Fastmcp tool parameter parsing type error

[weester-yan]

When I define the tool parameter as string, the parameter parsing function of fastmcp parses the numeric string I pass in into a numeric value.

• mcp/server/fastmcp/utilities/func_metadata.py

    def pre_parse_json(self, data: dict[str, Any]) -> dict[str, Any]:
        """Pre-parse data from JSON.

        Return a dict with same keys as input but with values parsed from JSON
        if appropriate.

        This is to handle cases like `["a", "b", "c"]` being passed in as JSON inside
        a string rather than an actual list. Claude desktop is prone to this - in fact
        it seems incapable of NOT doing this. For sub-models, it tends to pass
        dicts (JSON objects) as JSON strings, which can be pre-parsed here.
        """
        new_data = data.copy()  # Shallow copy
        for field_name, field_info in self.arg_model.model_fields.items():
            import logging
            logging.info((field_name, field_info))
            logging.info("before parse: ", new_data)
            if field_name not in data.keys():
                continue
            if isinstance(data[field_name], str):
                try:
                    pre_parsed = json.loads(data[field_name])
                except json.JSONDecodeError:
                    continue  # Not JSON - skip
                if isinstance(pre_parsed, str):
                    # This is likely that the raw value is e.g. `"hello"` which we
                    # Should really be parsed as '"hello"' in Python - but if we parse
                    # it as JSON it'll turn into just 'hello'. So we skip it.
                    continue
                new_data[field_name] = pre_parsed
             logging.info("after parse: ", new_data)
        assert new_data.keys() == data.keys()
        return new_data

test output:

video-1  | ('cid', FieldInfo(annotation=str, required=True, description='xxx.'))
video-1  | before parse: {'cid': '1.2'}
video-1  | after parse: {'cid': 1.2}
video-1  | Error calling tool: Error executing tool getinfo: 1 validation error for getinfoArguments
video-1  | cid
video-1  |   Input should be a valid string [type=string_type, input_value=1.2, input_type=float]
video-1  |     For further information visit https://errors.pydantic.dev/2.10/v/string_type

Here, json.loads will parse the incoming string "1.2" into the floating point number 1.2

So, when I use pydantic to define parameters in tool, a validation error occurs

from pydantic import validate_call, Field

@server.tool(description="xxx")
@validate_call
async def getinfo(
        cid: str = Field(..., description="xxx."),
) -> bool | None:

Is my understanding correct?

[msamon-nrg]

I experienced this same issue with this function signature:

def tool(account_id: str):
    ...

It was resolved once I updated it to def tool(account_id: int). I think you've identified the origin of the bug correctly. I believe what's happening is the json.loads(data[field_name]) is converting number strings to numbers in cases where data[field_name] is a number string. This is expected behavior of the json.loads method. For example:

>>> import json
>>> json.loads("1.2")
1.2

[dsp-ant]

Can you add more information, such as the version of the SDK?

[weester-yan]

I'm using version 1.3.0, but I saw that the latest version seems to have fixed this problem.

def pre_parse_json(self, data: dict[str, Any]) -> dict[str, Any]:
        """Pre-parse data from JSON.

        Return a dict with same keys as input but with values parsed from JSON
        if appropriate.

        This is to handle cases like `["a", "b", "c"]` being passed in as JSON inside
        a string rather than an actual list. Claude desktop is prone to this - in fact
        it seems incapable of NOT doing this. For sub-models, it tends to pass
        dicts (JSON objects) as JSON strings, which can be pre-parsed here.
        """
        new_data = data.copy()  # Shallow copy
        for field_name, _field_info in self.arg_model.model_fields.items():
            if field_name not in data.keys():
                continue
            if isinstance(data[field_name], str):
                try:
                    pre_parsed = json.loads(data[field_name])
                except json.JSONDecodeError:
                    continue  # Not JSON - skip
                ___________________________
                if isinstance(pre_parsed, str | int | float):
                    # This is likely that the raw value is e.g. `"hello"` which we
                    # Should really be parsed as '"hello"' in Python - but if we parse
                    # it as JSON it'll turn into just 'hello'. So we skip it.
                    continue
                ___________________________
                new_data[field_name] = pre_parsed
        assert new_data.keys() == data.keys()
        return new_data

Thank you very much for your reply.

[davidlin2k]

I suspect the problem is coming from this, I've also encountered similar problem

https://docs.pydantic.dev/latest/concepts/strict_mode/

[davidlin2k]

Seems like there is a PR trying to address this

#350

[0kenx]

I can confirm the same bug. When client tries to call a functon of arg str and with a valid JSON string, it produces error:

2025-04-01T18:23:11.591Z [filesystem] [info] Message from client: {"method":"tools/call","params":{"name":"write_file","arguments":{"path":"t.json","content":"{\"id\": 7392, \"name\": \"RandomProject\", \"version\": \"1.2.3\", \"isActive\": true, \"metadata\": {\"createdAt\": \"2024-04-01T12:34:56Z\", \"tags\": [\"random\", \"test\", \"example\"], \"complexity\": 5.7}, \"users\": [{\"userId\": 1001, \"username\": \"john_doe\", \"email\": \"[email protected]\"}, {\"userId\": 1002, \"username\": \"jane_smith\", \"email\": \"[email protected]\"}], \"permissions\": {\"read\": true, \"write\": false, \"delete\": false}}"}},"jsonrpc":"2.0","id":20}
2025-04-01 18:23:11,595 - mcp.server.lowlevel.server - INFO - Processing request of type CallToolRequest
2025-04-01T18:23:11.602Z [filesystem] [info] Message from server: {"jsonrpc":"2.0","id":20,"result":{"content":[{"type":"text","text":"Error executing tool write_file: 1 validation error for write_fileArguments\ncontent\n  Input should be a valid string [type=string_type, input_value={'id': 7392, 'name': 'Ran...False, 'delete': False}}, input_type=dict]\n    For further information visit https://errors.pydantic.dev/2.10/v/string_type"}],"isError":true}}