modelcontextprotocol / modelcontextprotocol/python-sdk

McpError is not pickle-safe and fails to unpickle

Open Beginner friendly
#2,431 9 comments 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

bug fix proposed P2 ready for work
Dominant language
Python
Stars
24.3k
Forks
4k
Avg merge
1d 1h
Merged PRs (30d)
31

Description

Initial Checks
Description

Summary

mcp.shared.exceptions.McpError does not survive a normal cloudpickle.dumps() / cloudpickle.loads() round-trip.

The failure appears to come from McpError.__init__ expecting an ErrorData object, while exception unpickling reconstructs it with a plain string from Exception.args.

This is surfacing for us through background task execution, but the bug reproduces without Docket/FastMCP task machinery.

Actual behavior

Unpickling fails with:

AttributeError: 'str' object has no attribute 'message'

Traceback points at McpError.__init__:

class McpError(Exception):
    error: ErrorData

    def __init__(self, error: ErrorData):
        super().__init__(error.message)
        self.error = error

Expected behavior

McpError(ErrorData(...)) should round-trip through pickle/cloudpickle without crashing.

At minimum, this should work:

  • serialize McpError
  • deserialize McpError
  • preserve the message
  • preserve the error payload, or at least degrade safely without raising during unpickle

Suspected root cause

McpError stores error.message in Exception.args via super().__init__(error.message).

On unpickle, exception reconstruction uses args, so McpError is effectively reconstructed as:

McpError("Authentication Required")

But McpError.__init__ assumes error is always an ErrorData, so it does:

error.message

which crashes for str.

Suggested fix

McpError likely needs to be pickle-safe by design. Any of these would probably fix it:

  1. Make __init__ accept both ErrorData and str, normalizing str into an ErrorData.
  2. Implement __reduce__ so pickle reconstructs using the full ErrorData.
  3. Ensure constructor args and exception state are aligned with standard exception pickling behavior.

A robust version would probably do both __reduce__ and tolerant initialization.

Notes

This bug is easy to misattribute to cloudpickle or task runners, but the reproducer above shows it is local to McpError itself.

Example Code
from importlib.metadata import version

import cloudpickle
from mcp.shared.exceptions import McpError
from mcp.types import ErrorData


print("Versions:")
print(f"  mcp={version('mcp')}")
print(f"  cloudpickle={version('cloudpickle')}")

original = McpError(ErrorData(code=-32600, message="Authentication Required"))

print("\nOriginal exception:")
print(f"  type={type(original).__name__}")
print(f"  str={str(original)!r}")
print(f"  error_type={type(original.error).__name__}")
print(f"  error_message={original.error.message!r}")

payload = cloudpickle.dumps(original)

print("\nUnpickling:")
restored = cloudpickle.loads(payload)
print(f"  restored_type={type(restored).__name__}")
print(f"  restored_args={restored.args!r}")
print(f"  restored_error={getattr(restored, 'error', None)!r}")
Python & MCP Python SDK
- `mcp==1.26.0`
- `fastmcp==3.2.3`
- `cloudpickle==3.1.2`
- Python 3.13

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start at McpError in mcp.shared.exceptions and reproduce the failure with the supplied cloudpickle example. Check how Exception.args reconstructs the exception during unpickling, then verify that an McpError round-trip preserves its message and error payload or degrades without raising.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
backend
Issue type
Bug
Difficulty
2/5
Estimated time
1-3 hours
Activity status
Active
Clarity
Mostly clear
Newbie friendliness
74/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.