# How to integrate Canny MCP with LlamaIndex

```json
{
  "title": "How to integrate Canny MCP with LlamaIndex",
  "toolkit": "Canny",
  "toolkit_slug": "canny",
  "framework": "LlamaIndex",
  "framework_slug": "llama-index",
  "url": "https://composio.dev/toolkits/canny/framework/llama-index",
  "markdown_url": "https://composio.dev/toolkits/canny/framework/llama-index.md",
  "updated_at": "2026-05-12T10:05:00.771Z"
}
```

## Introduction

This guide walks you through connecting Canny to LlamaIndex using the Composio tool router. By the end, you'll have a working Canny agent that can add 'urgent' tag to all critical feedback posts, create a new post on the bugs board, change status of top-voted post to 'in progress' through natural language commands.
This guide will help you understand how to give your LlamaIndex agent real control over a Canny account through Composio's Canny MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Canny with

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

The Canny MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Canny account. It provides structured and secure access to your feedback boards, so your agent can create new posts, manage user feedback, update post status, and keep changelogs up to date—all automatically, on your behalf.
- Automated feedback collection and posting: Enable your agent to create new posts on boards, capturing fresh user suggestions or bug reports with the right context every time.
- User and comment management: Let your agent create or update user profiles, add new comments to posts, and even delete users or comments for moderation or compliance needs.
- Status and tag updates: Have your agent update post statuses to reflect progress or changes, apply tags to categorize feedback, and create new tags as your product evolves.
- Changelog automation: Seamlessly generate and publish changelog entries to keep users informed about new features or bug fixes, with full control over timing and notifications.
- Feedback voting and prioritization: Allow your agent to create or migrate votes for posts, helping you track which ideas matter most to your users with minimal manual effort.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `CANNY_ADD_POST_TAG` | Add Post Tag | Tool to add a tag to a specific post. Use when you need to categorize or group content by applying an existing tag. |
| `CANNY_CHANGE_POST_STATUS` | Change Post Status | Tool to change a post's status. Use when you need to update a post's workflow stage and optionally notify voters. |
| `CANNY_CREATE_CHANGELOG_ENTRY` | Create Changelog Entry | Tool to create and optionally publish a new changelog entry. Use when you need to add a product update record, control publish timing, and notify users. Example: "Create changelog entry titled 'Version 1.2' with details '...' and publish immediately.". |
| `CANNY_CREATE_COMMENT` | Create Comment | Tool to create a new comment on a post. Use when you have the authorID and postID and want to submit feedback or replies. |
| `CANNY_CREATE_OR_UPDATE_USER` | Create or Update User | Creates a new user or updates an existing user in Canny. If a user with the given identifier (email, userID, or id) already exists, their profile is updated; otherwise, a new user is created. IMPORTANT: At least one of 'email', 'userID', or 'id' must be provided along with 'name'. Use cases: - Sync users from your application to Canny - Update user profiles (name, avatar, custom fields) - Associate users with companies for segmentation Example: Create user with email: {"name": "Jane Doe", "email": "jane@example.com"} Example: Sync app user: {"name": "John Smith", "userID": "app_user_123", "email": "john@example.com"} |
| `CANNY_CREATE_POST` | Create Post | Tool to create a new post (feature request or feedback) on a Canny board. Use this action when you need to submit new feedback or feature requests to a board. Requires a valid boardID (from list_boards) and authorID (from create_or_update_user or list_users). |
| `CANNY_CREATE_TAG` | Create Tag | Tool to create a new tag. Use when you have the boardID and tag name and need to categorize posts. |
| `CANNY_CREATE_VOTE` | Create Vote | Tool to create a vote for a post. Use when you need to record or migrate a user's vote on a post, optionally setting priority or original creation time. Example: Create a vote for postID abc123 with voterID user_456. |
| `CANNY_DELETE_COMMENT` | Delete Comment | Tool to delete a comment. Use when moderation is required to remove a specific comment by its id. Example: "Delete the comment with ID 553c3ef8b8cdcd1501ba1238." |
| `CANNY_DELETE_POST` | Delete Post | Tool to delete a post. Use when you need to permanently remove a post by its id. Example: "Delete the post with ID 553c3ef8b8cdcd1501ba1238." |
| `CANNY_CANNY_DELETE_USER` | Delete User | Tool to delete a user and their comments and votes. Use when you need to fully remove a user’s account and all associated data (e.g., GDPR compliance). |
| `CANNY_DELETE_VOTE` | Delete Vote | Tool to delete a vote. Use when you need to remove a user's vote from a specific post by its id. Example: "Delete the vote from postID abc123 for voterID user_456." |
| `CANNY_LIST_BOARDS` | List Boards | Tool to list all boards. Use when you need to retrieve every board for your company after authentication. |
| `CANNY_LIST_CATEGORIES` | List Categories | Tool to list categories. Use when fetching categories for a specific board by its ID. |
| `CANNY_LIST_COMMENTS` | List Comments | Retrieves a paginated list of comments from Canny. Comments can be filtered by board, post, author, or company. Use this action to: - Get all comments across your Canny instance - Find comments on a specific post (using postID) - List comments from a specific board (using boardID) - See comments by a specific user (using authorID) - Track feedback from a company's users (using companyID) Returns comments ordered by creation date (newest first). Use 'limit' and 'skip' for pagination. |
| `CANNY_LIST_COMPANIES` | List Companies | Tool to list companies associated with your Canny account. Use after authentication to retrieve companies with pagination support. |
| `CANNY_LIST_OPPORTUNITIES` | List Opportunities | Tool to list opportunities linked to posts. Use when you need to fetch customer opportunities synced from CRM. |
| `CANNY_LIST_POSTS` | List Posts | Tool to list posts with various filters. Use after selecting a board or to search/filter posts. |
| `CANNY_LIST_TAGS` | List Tags | Tool to list tags. Use when fetching tags optionally filtered by board ID and handling pagination. |
| `CANNY_LIST_USERS` | List Users | List all end-users in your Canny workspace with pagination support. Use this tool to: - Fetch users from your Canny workspace - Paginate through large user lists using cursor-based pagination - Get user details including email, name, admin status, and custom fields Returns a paginated list of users. Use the returned cursor to fetch subsequent pages. |
| `CANNY_LIST_VOTES` | List Votes | Retrieve votes from Canny with optional filtering by board, post, or voter. Use this action to: - Get all votes on a specific post (filter by postID) - Get all votes by a specific user (filter by voterID) - Get all votes on posts in a board (filter by boardID) - List all votes across the account (no filters) Results are paginated - use 'limit' and 'skip' parameters to navigate through pages. Check 'hasMore' in the response to determine if more results are available. |
| `CANNY_RETRIEVE_BOARD` | Retrieve Board | Tool to retrieve details of a board by its ID. Use when you need metadata for a specific board. |
| `CANNY_RETRIEVE_TAG` | Retrieve Tag | Tool to retrieve details of a tag by its ID. Use after obtaining a valid tag ID. |
| `CANNY_RETRIEVE_USER` | Retrieve User | Tool to retrieve user details by Canny user ID, app user ID, or email. Use when you have exactly one identifier and need full user information. Example: "Retrieve user with email user@example.com" |
| `CANNY_UPDATE_POST` | Update Post | Tool to update post details. Use when you need to change a post's title, details, ETA, images, or custom fields. |

## Supported Triggers

None listed.

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

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

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

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 Canny 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, canny)
- 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 Canny 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=["canny"],
    )

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

  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 Canny 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 Canny
```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 Canny, 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=["canny"],
    )

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

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

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

## Related Toolkits

- [Google Sheets](https://composio.dev/toolkits/googlesheets) - Google Sheets is a cloud-based spreadsheet tool for real-time collaboration and data analysis. It lets teams work together from anywhere, updating information instantly.
- [Notion](https://composio.dev/toolkits/notion) - Notion is a collaborative workspace for notes, docs, wikis, and tasks. It streamlines team knowledge, project tracking, and workflow customization in one place.
- [Airtable](https://composio.dev/toolkits/airtable) - Airtable combines the flexibility of spreadsheets with the power of a database for easy project and data management. Teams use Airtable to organize, track, and collaborate with custom views and automations.
- [Asana](https://composio.dev/toolkits/asana) - Asana is a collaborative work management platform for teams to organize and track projects. It streamlines teamwork, boosts productivity, and keeps everyone aligned on goals.
- [Google Tasks](https://composio.dev/toolkits/googletasks) - Google Tasks is a to-do list and task management tool integrated into Gmail and Google Calendar. It helps you organize, track, and complete tasks across your Google ecosystem.
- [Linear](https://composio.dev/toolkits/linear) - Linear is a modern issue tracking and project planning tool for fast-moving teams. It helps streamline workflows, organize projects, and boost productivity.
- [Jira](https://composio.dev/toolkits/jira) - Jira is Atlassian’s platform for bug tracking, issue tracking, and agile project management. It helps teams organize work, prioritize tasks, and deliver projects efficiently.
- [Clickup](https://composio.dev/toolkits/clickup) - ClickUp is an all-in-one productivity platform for managing tasks, docs, goals, and team collaboration. It streamlines project workflows so teams can work smarter and stay organized in one place.
- [Monday](https://composio.dev/toolkits/monday) - Monday.com is a customizable work management platform for project planning and collaboration. It helps teams organize tasks, automate workflows, and track progress in real time.
- [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.
- [Agiled](https://composio.dev/toolkits/agiled) - Agiled is an all-in-one business management platform for CRM, projects, and finance. It helps you streamline workflows, consolidate client data, and manage business processes in one place.
- [Ascora](https://composio.dev/toolkits/ascora) - Ascora is a cloud-based field service management platform for service businesses. It streamlines scheduling, invoicing, and customer operations in one place.
- [Basecamp](https://composio.dev/toolkits/basecamp) - Basecamp is a project management and team collaboration tool by 37signals. It helps teams organize tasks, share files, and communicate efficiently in one place.
- [Beeminder](https://composio.dev/toolkits/beeminder) - Beeminder is an online goal-tracking platform that uses monetary pledges to keep you motivated. Stay accountable and hit your targets with real financial incentives.
- [Boxhero](https://composio.dev/toolkits/boxhero) - Boxhero is a cloud-based inventory management platform for SMBs, offering real-time updates, barcode scanning, and team collaboration. It helps businesses streamline stock tracking and analytics for smarter inventory decisions.
- [Breathe HR](https://composio.dev/toolkits/breathehr) - Breathe HR is cloud-based HR software for SMEs to manage employee data, absences, and performance. It simplifies HR admin, making it easy to keep employee records accurate and up to date.
- [Breeze](https://composio.dev/toolkits/breeze) - Breeze is a project management platform designed to help teams plan, track, and collaborate on projects. It streamlines workflows and keeps everyone on the same page.
- [Bugherd](https://composio.dev/toolkits/bugherd) - Bugherd is a visual feedback and bug tracking tool for websites. It helps teams and clients report website issues directly on live sites for faster fixes.
- [Chmeetings](https://composio.dev/toolkits/chmeetings) - Chmeetings is a church management platform for events, members, donations, and volunteers. It streamlines church operations and improves community engagement.
- [ClickSend](https://composio.dev/toolkits/clicksend) - ClickSend is a cloud-based SMS and email marketing platform for businesses. It streamlines communication by enabling quick message delivery and contact management.

## Frequently Asked Questions

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

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

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

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

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