Mcp

bench get-app https://github.com/frappe/mcp

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# Frappe MCP Frappe MCP allows your Frappe Framework app to function as a [Streamable HTTP MCP server](https://modelcontextprotocol.io/specification/2025-06-18/basic/transports#streamable-http). ```python # app/app/mcp.py import frappe_mcp mcp = frappe_mcp.MCP("todo-mcp") @mcp.tool() def fetch_todos(username: str): ... @mcp.tool() def mark_done(name: str): ... # MCP endpoint at: http:///api/method/app.mcp.handle_mcp @mcp.register() def handle_mcp(): ... ``` > [!NOTE] > > **Why not use the official Python SDK?** > > The official Python SDK only supports async Python, i.e. it assumes that your > server is an ASGI server. > > Frappe Framework is not async, it makes use of Werkzeug, a WSGI server, and so > a from scratch implementation was needed. > [!IMPORTANT] > > Frappe MCP is in a highly experimental state, there will be bugs, breaking > changes and large updates. Mostly without notice. _On GitHub, click the Index button on the top right to view the index._ ## Installation Using PIP: ```bash pip install frappe-mcp ``` Using UV: ```bash uv add frappe-mcp ``` ## Limitations Frappe MCP is yet in its infancy, as of now it **only supports** Tools. Remaining server features such as resources, prompts, tool streaming using SSE will be added as needed. ## Auth If you are using a version of the Framework having the OAuth2 updates ([frappe#33188](https://github.com/frappe/frappe/pull/33188)) then using Frappe MCP with it should be pretty straight forward. You can view this video to check out how to set up Auth on the MCP Inspector. https://github.com/user-attachments/assets/a1783a36-7bea-4361-8c7b-bdbb9789877b If your version does not contain these updates, you will have to register an OAuth Client on your Framework instance for the MCP client. You can check the [docs](https://docs.frappe.io/framework/oauth2) for this. ## Documentation Frappe MCP is fairly straightforward to use. Most of the MCP specific heavy lifting is handled for you. ### Basic Usage To use `frappe-mcp` you first create an instance of the `mcp` object: ```python # app/app/mcp.py (same dir as hooks.py) import frappe_mcp mcp = frappe_mcp.MCP("your-app-mcp") ``` Each instance of an `MCP` object can be used to register a single MCP endpoint. You can create multiple of these objects if you need to serve multiple MCP endpoints for instance to group functionality. #### Register tools with `@mcp.tool` You use the instaniated object i.e. `mcp` to register tools: ```python # app/app/tools/tools.py from app.mcp import mcp @mcp.tool() def tool_name(a: int, b: str): """Description of what the tool does Args: a: Description for arg `a`. b: Description for arg `b`. """ ... # tool body return value ``` > [!TIP] > > Using Google style docstrings and type annotations like in the example above > allows Frappe MCP to extract the `inputSchema` for the tool without any additional > configuration. If needed, you can manually provide the `inputSchema` and other meta data like annotations. Check the [Tools](#tools) section for more details. #### Register endpoint using `@mcp.register` You use the instantiated object to mark a function as the _entry point_ to your MCP server, i.e. the function endpoint will be where your MCP server is served from. ```python # app/app/mcp.py @mcp.register() def handle_mcp(): import app.tools.tools # ensures that your tools are registered ``` Once this is done, your MCP server should be serving at the REST endpoint for the method ([docs](https://docs.frappe.io/framework/user/en/api/rest#remote-method-calls)). In this case the endpoint when running locally would be: ``` http:///api/method/app.mcp.handle_mcp ``` > [!WARNING] > > The function body's **only purpose is to import files containing your tools**. > If this is not done your tools will not be loaded as Frappe MCP does not know where > your tools are located. > > If your tools are in the same file, or have been imported globally, you can > leave the function body empty. ### Tools You can register tools, in the following ways: 1. Using the `@mcp.tool` decorator 2. Using the `mcp.add_tool` method #### `@mcp.tool` decorator The `@mcp.tool` decorator registers a function as a tool that can be used by an LLM. The decorator accepts the following optional arguments: - `name` (optional `str`): The name of the tool. If not provided, the function's `__name__` will be used. - `description` (optional `str`): A description of what the tool does. If not provided, it will be extracted from the function's docstring. - `input_schema` (optional `dict`): The JSON schema for the tool's input. If not provided, it will be inferred from the function's signature and docstring. - `use_entire_docstring` (optional `bool`): If `True`, the entire docstring will be used as the tool's description. Otherwise, only the first section is used (i.e. no `Args`). Defaults to `False`. - `annotations` (optional `dict`): Additional context about the tool, such as validation information or examples of how to use it. This should be a dictionary conforming to the `ToolAnnotations` `TypedDict` structure. **Example:** ```python from frappe_mcp import ToolAnnotations, MCP mcp = MCP() annotations = ToolAnnotations( title="Get Current Weather", readOnlyHint=True, ) @mcp.tool(annotations=annotations) def get_current_weather(location: str, unit: str = "celsius"): '''Get the current weather in a given location.''' # ... implementation ... ``` #### `mcp.add_tool` method The `mcp.add_tool` method allows manually defining a tool, serving as an alternative to the `@mcp.tool` decorator. It takes a `Tool` object as an arg. **Example:** ```python from frappe_mcp import Tool, MCP mcp = MCP() def get_current_weather(location: str, unit: str = "celsius"): '''Get the current weather in a given location.''' # ... implementation ... # Create a tool object weather_tool = Tool( name="get_current_weather", description="...", input_schema={'type':'object', 'properties':{ ... }}, output_schema=None, annotations=None, fn=get_current_weather, ) # Add the tool to the MCP instance mcp.add_tool(weather_tool) ``` #### Tool Annotations The `ToolAnnotations` can be used to provide additional tool annotations defined by the MCP spec ([reference](https://modelcontextprotocol.io/docs/concepts/tools#tool-annotations)). ```python class ToolAnnotations(TypedDict, total=False): title: str | None readOnlyHint: bool | None destructiveHint: bool | None idempotentHint: bool | None openWorldHint: bool | None ``` #### Tool Definition The `Tool` object that is used when manually defining and registering a tool using `mcp.add_tool`. ```python class Tool(TypedDict): name: str description: str input_schema: dict[str, Any] output_schema: dict[str, Any] | None annotations: ToolAnnotations | None fn: Callable ``` #### Input Schema Input schema refers to the [JSON Schema](https://json-schema.org/understanding-json-schema/reference/type) definition that describes a tool's parameters. The following tool: ```python @mcp.tool() def tool_name(a: int, b: str = "default"): """Description of what the tool does Args: a: Description for arg `a`. b: Description for arg `b`. """ ... # tool body return value ``` will have this input schema: ```json { "type": "object", "properties": { "a": { "type": "integer", "description": "Description for arg `a`." }, "b": { "type": "string", "description": "Description for arg `b`." } }, "required": ["a"] } ``` This input schema is generated from the tool body automatically when using the decorator. ### MCP The `MCP` class is the main class for creating an MCP server. This class orchestrates the handling of JSON-RPC requests, manages a registry of available tools, and integrates with a WSGI server (like Frappe Framework) to expose MCP functionality. In a Frappe application, you would typically create a single instance of this class and use the `@mcp.register()` decorator on an API endpoint. Tools can be added using the `@mcp.tool()` decorator. For use in other Werkzeug-based servers, you can use the `mcp.handle()` method directly. #### `mcp.register` decorator This decorator is used in Frappe applications to designate a function as the entry point for MCP requests. It wraps the function with the necessary logic to handle JSON-RPC messages, including initializing the tool registry and routing requests to the appropriate handlers. The decorator accepts the following optional arguments: - `allow_guest` (optional `bool`): If `True`, allows unauthenticated access to the endpoint. Defaults to `False`. - `xss_safe` (optional `bool`): If `True`, response will not be sanitized for XSS. Defaults to `False`. **Example:** ```python # In app/mcp.py from frappe_mcp import MCP mcp = MCP(name="my-mcp-server") @mcp.register() def handle_mcp(): '''The entry point for MCP requests.''' # This function body is executed before request handling. # It's a good place to import modules that register tools. import app.tools ``` #### `mcp.handle` method This method directly processes a `werkzeug.Request` and returns a `werkzeug.Response`. It's the core request handling logic. This method can be used to integrate the MCP server into **any Werkzeug-based application** i.e. even if you're not using Frappe Framework, you can use this to handle MCP endpoints in your server. It accepts the following arguments: - `request`: The `werkzeug.Request` object containing the MCP request. - `response`: A `werkzeug.Response` object to be populated with the MCP response. It returns the populated `werkzeug.Response` object. ## CLI Frappe MCP comes with a handy CLI tool to help you verify that your MCP server is set up correctly. Its `check` command inspects your Frappe apps to ensure that `frappe_mcp` is being used correctly. This is also the default command, so you can run it with `frappe-mcp` or `frappe-mcp check`. It performs the following checks: - Verifies that it's running within a Frappe environment. - Finds all apps that are potentially using `frappe_mcp`. - For each app, it discovers MCP handlers. - It then checks the handlers and their tools for correctness. **Options:** - `--app`, `-a`': Check only a specific app. - `--verbose`, `-v`: Show detailed information such as the input schema. **Usage:** ```bash # After installing frappe-mcp and using it in your app # In your frappe bench dir so that you can use the cli source ./env/bin/activate # Check all apps that might be using Frappe MCP frappe-mcp # Check specific app with verbose output frappe-mcp check --app app_name --verbose ``` ## Testing against Inspector You can use the official [inspector](https://github.com/modelcontextprotocol/inspector) tool to verify if your MCP endpoints are being served correctly.  Make sure to: 1. Set **Transport** to **Streamable HTTP**. 2. Set **URL** to your MCP endpoint (you can use the CLI command `frappe-mcp check` to get it). 3. Navigate to Auth Settings then click on **Quick OAuth Flow** After this you'll be prompted to login and authorize the client after which you can use it to test out your MCP server. > [!NOTE] > > You may skip the final step by setting the `allow_guests` flag, i.e: > > ```python > @mcp.register(allow_guests=True) > def handle_mcp(): ... > ``` > > **This bypasses auth, so make sure you don't do this in production.**