convertContentBlocks(content) {
  if (!content.some((item) => item.type === "image"))
    return sanitizeNonEmptyTransportPayloadText(content.map((item) => "text" in item ? item.text : "").join("\n"));
  // ...
  if (!blocks.some((block) => block.type === "text"))
    blocks.unshift({ type: "text", text: "(see attached image)" });
}

Non-text content is treated as image, and when no text blocks exist, the placeholder is inserted.

Proposed Fix

Add resource type handling to the content pipeline:

// In contentToText
if (part.type === "resource" && part.resource && typeof part.resource.text === "string") {
  return part.resource.text;
}

// In contentToOpenAIParts
if (part.type === "resource" && part.resource && typeof part.resource.text === "string") {
  parts.push({ type: "input_text", text: part.resource.text });
  continue;
}

Additionally, the transport layer should not blindly fall back to (see attached image) for unknown content types. It should either extract text from known types or pass through an error/unknown-type indicator.

Environment

• OpenClaw version: 2026.4.27
• Platform: macOS
• Memory backend: QMD
• API provider: Xiaomi MiMo (openai-completions)
• Node.js: v22.22.2