Skip to content

MCP text/plain resource.blob results reach the model as empty output #4916

Description

@kszobi

Describe the bug

When an MCP tool returns a successful embedded resource containing valid base64-encoded
UTF-8 text in resource.blob with mimeType: "text/plain", Copilot CLI does not expose
that text to the model. The model receives empty or unusable tool output and cannot quote
the returned nonce.

Two control representations of the same kind of text work:

MCP result representation Result
Direct { type: "text", text: ... } Model receives usable text and can quote the nonce
Embedded resource.text Model receives usable text and can quote the nonce
Embedded resource.blob with mimeType: "text/plain" Tool succeeds, but the model cannot read the nonce

This is not specific to large output or to one model. It reproduces with a tiny randomized
UTF-8 string and with both GPT-6 Astra and GPT-5.6 Sol.

A fresh run on Copilot CLI 1.0.87-0 reproduced the failure on both models. The direct
text and resource.text controls remained usable.

Public SDK source shows the relevant representation boundary:
convertMcpCallToolResult
appends resource.text to textResultForLlm, while every resource.blob is placed in
binaryResultsForLlm as a resource, regardless of MIME type. This establishes that
resource.text and resource.blob enter different result channels before provider
serialization; the textual blob is not subsequently delivered as usable model input.

The MCP schema permits BlobResourceContents to carry the resource's optional MIME type
without restricting it to image formats:
ResourceContents / BlobResourceContents.

Affected version

GitHub Copilot CLI 1.0.87-0

Steps to reproduce the behavior

  1. Save the following dependency-free Node.js stdio MCP server as
    mcp-text-blob-repro.mjs:
mcp-text-blob-repro.mjs
import { randomUUID } from "node:crypto";
import { createInterface } from "node:readline";

const tools = [
  {
    name: "direct_text",
    description: "Return a unique UTF-8 nonce as ordinary MCP text content.",
    inputSchema: { type: "object", properties: {}, additionalProperties: false },
  },
  {
    name: "resource_text",
    description: "Return a unique UTF-8 nonce in an embedded resource.text field.",
    inputSchema: { type: "object", properties: {}, additionalProperties: false },
  },
  {
    name: "resource_blob",
    description:
      "Return a unique UTF-8 nonce as base64 resource.blob with mimeType text/plain.",
    inputSchema: { type: "object", properties: {}, additionalProperties: false },
  },
];

function write(message) {
  process.stdout.write(`${JSON.stringify(message)}\n`);
}

function toolResult(name) {
  const nonce = process.env.REPRO_NONCE || randomUUID();
  const expected = `${name}:${nonce}`;
  process.stderr.write(`[repro] ${name} expected: ${expected}\n`);

  if (name === "direct_text") {
    return {
      content: [{ type: "text", text: expected }],
      isError: false,
    };
  }

  if (name === "resource_text") {
    return {
      content: [{
        type: "resource",
        resource: {
          uri: "memory://copilot-text-blob-repro/resource-text.txt",
          mimeType: "text/plain",
          text: expected,
        },
      }],
      isError: false,
    };
  }

  if (name === "resource_blob") {
    return {
      content: [{
        type: "resource",
        resource: {
          uri: "memory://copilot-text-blob-repro/resource-blob.txt",
          mimeType: "text/plain",
          blob: Buffer.from(expected, "utf8").toString("base64"),
        },
      }],
      isError: false,
    };
  }

  throw new Error(`Unknown tool: ${name}`);
}

const input = createInterface({ input: process.stdin, crlfDelay: Infinity });

input.on("line", (line) => {
  if (!line.trim()) return;

  let request;
  try {
    request = JSON.parse(line);
  } catch {
    return;
  }

  if (request.id === undefined) return;

  try {
    let result;
    switch (request.method) {
      case "initialize":
        result = {
          protocolVersion: request.params?.protocolVersion ?? "2025-06-18",
          capabilities: { tools: {} },
          serverInfo: { name: "copilot-text-blob-repro", version: "1.0.0" },
        };
        break;
      case "ping":
        result = {};
        break;
      case "tools/list":
        result = { tools };
        break;
      case "tools/call":
        result = toolResult(request.params?.name);
        break;
      default:
        write({
          jsonrpc: "2.0",
          id: request.id,
          error: { code: -32601, message: `Method not found: ${request.method}` },
        });
        return;
    }

    write({ jsonrpc: "2.0", id: request.id, result });
  } catch (error) {
    write({
      jsonrpc: "2.0",
      id: request.id,
      error: {
        code: -32602,
        message: error instanceof Error ? error.message : String(error),
      },
    });
  }
});
  1. In the same directory, save this as .mcp.json:
{
  "mcpServers": {
    "text-blob-repro": {
      "type": "stdio",
      "command": "node",
      "args": ["./mcp-text-blob-repro.mjs"],
      "env": {
        "REPRO_NONCE": "6f76fba4-4639-4ee2-8e95-c6cdd2e5b80d"
      },
      "tools": ["*"]
    }
  }
}
  1. From that directory, run these three commands. --available-tools prevents the model
    from reading .mcp.json or using another tool to discover the configured nonce:
copilot -p 'Call the direct_text tool exactly once. Return only the UUID suffix after the colon, with no explanation.' `
  --model gpt-5.6-sol `
  --additional-mcp-config '@.mcp.json' `
  --disable-builtin-mcps `
  --available-tools text-blob-repro-direct_text `
  --allow-all-tools
copilot -p 'Call the resource_text tool exactly once. Return only the UUID suffix after the colon, with no explanation.' `
  --model gpt-5.6-sol `
  --additional-mcp-config '@.mcp.json' `
  --disable-builtin-mcps `
  --available-tools text-blob-repro-resource_text `
  --allow-all-tools
copilot -p 'Call the resource_blob tool exactly once. Return only the UUID suffix after the colon, with no explanation. If no content is visible, reply exactly ATTACHMENT_UNAVAILABLE.' `
  --model gpt-5.6-sol `
  --additional-mcp-config '@.mcp.json' `
  --disable-builtin-mcps `
  --available-tools text-blob-repro-resource_blob `
  --allow-all-tools

Observed:

  • direct_text: 6f76fba4-4639-4ee2-8e95-c6cdd2e5b80d
  • resource_text: 6f76fba4-4639-4ee2-8e95-c6cdd2e5b80d
  • resource_blob: tool execution succeeds, but the nonce is absent from model-visible
    output and the model returns ATTACHMENT_UNAVAILABLE.

Replacing --model gpt-5.6-sol with --model gpt-6-astra reproduces the
resource_blob failure.

Expected behavior

For a successful embedded resource with an allowlisted textual MIME type such as
text/plain, Copilot CLI should make valid decoded UTF-8 content available to the model
through the normal text-result path (including the existing bounded large-output handling).

If the content cannot be safely decoded or supported, the tool result should fail
explicitly or contain a clear model-visible diagnostic. A successful tool execution should
not silently become empty model-visible output while usable text is present.

Additional context

A possible fix direction, rather than a required implementation:

  1. Base64-decode only explicitly allowlisted textual MIME types.
  2. Enforce a decoded-size cap and strict UTF-8 validation.
  3. Route valid decoded text through textResultForLlm or an equivalent supported
    model-visible text/file path.
  4. Keep binary attachment handling for MIME types and providers that support it.
  5. Apply the same normalization to native MCP and SDK/external-tool results.
  6. Add integration coverage for direct text, resource.text, and text/plain
    resource.blob across both provider/model paths.

Activity

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Metadata

Metadata

Assignees

No one assigned

    Labels

    Type

    Projects

    No projects

      Milestone

      No milestone

      Relationships

      None yet

      Development

      No branches or pull requests

      Issue actions