# How to integrate Doppler secretops MCP with LlamaIndex

```json
{
  "title": "How to integrate Doppler secretops MCP with LlamaIndex",
  "toolkit": "Doppler secretops",
  "toolkit_slug": "doppler_secretops",
  "framework": "LlamaIndex",
  "framework_slug": "llama-index",
  "url": "https://composio.dev/toolkits/doppler_secretops/framework/llama-index",
  "markdown_url": "https://composio.dev/toolkits/doppler_secretops/framework/llama-index.md",
  "updated_at": "2026-05-12T10:09:34.971Z"
}
```

## Introduction

This guide walks you through connecting Doppler secretops to LlamaIndex using the Composio tool router. By the end, you'll have a working Doppler secretops agent that can list all recent config changes for project x, rollback staging config to previous version, clone production config to a new branch through natural language commands.
This guide will help you understand how to give your LlamaIndex agent real control over a Doppler secretops account through Composio's Doppler secretops MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Doppler secretops with

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

The Doppler secretops MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Doppler secretops account. It provides structured and secure access to your secrets management platform, so your agent can perform actions like auditing activity logs, managing environment configs, rolling back changes, and automating config cloning on your behalf.
- Fetch activity and config logs: Quickly retrieve detailed activity logs and config change histories to monitor changes and track security events across your Doppler workspace.
- Rollback and restore configurations: Direct your agent to roll back a config to a previous version, helping you easily undo unwanted or risky changes with confidence.
- Clone and create branch configs: Automate the cloning of config branches or create new branch configs for different environments and projects, streamlining your secrets management workflows.
- Config locking and deletion: Secure your critical configs by locking them against unwanted changes or safely deleting obsolete configurations as part of environment cleanup.
- Retrieve detailed config metadata: Instantly get comprehensive details for any specific config, including project and environment context, to support debugging and compliance tasks.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `DOPPLER_SECRETOPS_ACTIVITY_LOGS_LIST` | Activity Logs List | Tool to list workplace activity logs. Use when you need to fetch recent activity logs. |
| `DOPPLER_SECRETOPS_ACTIVITY_LOGS_RETRIEVE` | Retrieve Activity Log | Tool to retrieve a single activity log entry by id. Use when you have a valid Activity Log id. |
| `DOPPLER_SECRETOPS_CONFIG_LOGS_GET` | Retrieve Config Log Entry | Tool to retrieve a specific config log entry. Use when needing details of a single config log; call after specifying project, config, and log identifiers. |
| `DOPPLER_SECRETOPS_CONFIG_LOGS_LIST` | Config Logs List | Tool to list config change logs for a specific config. Use when you need the audit trail for a config after confirming its identity. |
| `DOPPLER_SECRETOPS_CONFIG_LOGS_ROLLBACK` | Config Logs Rollback | Tool to rollback a config to a selected log version. Use when needing to undo a specific change by its log ID, after confirming project, config, and log ID. |
| `DOPPLER_SECRETOPS_CONFIGS_CLONE` | Clone Config | Tool to clone a branch config including all its secrets. Use after confirming the source config details. |
| `DOPPLER_SECRETOPS_CONFIGS_CREATE` | Create Branch Config | Tool to create a branch config. Use when you need to programmatically establish a new branch-based configuration for a specified project and environment. Use after selecting the target project and environment. |
| `DOPPLER_SECRETOPS_CONFIGS_DELETE` | Configs Delete | Tool to delete a config permanently. Use when you need to remove a config that is no longer needed. |
| `DOPPLER_SECRETOPS_CONFIGS_GET` | Get Config Details | Tool to fetch a config's details. Use when you need metadata for a specific config after specifying the project and config names. Example: "Get details for config 'staging-config' in project 'proj-123'." |
| `DOPPLER_SECRETOPS_CONFIGS_LOCK` | Lock Config | Tool to lock a config. Use when you need to prevent a config from being renamed or deleted after confirming the project and config names. Example: "Lock config 'staging-config' in project 'proj-123' after finalizing environment setup." |
| `DOPPLER_SECRETOPS_CONFIGS_UNLOCK` | Unlock Config | Tool to unlock a config. Use when you need to allow renaming or deletion of a previously locked config. Example: "Unlock config 'staging-config' in project 'proj-123'." |
| `DOPPLER_SECRETOPS_CONFIGS_UPDATE` | Update Config | Tool to modify an existing config. Use when you need to rename a config after confirming project and config names. |
| `DOPPLER_SECRETOPS_DYNAMIC_SECRETS_REVOKE_LEASE` | Revoke Dynamic Secret Lease | Tool to revoke a dynamic secret lease. Use when you need to invalidate an active lease by its ID after confirming the config and dynamic secret identifiers. |
| `DOPPLER_SECRETOPS_ENVIRONMENTS_CREATE` | Create Environment | Tool to create a new environment. Use when you need to programmatically create an environment for a specified project. |
| `DOPPLER_SECRETOPS_ENVIRONMENTS_DELETE` | Environments Delete | Tool to delete an environment. Use when you need to remove an environment from a project after confirming it's no longer in use. |
| `DOPPLER_SECRETOPS_ENVIRONMENTS_GET` | Get Environment Details | Tool to retrieve an environment. Use when you need metadata for a specific environment after specifying the project and environment slug. |
| `DOPPLER_SECRETOPS_ENVIRONMENTS_LIST` | List Environments | Tool to list environments in a Doppler project. Use when you need environment metadata for a specific project after providing the project slug. |
| `DOPPLER_SECRETOPS_ENVIRONMENTS_RENAME` | Rename Environment | Tool to rename an environment. Use when you need to update an environment's display name after confirming project and environment identifiers. |
| `DOPPLER_SECRETOPS_GROUPS_DELETE_MEMBER` | Remove Group Member | Tool to remove a member from a group. Use after confirming the group slug and member identifiers. |
| `DOPPLER_SECRETOPS_INTEGRATIONS_LIST` | Integrations List | Tool to list all external integrations. Use when you need to retrieve all configured external integrations after authentication. |
| `DOPPLER_SECRETOPS_INVITES_LIST` | Invites List | Tool to list open workplace invites. Use when you need to retrieve all pending invitations for the current Doppler workplace after authenticating. |
| `DOPPLER_SECRETOPS_PROJECT_MEMBERS_DELETE` | Remove Project Member | Tool to remove a member from a project. Use after confirming project slug, member type, and slug. Example: "Delete member 'jdoe' of type 'users' from project 'my-project-slug'." |
| `DOPPLER_SECRETOPS_PROJECT_MEMBERS_GET` | Get Project Member | Tool to retrieve a project member by type and slug. Use after confirming project slug, member type, and slug. |
| `DOPPLER_SECRETOPS_PROJECT_PERMISSIONS_LIST` | Project Permissions List | Tool to list project-level permissions. Use when you need to fetch all available permissions for projects after authentication. |
| `DOPPLER_SECRETOPS_PROJECT_ROLES_GET` | Get Project Role | Tool to retrieve a project role. Use when you need details of a specific project role after authenticating. |
| `DOPPLER_SECRETOPS_PROJECTS_CREATE` | Create Project | Tool to create a project. Use when you need to programmatically initialize a new Doppler project after authentication. |
| `DOPPLER_SECRETOPS_PROJECTS_DELETE` | Projects Delete | Tool to delete a project permanently. Use after confirming irreversible removal. |
| `DOPPLER_SECRETOPS_PROJECTS_LIST` | List Projects | Tool to list Doppler projects. Use when you need to retrieve all projects with optional pagination. |
| `DOPPLER_SECRETOPS_SECRETS_UPDATE` | Update Secrets | Tool to update secrets in a config. Use when you need to change secret values for deployments. |

## Supported Triggers

None listed.

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

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

### 1. Getting API Keys for OpenAI, Composio, and Doppler secretops

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 Doppler secretops 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, doppler secretops)
- 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 Doppler secretops 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=["doppler_secretops"],
    )

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

  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 Doppler secretops 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 Doppler secretops
```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 Doppler secretops, 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=["doppler_secretops"],
    )

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

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

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

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- [Codeinterpreter](https://composio.dev/toolkits/codeinterpreter) - Codeinterpreter is a Python-based coding environment with built-in data analysis and visualization. It lets you instantly run scripts, plot results, and prototype solutions inside supported platforms.
- [GitHub](https://composio.dev/toolkits/github) - GitHub is a code hosting platform for version control and collaborative software development. It streamlines project management, code review, and team workflows in one place.
- [Ably](https://composio.dev/toolkits/ably) - Ably is a real-time messaging platform for live chat and data sync in modern apps. It offers global scale and rock-solid reliability for seamless, instant experiences.
- [Abuselpdb](https://composio.dev/toolkits/abuselpdb) - Abuselpdb is a central database for reporting and checking IPs linked to malicious online activity. Use it to quickly identify and report suspicious or abusive IP addresses.
- [Alchemy](https://composio.dev/toolkits/alchemy) - Alchemy is a blockchain development platform offering APIs and tools for Ethereum apps. It simplifies building and scaling Web3 projects with robust infrastructure.
- [Algolia](https://composio.dev/toolkits/algolia) - Algolia is a hosted search API that powers lightning-fast, relevant search experiences for web and mobile apps. It helps developers deliver instant, typo-tolerant, and scalable search without complex infrastructure.
- [Anchor browser](https://composio.dev/toolkits/anchor_browser) - Anchor browser is a developer platform for AI-powered web automation. It transforms complex browser actions into easy API endpoints for streamlined web interaction.
- [Apiflash](https://composio.dev/toolkits/apiflash) - Apiflash is a website screenshot API for programmatically capturing web pages. It delivers high-quality screenshots on demand for automation, monitoring, or reporting.
- [Apiverve](https://composio.dev/toolkits/apiverve) - Apiverve delivers a suite of powerful APIs that simplify integration for developers. It's designed for reliability and scalability so you can build faster, smarter applications without the integration headache.
- [Appcircle](https://composio.dev/toolkits/appcircle) - Appcircle is an enterprise-grade mobile CI/CD platform for building, testing, and publishing mobile apps. It streamlines mobile DevOps so teams ship faster and with more confidence.
- [Appdrag](https://composio.dev/toolkits/appdrag) - Appdrag is a cloud platform for building websites, APIs, and databases with drag-and-drop tools and code editing. It accelerates development and iteration by combining hosting, database management, and low-code features in one place.
- [Appveyor](https://composio.dev/toolkits/appveyor) - AppVeyor is a cloud-based continuous integration service for building, testing, and deploying applications. It helps developers automate and streamline their software delivery pipelines.
- [Backendless](https://composio.dev/toolkits/backendless) - Backendless is a backend-as-a-service platform for mobile and web apps, offering database, file storage, user authentication, and APIs. It helps developers ship scalable applications faster without managing server infrastructure.
- [Baserow](https://composio.dev/toolkits/baserow) - Baserow is an open-source no-code database platform for building collaborative data apps. It makes it easy for teams to organize data and automate workflows without writing code.
- [Bench](https://composio.dev/toolkits/bench) - Bench is a benchmarking tool for automated performance measurement and analysis. It helps you quickly evaluate, compare, and track your systems or workflows.
- [Better stack](https://composio.dev/toolkits/better_stack) - Better Stack is a monitoring, logging, and incident management solution for apps and services. It helps teams ensure application reliability and performance with real-time insights.
- [Bitbucket](https://composio.dev/toolkits/bitbucket) - Bitbucket is a Git-based code hosting and collaboration platform for teams. It enables secure repository management and streamlined code reviews.
- [Blazemeter](https://composio.dev/toolkits/blazemeter) - Blazemeter is a continuous testing platform for web and mobile app performance. It empowers teams to automate and analyze large-scale tests with ease.
- [Blocknative](https://composio.dev/toolkits/blocknative) - Blocknative delivers real-time mempool monitoring and transaction management for public blockchains. Instantly track pending transactions and optimize blockchain interactions with live data.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Doppler secretops MCP?

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

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

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

---
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