# How to integrate Openweather api MCP with LlamaIndex

```json
{
  "title": "How to integrate Openweather api MCP with LlamaIndex",
  "toolkit": "Openweather api",
  "toolkit_slug": "openweather_api",
  "framework": "LlamaIndex",
  "framework_slug": "llama-index",
  "url": "https://composio.dev/toolkits/openweather_api/framework/llama-index",
  "markdown_url": "https://composio.dev/toolkits/openweather_api/framework/llama-index.md",
  "updated_at": "2026-05-12T10:20:57.968Z"
}
```

## Introduction

This guide walks you through connecting Openweather api to LlamaIndex using the Composio tool router. By the end, you'll have a working Openweather api agent that can get current weather in paris right now, show 5-day forecast for san francisco, check today's air quality in new delhi through natural language commands.
This guide will help you understand how to give your LlamaIndex agent real control over a Openweather api account through Composio's Openweather api MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Openweather api with

- [ChatGPT](https://composio.dev/toolkits/openweather_api/framework/chatgpt)
- [OpenAI Agents SDK](https://composio.dev/toolkits/openweather_api/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/openweather_api/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/openweather_api/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/openweather_api/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/openweather_api/framework/codex)
- [Cursor](https://composio.dev/toolkits/openweather_api/framework/cursor)
- [VS Code](https://composio.dev/toolkits/openweather_api/framework/vscode)
- [OpenCode](https://composio.dev/toolkits/openweather_api/framework/opencode)
- [OpenClaw](https://composio.dev/toolkits/openweather_api/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/openweather_api/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/openweather_api/framework/cli)
- [Google ADK](https://composio.dev/toolkits/openweather_api/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/openweather_api/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/openweather_api/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/openweather_api/framework/mastra-ai)
- [CrewAI](https://composio.dev/toolkits/openweather_api/framework/crew-ai)

## TL;DR

Here's what you'll learn:
- Set your OpenAI and Composio API keys
- Install LlamaIndex and Composio packages
- Create a Composio Tool Router session for Openweather api
- Connect LlamaIndex to the Openweather api MCP server
- Build a Openweather api-powered agent using LlamaIndex
- Interact with Openweather api through natural language

## What is LlamaIndex?

LlamaIndex is a data framework for building LLM applications. It provides tools for connecting LLMs to external data sources and services through agents and tools.
Key features include:
- ReAct Agent: Reasoning and acting pattern for tool-using agents
- MCP Tools: Native support for Model Context Protocol
- Context Management: Maintain conversation context across interactions
- Async Support: Built for async/await patterns

## What is the Openweather api MCP server, and what's possible with it?

The Openweather api MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Openweather api account. It provides structured and secure access to real-time, forecasted, and historical weather data, so your agent can fetch current conditions, deliver forecasts, analyze air quality, and perform location-based weather insights on your behalf.
- Current weather retrieval: Instantly get up-to-the-minute weather details for any city or geographic coordinate, including temperature, humidity, and wind.
- Five-day weather forecasting: Ask your agent for detailed 5-day forecasts in 3-hour intervals to plan events, travel, or outdoor activities.
- Air pollution and UV index analysis: Retrieve current, forecasted, and historical air pollution data, as well as UV index values, to monitor environmental quality for any location.
- Geocoding and reverse geocoding: Convert location names to coordinates or find city/state information from latitude and longitude, enabling location-aware weather queries.
- Radius-based weather search: Fetch weather conditions for all cities within a specified radius around a geographic point for broader regional analysis.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `OPENWEATHER_API_DELETE_WEATHER_STATION` | Delete Weather Station | Tool to delete a registered weather station. Use after identifying a station to remove. Returns confirmation message upon success. |
| `OPENWEATHER_API_GET5_DAY_FORECAST` | Get 5 Day Forecast | Tool to get a 5-day forecast every 3 hours (up to 40 UTC timestamps). Exactly one location identifier required per call: `q`, `id`, `zip`, or `lat`+`lon` pair. Use `city.timezone` offset to convert timestamps to local time before grouping into daily summaries. |
| `OPENWEATHER_API_GET_AIR_POLLUTION_CURRENT` | Get Current Air Pollution Data | Tool to fetch current air pollution data for a location. Use when you need real-time air quality details by latitude and longitude. |
| `OPENWEATHER_API_GET_AIR_POLLUTION_FORECAST` | Get Air Pollution Forecast | Tool to get forecasted air pollution data for a specific location. Use after confirming latitude and longitude. Forecast availability may be limited for remote or oceanic coordinates; verify response timestamps to confirm returned data represents a true forecast rather than a current snapshot. |
| `OPENWEATHER_API_GET_AIR_POLLUTION_HISTORY` | Get Air Pollution History | Tool to retrieve historical air pollution data. Use when you need past air quality levels for a specific latitude/longitude and time range. |
| `OPENWEATHER_API_GET_CIRCLE_CITY_WEATHER` | Get Circle City Weather | Tool to search for current weather data in cities around a geographic point. Use when you need to fetch weather within a radius circle after confirming latitude and longitude. |
| `OPENWEATHER_API_GET_CURRENT_WEATHER` | Get Current Weather | Tool to retrieve current weather data for a location. Use when you need up-to-the-minute weather info. Exactly one location identifier must be provided per call: either `q`, `id`, `zip`, or the pair `lat`+`lon`. Passing multiple identifiers causes errors or ambiguous matches. |
| `OPENWEATHER_API_GET_GEOCODING_BY_ZIP` | Get Geocoding by Zip Code | Tool to convert zip/post code into geographic coordinates. Use when you need latitude and longitude for a specific postal code. |
| `OPENWEATHER_API_GET_GEOCODING_DIRECT` | Get Direct Geocoding | Tool to convert a location name into geographic coordinates. Use when you need latitude and longitude for a given location after confirming the precise name. |
| `OPENWEATHER_API_GET_GEOCODING_REVERSE` | Get Reverse Geocoding | Tool to convert geographic coordinates into a location name. Use when you need city, state, and country info from latitude and longitude. |
| `OPENWEATHER_API_GET_STATION_MEASUREMENTS` | Get Station Measurements | Tool to retrieve aggregated measurements from a weather station with minute, hour, or day granularity. Use when you need historical weather data from a specific registered station. |
| `OPENWEATHER_API_GET_UV_INDEX` | Get Current UV Index | Tool to retrieve current UV index for a location. Use when you need up-to-the-minute UV index by latitude and longitude. |
| `OPENWEATHER_API_GET_UV_INDEX_FORECAST` | Get UV Index Forecast | Tool to retrieve UV index forecast for a specific location. Use when you need upcoming UV index values after confirming latitude and longitude. Returns up to 8 days of data. Data may be sparse or absent for ocean and remote locations; an empty response means no data available, not safe UV conditions. |
| `OPENWEATHER_API_GET_UV_INDEX_HISTORY` | Get UV Index History | Tool to retrieve historical UV index data for a specified location and time range. Use when you need to analyze past UV exposure trends after confirming coordinates and time period. |
| `OPENWEATHER_API_GET_WEATHER_MAP_TILE` | Get Weather Map Tile (2.0) | Tool to fetch Weather Maps 2.0 tile images. Use when you need dynamic weather layers at specific zoom and coordinates with advanced styling options. |
| `OPENWEATHER_API_GET_WEATHER_STATION` | Get Weather Station | Tool to get information about a specific weather station by its ID. Use when you need details about a particular station. |
| `OPENWEATHER_API_GET_WEATHER_STATIONS` | Get Weather Stations | Tool to list all weather stations added to your account. Use after setting up your OpenWeather API key. |
| `OPENWEATHER_API_GET_WEATHER_TRIGGERS` | Get Weather Triggers | Tool to retrieve weather triggers for specific conditions. Use after defining trigger criteria. |
| `OPENWEATHER_API_POST_ADD_WEATHER_STATION` | Add Weather Station | Tool to add a new weather station to your account. Use when you need to register a station before sending custom data. |
| `OPENWEATHER_API_POST_SUBMIT_STATION_MEASUREMENTS` | Submit Station Measurements | Tool to submit weather measurements from a registered station. Use when you need to send temperature, wind, pressure, humidity, or precipitation data for a station. |
| `OPENWEATHER_API_UPDATE_WEATHER_STATION` | Update Weather Station | Tool to update weather station details. Use when you need to modify the name, location, or external ID of an existing station. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Openweather api MCP server is an implementation of the Model Context Protocol that connects your AI agent to Openweather api. It provides structured and secure access so your agent can perform Openweather api operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 1. Prerequisites

Before you begin, make sure you have:
- Python 3.8/Node 16 or higher installed
- A Composio account with the API key
- An OpenAI API key
- A Openweather api account and project
- Basic familiarity with async Python/Typescript

### 1. Getting API Keys for OpenAI, Composio, and Openweather api

No description provided.

### 2. Installing dependencies

No description provided.
```python
pip install composio-llamaindex llama-index llama-index-llms-openai llama-index-tools-mcp python-dotenv
```

```typescript
npm install @composio/llamaindex @llamaindex/openai @llamaindex/tools @llamaindex/workflow dotenv
```

### 3. Set environment variables

Create a .env file in your project root:
These credentials will be used to:
- Authenticate with OpenAI's GPT-5 model
- Connect to Composio's Tool Router
- Identify your Composio user session for Openweather api access
```bash
OPENAI_API_KEY=your-openai-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id
```

### 4. Import modules

No description provided.
```python
import asyncio
import os
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()
```

```typescript
import "dotenv/config";
import readline from "node:readline/promises";
import { stdin as input, stdout as output } from "node:process";

import { Composio } from "@composio/core";

import { mcp } from "@llamaindex/tools";
import { agent as createAgent } from "@llamaindex/workflow";
import { openai } from "@llamaindex/openai";

dotenv.config();
```

### 5. Load environment variables and initialize Composio

No description provided.
```python
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set in the environment")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment")
```

```typescript
const OPENAI_API_KEY = process.env.OPENAI_API_KEY;
const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY;
const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID;

if (!OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set");
if (!COMPOSIO_API_KEY) throw new Error("COMPOSIO_API_KEY is not set");
if (!COMPOSIO_USER_ID) throw new Error("COMPOSIO_USER_ID is not set");
```

### 6. Create a Tool Router session and build the agent function

What's happening here:
- We create a Composio client using your API key and configure it with the LlamaIndex provider
- We then create a tool router MCP session for your user, specifying the toolkits we want to use (in this case, openweather api)
- The session returns an MCP HTTP endpoint URL that acts as a gateway to all your configured tools
- LlamaIndex will connect to this endpoint to dynamically discover and use the available Openweather api tools.
- The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent.
```python
async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["openweather_api"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")

    description = "An agent that uses Composio Tool Router MCP tools to perform Openweather api actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Openweather api actions.
    """
    return ReActAgent(tools=tools, llm=llm, description=description, system_prompt=system_prompt, verbose=True)
```

```typescript
async function buildAgent() {

  console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`);
  console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`);

  const composio = new Composio({
    apiKey: COMPOSIO_API_KEY,
    provider: new LlamaindexProvider(),
  });

  const session = await composio.create(
    COMPOSIO_USER_ID!,
    {
      toolkits: ["openweather_api"],
    },
  );

  const mcpUrl = session.mcp.url;
  console.log(`Composio Tool Router MCP URL: ${mcpUrl}`);

  const server = mcp({
    url: mcpUrl,
    clientName: "composio_tool_router_with_llamaindex",
    requestInit: {
      headers: {
        "x-api-key": COMPOSIO_API_KEY!,
      },
    },
    // verbose: true,
  });

  const tools = await server.tools();

  const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" });

  const agent = createAgent({
    name: "composio_tool_router_with_llamaindex",
        description : "An agent that uses Composio Tool Router MCP tools to perform actions.",
    systemPrompt:
      "You are a helpful assistant connected to Composio Tool Router."+
"Use the available tools to answer user queries and perform Openweather api actions." ,
    llm,
    tools,
  });

  return agent;
}
```

### 7. Create an interactive chat loop

No description provided.
```python
async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")
```

```typescript
async function chatLoop(agent: ReturnType<typeof createAgent>) {
  const rl = readline.createInterface({ input, output });

  console.log("Type 'quit' or 'exit' to stop.");

  while (true) {
    let userInput: string;

    try {
      userInput = (await rl.question("\nYou: ")).trim();
    } catch {
      console.log("\nAgent: Bye!");
      break;
    }

    if (!userInput) {
      continue;
    }

    const lower = userInput.toLowerCase();
    if (lower === "quit" || lower === "exit") {
      console.log("Agent: Bye!");
      break;
    }

    try {
      process.stdout.write("Agent: ");

      const stream = agent.runStream(userInput);
      let finalResult: any = null;

      for await (const event of stream) {
        // The event.data contains the streamed content
        const data: any = event.data;

        // Check for streaming delta content
        if (data?.delta) {
          process.stdout.write(data.delta);
        }

        // Store final result for fallback
        if (data?.result || data?.message) {
          finalResult = data;
        }
      }

      // If no streaming happened, show the final result
      if (finalResult) {
        const answer =
          finalResult.result ??
          finalResult.message?.content ??
          finalResult.message ??
          "";
        if (answer && typeof answer === "string" && !answer.includes("[object")) {
          process.stdout.write(answer);
        }
      }

      console.log(); // New line after streaming completes
    } catch (err: any) {
      console.error("\nAgent error:", err?.message ?? err);
    }
  }

  rl.close();
}
```

### 8. Define the main entry point

What's happening here:
- We're orchestrating the entire application flow
- The agent gets built with proper error handling
- Then we kick off the interactive chat loop so you can start talking to Openweather api
```python
async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")
```

```typescript
async function main() {
  try {
    const agent = await buildAgent();
    await chatLoop(agent);
  } catch (err) {
    console.error("Failed to start agent:", err);
    process.exit(1);
  }
}

main();
```

### 9. Run the agent

When prompted, authenticate and authorise your agent with Openweather api, then start asking questions.
```bash
python llamaindex_agent.py
```

```typescript
npx ts-node llamaindex-agent.ts
```

## Complete Code

```python
import asyncio
import os
import signal
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")

async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["openweather_api"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")
    description = "An agent that uses Composio Tool Router MCP tools to perform Openweather api actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Openweather api actions.
    """
    return ReActAgent(
        tools=tools,
        llm=llm,
        description=description,
        system_prompt=system_prompt,
        verbose=True,
    );

async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")

async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")
```

```typescript
import "dotenv/config";
import readline from "node:readline/promises";
import { stdin as input, stdout as output } from "node:process";

import { Composio } from "@composio/core";
import { LlamaindexProvider } from "@composio/llamaindex";

import { mcp } from "@llamaindex/tools";
import { agent as createAgent } from "@llamaindex/workflow";
import { openai } from "@llamaindex/openai";

dotenv.config();

const OPENAI_API_KEY = process.env.OPENAI_API_KEY;
const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY;
const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID;

if (!OPENAI_API_KEY) {
    throw new Error("OPENAI_API_KEY is not set in the environment");
  }
if (!COMPOSIO_API_KEY) {
    throw new Error("COMPOSIO_API_KEY is not set in the environment");
  }
if (!COMPOSIO_USER_ID) {
    throw new Error("COMPOSIO_USER_ID is not set in the environment");
  }

async function buildAgent() {

  console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`);
  console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`);

  const composio = new Composio({
    apiKey: COMPOSIO_API_KEY,
    provider: new LlamaindexProvider(),
  });

  const session = await composio.create(
    COMPOSIO_USER_ID!,
    {
      toolkits: ["openweather_api"],
    },
  );

  const mcpUrl = session.mcp.url;
  console.log(`Composio Tool Router MCP URL: ${mcpUrl}`);

  const server = mcp({
    url: mcpUrl,
    clientName: "composio_tool_router_with_llamaindex",
    requestInit: {
      headers: {
        "x-api-key": COMPOSIO_API_KEY!,
      },
    },
    // verbose: true,
  });

  const tools = await server.tools();

  const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" });

  const agent = createAgent({
    name: "composio_tool_router_with_llamaindex",
    description:
      "An agent that uses Composio Tool Router MCP tools to perform actions.",
    systemPrompt:
      "You are a helpful assistant connected to Composio Tool Router."+
"Use the available tools to answer user queries and perform Openweather api actions." ,
    llm,
    tools,
  });

  return agent;
}

async function chatLoop(agent: ReturnType<typeof createAgent>) {
  const rl = readline.createInterface({ input, output });

  console.log("Type 'quit' or 'exit' to stop.");

  while (true) {
    let userInput: string;

    try {
      userInput = (await rl.question("\nYou: ")).trim();
    } catch {
      console.log("\nAgent: Bye!");
      break;
    }

    if (!userInput) {
      continue;
    }

    const lower = userInput.toLowerCase();
    if (lower === "quit" || lower === "exit") {
      console.log("Agent: Bye!");
      break;
    }

    try {
      process.stdout.write("Agent: ");

      const stream = agent.runStream(userInput);
      let finalResult: any = null;

      for await (const event of stream) {
        // The event.data contains the streamed content
        const data: any = event.data;

        // Check for streaming delta content
        if (data?.delta) {
          process.stdout.write(data.delta);
        }

        // Store final result for fallback
        if (data?.result || data?.message) {
          finalResult = data;
        }
      }

      // If no streaming happened, show the final result
      if (finalResult) {
        const answer =
          finalResult.result ??
          finalResult.message?.content ??
          finalResult.message ??
          "";
        if (answer && typeof answer === "string" && !answer.includes("[object")) {
          process.stdout.write(answer);
        }
      }

      console.log(); // New line after streaming completes
    } catch (err: any) {
      console.error("\nAgent error:", err?.message ?? err);
    }
  }

  rl.close();
}

async function main() {
  try {
    const agent = await buildAgent();
    await chatLoop(agent);
  } catch (err: any) {
    console.error("Failed to start agent:", err?.message ?? err);
    process.exit(1);
  }
}

main();
```

## Conclusion

You've successfully connected Openweather api to LlamaIndex through Composio's Tool Router MCP layer.
Key takeaways:
- Tool Router dynamically exposes Openweather api tools through an MCP endpoint
- LlamaIndex's ReActAgent handles reasoning and orchestration; Composio handles integrations
- The agent becomes more capable without increasing prompt size
- Async Python provides clean, efficient execution of agent workflows
You can easily extend this to other toolkits like Gmail, Notion, Stripe, GitHub, and more by adding them to the toolkits parameter.

## How to build Openweather api MCP Agent with another framework

- [ChatGPT](https://composio.dev/toolkits/openweather_api/framework/chatgpt)
- [OpenAI Agents SDK](https://composio.dev/toolkits/openweather_api/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/openweather_api/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/openweather_api/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/openweather_api/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/openweather_api/framework/codex)
- [Cursor](https://composio.dev/toolkits/openweather_api/framework/cursor)
- [VS Code](https://composio.dev/toolkits/openweather_api/framework/vscode)
- [OpenCode](https://composio.dev/toolkits/openweather_api/framework/opencode)
- [OpenClaw](https://composio.dev/toolkits/openweather_api/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/openweather_api/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/openweather_api/framework/cli)
- [Google ADK](https://composio.dev/toolkits/openweather_api/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/openweather_api/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/openweather_api/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/openweather_api/framework/mastra-ai)
- [CrewAI](https://composio.dev/toolkits/openweather_api/framework/crew-ai)

## Related Toolkits

- [Excel](https://composio.dev/toolkits/excel) - Microsoft Excel is a robust spreadsheet application for organizing, analyzing, and visualizing data. It's the go-to tool for calculations, reporting, and flexible data management.
- [21risk](https://composio.dev/toolkits/_21risk) - 21RISK is a web app built for easy checklist, audit, and compliance management. It streamlines risk processes so teams can focus on what matters.
- [Abstract](https://composio.dev/toolkits/abstract) - Abstract provides a suite of APIs for automating data validation and enrichment tasks. It helps developers streamline workflows and ensure data quality with minimal effort.
- [Addressfinder](https://composio.dev/toolkits/addressfinder) - Addressfinder is a data quality platform for verifying addresses, emails, and phone numbers. It helps you ensure accurate customer and contact data every time.
- [Agenty](https://composio.dev/toolkits/agenty) - Agenty is a web scraping and automation platform for extracting data and automating browser tasks—no coding needed. It streamlines data collection, monitoring, and repetitive online actions.
- [Ambee](https://composio.dev/toolkits/ambee) - Ambee is an environmental data platform providing real-time, hyperlocal APIs for air quality, weather, and pollen. Get precise environmental insights to power smarter decisions in your apps and workflows.
- [Ambient weather](https://composio.dev/toolkits/ambient_weather) - Ambient Weather is a platform for personal weather stations with a robust API for accessing local, real-time, and historical weather data. Get detailed environmental insights directly from your own sensors for smarter apps and automations.
- [Anonyflow](https://composio.dev/toolkits/anonyflow) - Anonyflow is a service for encryption-based data anonymization and secure data sharing. It helps organizations meet GDPR, CCPA, and HIPAA data privacy compliance requirements.
- [Api ninjas](https://composio.dev/toolkits/api_ninjas) - Api ninjas offers 120+ public APIs spanning categories like weather, finance, sports, and more. Developers use it to supercharge apps with real-time data and actionable endpoints.
- [Api sports](https://composio.dev/toolkits/api_sports) - Api sports is a comprehensive sports data platform covering 2,000+ competitions with live scores and 15+ years of stats. Instantly access up-to-date sports information for analysis, apps, or chatbots.
- [Apify](https://composio.dev/toolkits/apify) - Apify is a cloud platform for building, deploying, and managing web scraping and automation tools called Actors. It lets you automate data extraction and workflow tasks at scale—no infrastructure headaches.
- [Autom](https://composio.dev/toolkits/autom) - Autom is a lightning-fast search engine results data platform for Google, Bing, and Brave. Developers use it to access fresh, low-latency SERP data on demand.
- [Beaconchain](https://composio.dev/toolkits/beaconchain) - Beaconchain is a real-time analytics platform for Ethereum 2.0's Beacon Chain. It provides detailed insights into validators, blocks, and overall network performance.
- [Big data cloud](https://composio.dev/toolkits/big_data_cloud) - BigDataCloud provides APIs for geolocation, reverse geocoding, and address validation. Instantly access reliable location intelligence to enhance your applications and workflows.
- [Bigpicture io](https://composio.dev/toolkits/bigpicture_io) - BigPicture.io offers APIs for accessing detailed company and profile data. Instantly enrich your applications with up-to-date insights on 20M+ businesses.
- [Bitquery](https://composio.dev/toolkits/bitquery) - Bitquery is a blockchain data platform offering indexed, real-time, and historical data from 40+ blockchains via GraphQL APIs. Get unified, reliable access to complex on-chain data for analytics, trading, and research.
- [Brightdata](https://composio.dev/toolkits/brightdata) - Brightdata is a leading web data platform offering advanced scraping, SERP APIs, and anti-bot tools. It lets you collect public web data at scale, bypassing blocks and friction.
- [Builtwith](https://composio.dev/toolkits/builtwith) - BuiltWith is a web technology profiler that uncovers the technologies powering any website. Gain actionable insights into analytics, hosting, and content management stacks for smarter research and lead generation.
- [Byteforms](https://composio.dev/toolkits/byteforms) - Byteforms is an all-in-one platform for creating forms, managing submissions, and integrating data. It streamlines workflows by centralizing form data collection and automation.
- [Cabinpanda](https://composio.dev/toolkits/cabinpanda) - Cabinpanda is a data collection platform for building and managing online forms. It helps streamline how you gather, organize, and analyze responses.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Openweather api MCP?

With a standalone Openweather api MCP server, the agents and LLMs can only access a fixed set of Openweather api tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Openweather api and many other apps based on the task at hand, all through a single MCP endpoint.

### Can I use Tool Router MCP with LlamaIndex?

Yes, you can. LlamaIndex fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Openweather api tools.

### Can I manage the permissions and scopes for Openweather api while using Tool Router?

Yes, absolutely. You can configure which Openweather api scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

### How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Openweather api data and credentials are handled as safely as possible.

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