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[MCPServer] Optional ResourcesAsTools support ala FastMCP

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評估

難度
4/5
預估耗時
3-5 天
新手友好度
45/100
Issue 類型
功能
描述清晰度
描述清楚
活躍度
活躍
技術堆疊
python
領域
api, backend, devtools

研究方向

Look at the MCP server implementation in the python-sdk, particularly how resources and tools are registered and exposed. Examine FastMCP's ResourcesAsTools transform for reference. The work involves adding a new transform class, modifying tool generation logic, and ensuring compatibility with existing resource definitions. Start by understanding the server's resource and tool handling in the SDK's core modules.

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描述

Description

As per FastMCP's documentation:

Some MCP clients only support tools. They cannot list or read resources directly because they lack resource protocol support.

An example of this is Cursor.

A workaround for this is that FastMCP provides the ResourcesAsTools transform to bridge this gap by exposing list_resources and read_resource as tools.

It would be great if we support this feature here. Would love to open & scope a PR here if it's something we should support.

Additional Implementation Considerations

However, the above still requires tool-only clients (and the LLM using them) to:

  1. Call list_resources to discover available resources/templates.
  2. Identify the relevant URI or URI template.
  3. Construct the resource URI manually for templates.
  4. Call read_resource with that URI.

This is particularly awkward for resource templates, where the parameters are already known by the resource definition but are not exposed as a tool input schema.

For example:

@mcp.resource("user://{user_id}/profile")
def user_profile(user_id: str) -> str:
    ...

A tool-only client currently has to discover the template and construct:

user://42/profile

before calling read_resource.

It would be great if ResourcesAsTools could optionally expose each resource and resource template as an individual tool.

For example:

@mcp.resource("config://app")
def app_config() -> str:
    ...

@mcp.resource("user://{user_id}/profile")
def user_profile(user_id: str) -> str:
    ...

mcp.add_transform(ResourcesAsTools(mcp, individual_tools=True))

could expose tools resembling:

app_config()
user_profile(user_id: str)

The generated tools would:

  • Reuse the resource's name, description, MIME type, and other metadata where appropriate.
  • Derive their input schema from the resource template parameters.
  • Internally resolve/read the corresponding resource.
  • Preserve the resource URI in the tool result where possible.
  • Continue to respect the server's existing middleware, authorization, visibility, and other resource-level behavior.

This would make resources much more natural to consume from clients that only support tools/list / tools/call, while keeping the existing ResourcesAsTools behavior available for applications that prefer the generic list_resources / read_resource interface.

Example

Given:

@mcp.resource("data://{dataset}/{year}")
def dataset(dataset: str, year: int) -> str:
    ...

a generated tool could look conceptually like:

{
  "name": "dataset",
  "description": "...",
  "inputSchema": {
    "type": "object",
    "properties": {
      "dataset": {"type": "string"},
      "year": {"type": "integer"}
    },
    "required": ["dataset", "year"]
  }
}

The client could then simply call:

await client.call_tool(
    "dataset",
    {"dataset": "election_results", "year": 2022}
)

without needing to know how the underlying resource URI is constructed.

Alternatives considered

If maintainer's want to support this, the existing list_resources + read_resource approach works, but it exposes the resource protocol's URI-oriented abstraction directly to the model. Generating tools would instead let tool-only clients consume the same resources through the interface they already understand.

Proposed Scope

We should PR iteratively:

  1. Add FastMCP-stype list_resources and read_resource tools.
  2. Optional Add individual_tool=True. This allows for one tool per resource/template with an InputSchema.

Other

  • Willing to submit PR
  • AI Assistance (Cursor)

References

No response

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Python
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