> ## Documentation Index > Fetch the complete documentation index at: https://docs.langbot.app/llms.txt > Use this file to discover all available pages before exploring further. # Component: Tool LangBot's built-in Local Agent calls tools to interact with the outside world during execution. Currently, adding tools is supported through both plugins and MCP. ## Adding Tool Components A single plugin can contain any number of tools. Execute the command `lbp comp Tool` in the plugin directory and follow the prompts to enter the tool configuration. ```bash theme={null} ➜ HelloPlugin > lbp comp Tool Generating component Tool... Tool name: get_weather_alerts Tool description: Get weather alerts for a US state. Component Tool generated successfully. 组件 Tool 生成成功。 ``` This will generate `get_weather_alerts.yaml` and `get_weather_alerts.py` files in the `components/tools/` directory. The `.yaml` file defines the basic information for the tool, and the `.py` file is the tool handler: ```bash theme={null} ➜ HelloPlugin > tree ... ├── components │ ├── __init__.py │ └── tools │ ├── __init__.py │ ├── get_weather_alerts.py │ └── get_weather_alerts.yaml ... ``` ## Manifest File: Tool ```yaml theme={null} apiVersion: v1 # Do not modify kind: Tool # Do not modify metadata: name: get_weather_alerts # Tool name, for LLM recognition label: en_US: GetWeatherAlerts # Tool display name, shown in LangBot UI, supports multilingual zh_Hans: GetWeatherAlerts description: en_US: 'Get weather alerts for a US state.' # Tool description, shown in LangBot UI, supports multilingual. Optional zh_Hans: '获取美国某个州的天气预警' spec: parameters: [] # Tool parameters, values generated by LLM based on conversation context llm_prompt: 'Get weather alerts for a US state.' # Tool prompt, for LLM to determine whether to call this tool execution: python: path: get_weather_alerts.py # Tool handler, do not modify attr: GetWeatherAlerts # Tool handler class name, matches the class name in get_weather_alerts.py ``` ## Plugin Processing The following code is generated by default (`components/tools/.py`). You need to implement the calling and return logic for this tool in the `call` method of the `GetWeatherAlerts` class. ```python theme={null} # Auto generated by LangBot Plugin SDK. # Please refer to https://docs.langbot.app/en/plugin/dev/tutor.html for more details. from __future__ import annotations from typing import Any from langbot_plugin.api.definition.components.tool.tool import Tool from langbot_plugin.api.entities.builtin.provider import session as provider_session class GetWeatherAlerts(Tool): async def call(self, params: dict[str, Any], session: provider_session.Session, query_id: int) -> str: """Fill your tool code here""" return {} ``` In the `call` method, implement this tool: The weather retrieval tool example comes from MCP's [Server Writing Example](https://modelcontextprotocol.io/quickstart/server). ```python theme={null} from __future__ import annotations from typing import Any from langbot_plugin.api.definition.components.tool.tool import Tool from langbot_plugin.api.entities.builtin.provider import session as provider_session import httpx # Constants NWS_API_BASE = "https://api.weather.gov" USER_AGENT = "weather-app/1.0" async def make_nws_request(url: str) -> dict[str, Any] | None: """Make a request to the NWS API with proper error handling.""" headers = { "User-Agent": USER_AGENT, "Accept": "application/geo+json" } async with httpx.AsyncClient() as client: try: response = await client.get(url, headers=headers, timeout=30.0) response.raise_for_status() return response.json() except Exception: return None def format_alert(feature: dict) -> str: """Format an alert feature into a readable string.""" props = feature["properties"] return f""" Event: {props.get('event', 'Unknown')} Area: {props.get('areaDesc', 'Unknown')} Severity: {props.get('severity', 'Unknown')} Description: {props.get('description', 'No description available')} Instructions: {props.get('instruction', 'No specific instructions provided')} """ class GetWeatherAlerts(Tool): async def call(self, params: dict[str, Any], session: provider_session.Session, query_id: int) -> str: """Fill your tool code here""" state = params.get("state", "CA") url = f"{NWS_API_BASE}/alerts/active/area/{state}" data = await make_nws_request(url) if not data or "features" not in data: return "Unable to fetch alerts or no alerts found." if not data["features"]: return "No active alerts for this state." alerts = [format_alert(feature) for feature in data["features"]] return "\n---\n".join(alerts) ``` In this tool, we need to get the `state` parameter from `params` and call the NWS API to get weather alerts for that state, so we need to define the `state` parameter in the `parameters` of the manifest file. The `parameters` format follows [JSON Schema](https://json-schema.org/docs), is supported by [OpenAI Function Calling feature](https://platform.openai.com/docs/guides/function-calling#defining-functions), and its root type is fixed as `type: object`. Please add parameters in `properties` and add required parameter descriptions in `required`. ```yaml theme={null} ... spec: parameters: type: object # Do not modify properties: # Do not modify, add parameters here state: type: string description: 'Two-letter US state code (e.g. CA, NY)' required: # Add required parameter descriptions here - state ... ``` This tool also uses the `httpx` library, so we need to add the `httpx` dependency in `requirements.txt` in the plugin directory. ```txt theme={null} # HelloPlugin/requirements.txt langbot-plugin # Already exists by default httpx ``` Now execute the command `lbp run` in the plugin directory to start debugging. Configure a model that supports tool calling in LangBot and select to use that model on the corresponding pipeline to use this tool. ## What's Next You have learned the basic usage of tools. Next, you can: * Check out [Plugin Common APIs](/en/plugin/dev/apis/common)