# How to integrate Corrently MCP with LlamaIndex

```json
{
  "title": "How to integrate Corrently MCP with LlamaIndex",
  "toolkit": "Corrently",
  "toolkit_slug": "corrently",
  "framework": "LlamaIndex",
  "framework_slug": "llama-index",
  "url": "https://composio.dev/toolkits/corrently/framework/llama-index",
  "markdown_url": "https://composio.dev/toolkits/corrently/framework/llama-index.md",
  "updated_at": "2026-05-12T10:07:39.206Z"
}
```

## Introduction

This guide walks you through connecting Corrently to LlamaIndex using the Composio tool router. By the end, you'll have a working Corrently agent that can log your household's latest electricity reading, forecast solar output for your address tomorrow, update co₂ meter with last week's consumption through natural language commands.
This guide will help you understand how to give your LlamaIndex agent real control over a Corrently account through Composio's Corrently MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Corrently with

- [OpenAI Agents SDK](https://composio.dev/toolkits/corrently/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/corrently/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/corrently/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/corrently/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/corrently/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/corrently/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/corrently/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/corrently/framework/cli)
- [Google ADK](https://composio.dev/toolkits/corrently/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/corrently/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/corrently/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/corrently/framework/mastra-ai)
- [CrewAI](https://composio.dev/toolkits/corrently/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 Corrently
- Connect LlamaIndex to the Corrently MCP server
- Build a Corrently-powered agent using LlamaIndex
- Interact with Corrently 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 Corrently MCP server, and what's possible with it?

The Corrently MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Corrently account. It provides structured and secure access so your agent can perform Corrently operations on your behalf.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `CORRENTLY_CO2_METER_UPDATE_READING` | CO₂ Meter Update | Tool to create or update a CO₂ meter reading for emissions tracking. Use when sending new or updated electricity consumption readings to Corrently. |
| `CORRENTLY_COMMIT_QUITTUNG` | Commit Strom-Quittung | Tool to finalize a Strom-Quittung (electricity receipt) after collecting transaction data. Use after gathering seller, buyer, and transaction details to create the final receipt. |
| `CORRENTLY_GEOCODE_LOCATION` | Geocode Location | Tool to geocode a free-text location into coordinates. Use when you need latitude and longitude from a place name. |
| `CORRENTLY_GET_ENERGY_SCHEDULE` | Energy Schedule Computation | Create an optimized operation schedule for energy-consuming devices based on the GrünstromIndex (Green Power Index). This tool determines the best time slots to run energy-intensive devices (heat pumps, EV chargers, etc.) by analyzing regional renewable energy availability, electricity prices, and CO2 emissions forecasts. Use this after collecting: - German postal code (required for regional data) - Desired optimization goal (price, co2, or comfort) - Number of hours the device needs to run |
| `CORRENTLY_GET_METERING_READING` | Get Metering Reading | Tool to retrieve metered electricity reading with green/grey energy split and CO2 emissions data. Use when you need to check current meter readings or analyze energy consumption patterns for a Stromkonto. |
| `CORRENTLY_GET_STROMKONTO_BALANCES` | Get Stromkonto Balances | Retrieve Stromkonto account balances from the energy blockchain ledger. Stromkonto is a ledger for green energy related transactions backed by Energychain blockchain to provide consensus of balances and transactions. Returns balance details across multiple sub-account types (green power bonus, generation, self-consumption, carbon offset, trees planted). |
| `CORRENTLY_GET_STROMKONTO_CHOICES` | Get Stromkonto Choices | Tool to get selectable contract choices for a Stromkonto customer. Use when you need to retrieve available balance and transaction options for an account. |
| `CORRENTLY_GET_WIM_PROCESS_STATUS` | Get WiM Process Status | Retrieve status information for WiM (Wechselprozesse im Messwesen) metering change processes. WiM processes handle meter changes and allocation workflows in the German electricity system. Use this tool to check the current status of ongoing or completed metering change processes, track process progress, or verify when a WiM process was initiated. |
| `CORRENTLY_GRUNSTROM_INDEX_FORECAST` | GrünstromIndex Forecast | Tool to retrieve hourly green power forecast and CO2 data. Use after obtaining the user API key. |
| `CORRENTLY_GSI_BEST_HOUR` | GSI Best Hour | Determines if now is the best time to turn on a device based on regional green energy (GrünstromIndex) forecasts in Germany. Returns true if the current hour has high renewable energy availability within the specified timeframe, false if waiting would be more sustainable. |
| `CORRENTLY_LOGIN_STROMKONTO` | Login to Stromkonto | Tool to initiate login to Stromkonto via email. Use when authenticating a user with their email address. |
| `CORRENTLY_MARKET_DATA` | Electricity Market Data | Retrieve real-time and forecast electricity pricing data for Germany by postal code (Postleitzahl). Returns wholesale market prices (EUR/MWh) and localized prices for specific grid areas. Data is provided in time intervals with timestamps in milliseconds since Unix epoch. Use this tool when you need current or forecasted electricity prices for energy optimization, cost analysis, or smart grid applications in Germany. |
| `CORRENTLY_PHEV_NAVIGATOR` | PHEV Navigator | Tool to get PHEV charge-or-fuel recommendation for German locations. Compares real-time fuel prices at nearby stations with electricity costs to recommend whether charging or fueling is more economical and eco-friendly. Requires a German postal code (PLZ). |
| `CORRENTLY_POST_METERING_READING` | Post Metering Reading | Tool to post a meter reading and get it decorated with green/grey energy split. Use when you need to split consumption readings into green power (1.8.1) and grey power (1.8.2) according to the local GreenPowerIndex value. |
| `CORRENTLY_PREPARE_RECEIPT_DATA` | Prepare Receipt Data | Tool to collect data for a receipt before finalizing. During the first call, an account parameter will be returned. Use this when you need to incrementally build receipt data through multiple requests. Call without an account parameter first to create a new session, then use the returned account identifier in subsequent calls to add more data. |
| `CORRENTLY_PV_GENERATION_GET_FORECAST` | PV Generation Forecast | Get hourly solar PV generation forecasts for a German location. Returns predicted energy output in watt-hours (Wh) for each hour over the specified forecast period. Use this tool when you need to optimize energy scheduling, estimate solar production, or plan energy storage based on expected PV generation. |
| `CORRENTLY_REGISTER_STROMKONTO` | Register Stromkonto Account | Tool to register a new Stromkonto energy account in the Corrently system. Use when creating a new account with email, name, and location details. All balances are initialized to zero upon registration. |
| `CORRENTLY_RENEWABLE_ENERGY_DISPATCH` | Renewable Energy Dispatch | Tool to get renewable energy flow and mix for a German ZIP code. Use when you need import/export and dispatch sources/destinations breakdown. |
| `CORRENTLY_STROMMIX` | Electricity Generation Mix | Tool to retrieve real-time electricity generation mix in Germany. Use when you need the current breakdown of generation by source. |
| `CORRENTLY_TARIFF_COMPONENTS` | Tariff Components | Retrieve detailed German electricity tariff cost breakdown by postal code. Returns comprehensive cost components including: - Grundgebühr (base monthly fee) - Arbeitspreis (energy price per kWh) - Network fees (Netznutzungsentgelt) - Taxes (Stromsteuer, Mehrwertsteuer) - Levies (EEG, KWKG, Offshore-Netzumlage) - Renewable energy credits Use this tool to understand electricity pricing transparency in Germany. |
| `CORRENTLY_TARIFF_SLPH0` | Standard Load Profile Tariff SLPH0 | Tool to retrieve standard load profile H0 tariff information. Use after providing a German postal code to get local SLPH0 tariffs. |
| `CORRENTLY_WEATHER_FORECAST` | Weather Forecast | Tool to retrieve hourly weather forecasts (wind speed and UV index) by geographic coordinates. Use when you need wind and UV data for a specific location. Returns up to 5 days of hourly forecasts. |
| `CORRENTLY_WIM_STATUS` | TyDID Consent Status | Check TyDID consent/grant status for an SSI (Self-Sovereign Identity). This tool queries the Corrently TyDID API to verify whether a given Ethereum-based identity has granted consent or if the consent has been revoked. Use cases: - Verify user consent before processing data - Check if a user has revoked access to their data - Monitor consent status changes in blockchain-based identity systems |

## Supported Triggers

None listed.

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

The Corrently MCP server is an implementation of the Model Context Protocol that connects your AI agent to Corrently. It provides structured and secure access so your agent can perform Corrently 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 Corrently account and project
- Basic familiarity with async Python/Typescript

### 1. Getting API Keys for OpenAI, Composio, and Corrently

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 Corrently 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, corrently)
- 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 Corrently 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=["corrently"],
    )

    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 Corrently actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Corrently 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: ["corrently"],
    },
  );

  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 Corrently 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 Corrently
```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 Corrently, 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=["corrently"],
    )

    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 Corrently actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Corrently 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: ["corrently"],
    },
  );

  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 Corrently 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 Corrently to LlamaIndex through Composio's Tool Router MCP layer.
Key takeaways:
- Tool Router dynamically exposes Corrently 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 Corrently MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/corrently/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/corrently/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/corrently/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/corrently/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/corrently/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/corrently/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/corrently/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/corrently/framework/cli)
- [Google ADK](https://composio.dev/toolkits/corrently/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/corrently/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/corrently/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/corrently/framework/mastra-ai)
- [CrewAI](https://composio.dev/toolkits/corrently/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.
- [Agentql](https://composio.dev/toolkits/agentql) - Agentql is a toolkit that connects AI agents to the web using a specialized query language. It enables structured web interaction and data extraction for smarter automations.
- [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.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Corrently MCP?

With a standalone Corrently MCP server, the agents and LLMs can only access a fixed set of Corrently tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Corrently 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 Corrently tools.

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

Yes, absolutely. You can configure which Corrently 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 Corrently data and credentials are handled as safely as possible.

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[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)