# How to integrate Doppler MCP with Vercel AI SDK v6 ```json { "title": "How to integrate Doppler MCP with Vercel AI SDK v6", "toolkit": "Doppler", "toolkit_slug": "doppler", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/doppler/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/doppler/framework/ai-sdk.md", "updated_at": "2026-03-29T06:31:11.666Z" } ``` ## Introduction This guide walks you through connecting Doppler to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Doppler agent that can get secrets for staging environment in doppler, add a new secret to marketing project, list all projects and their environments through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Doppler account through Composio's Doppler MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Doppler with - [ChatGPT](https://composio.dev/toolkits/doppler/framework/chatgpt) - [Antigravity](https://composio.dev/toolkits/doppler/framework/antigravity) - [OpenAI Agents SDK](https://composio.dev/toolkits/doppler/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/doppler/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/doppler/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/doppler/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/doppler/framework/codex) - [Cursor](https://composio.dev/toolkits/doppler/framework/cursor) - [VS Code](https://composio.dev/toolkits/doppler/framework/vscode) - [OpenCode](https://composio.dev/toolkits/doppler/framework/opencode) - [OpenClaw](https://composio.dev/toolkits/doppler/framework/openclaw) - [Hermes](https://composio.dev/toolkits/doppler/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/doppler/framework/cli) - [Google ADK](https://composio.dev/toolkits/doppler/framework/google-adk) - [LangChain](https://composio.dev/toolkits/doppler/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/doppler/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/doppler/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/doppler/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up and configure a Vercel AI SDK agent with Doppler integration - Using Composio's Tool Router to dynamically load and access Doppler tools - Creating an MCP client connection using HTTP transport - Building an interactive CLI chat interface with conversation history management - Handling tool calls and results within the Vercel AI SDK framework ## What is Vercel AI SDK? The Vercel AI SDK is a TypeScript library for building AI-powered applications. It provides tools for creating agents that can use external services and maintain conversation state. Key features include: - streamText: Core function for streaming responses with real-time tool support - MCP Client: Built-in support for Model Context Protocol via @ai-sdk/mcp - Step Counting: Control multi-step tool execution with stopWhen: stepCountIs() - OpenAI Provider: Native integration with OpenAI models ## What is the Doppler MCP server, and what's possible with it? The Doppler 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 account. It provides structured and secure access so your agent can perform Doppler operations on your behalf. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `DOPPLER_AUTH_ME` | Get Authenticated User Info | Tool to retrieve information about the authenticated user or token. Use when you need to verify authentication status or get details about the current token's workplace and permissions. | | `DOPPLER_CONFIG_LOGS_GET` | Get Config Log | Tool to retrieve a specific config log from Doppler. Use when you need to view details about a particular configuration change or event. | | `DOPPLER_CONFIG_LOGS_LIST` | List Config Logs | Tool to retrieve configuration change logs for a specific config in a project. Use when you need to view the history of configuration changes, track who made changes, or identify rollback actions. | | `DOPPLER_CONFIGS_GET` | Get Config | Tool to retrieve a specific Doppler config by project and config name. Use when you need to get configuration details for a specific project environment. | | `DOPPLER_LIST_DOPPLER_CONFIGS` | List Doppler Configs | Tool to list configurations from a Doppler project. Use when you need to retrieve all configs or filter by environment. Supports pagination for large result sets. | | `DOPPLER_CREATE_ENCRYPTED_SHARE_LINK` | Create Encrypted Share Link | Tool to generate a Doppler Share link by sending an encrypted secret. Use when you need to securely share secrets with end-to-end encryption. The receive flow is end-to-end encrypted where the encrypted secret will be decrypted on the recipient's browser. | | `DOPPLER_CREATE_PLAIN_TEXT_SHARE_LINK` | Create Plain Text Share Link | Tool to generate a Doppler Share link by sending a plain text secret. Use when you need to securely share secrets with expiration controls. The secret is not stored in plain text by Doppler; the receive flow is end-to-end encrypted where the encrypted secret is decrypted in the browser. | | `DOPPLER_LIST_ENVIRONMENTS` | List Environments | Tool to list all environments in a Doppler project. Use when you need to retrieve the environments available in a specific project. | | `DOPPLER_LIST_INTEGRATIONS` | List Integrations | Tool to retrieve all existing integrations in Doppler. Use when you need to list all configured integrations. | | `DOPPLER_LIST_CHANGE_REQUESTS` | List Change Requests | Tool to list existing change requests in the Doppler workplace. Use when you need to retrieve all change requests and their current status. | | `DOPPLER_GET_PROJECT_ROLE` | Get Project Role | Tool to retrieve details of a specific project role in Doppler. Use when you need to get information about a role's permissions and metadata. | | `DOPPLER_LIST_PROJECT_ROLES` | List Project Roles | Tool to list all available project roles in Doppler. Use when you need to retrieve all roles for permission management or to see what roles are available. | | `DOPPLER_LIST_PROJECT_ROLE_PERMISSIONS` | List Project Role Permissions | Tool to list all available permissions for project roles in Doppler. Use when you need to see what permissions can be assigned to custom project roles. | | `DOPPLER_GET_PROJECT_DETAILS` | Get Project Details | Tool to retrieve details of a specific Doppler project by its identifier. Use when you need to get project metadata including name, description, and creation timestamp. | | `DOPPLER_LIST_DOPPLER_PROJECTS` | List Doppler Projects | Tool to list all Doppler projects in your workspace. Use when you need to retrieve available projects for configuration management or to get project details. | | `DOPPLER_DELETE_SECRET` | Delete Secret | Tool to delete a secret from a Doppler config. Use when you need to permanently remove a secret from a specific project and config. | | `DOPPLER_DOWNLOAD_SECRETS` | Download Secrets | Tool to download secrets from a Doppler config in various formats. Use when you need to retrieve all secrets or a subset of secrets from a specific project and config. Supports multiple output formats and name transformations. | | `DOPPLER_GET_SECRET` | Get Secret | Tool to retrieve a specific secret from a Doppler project config. Use when you need to get the value of a specific secret including its raw and computed values. | | `DOPPLER_LIST_DOPPLER_SECRETS` | List Doppler Secrets | Tool to list all secrets for a specific Doppler config within a project. Use when you need to retrieve secret values and metadata. Returns both raw and computed values for each secret, along with visibility settings and optional notes. | | `DOPPLER_LIST_SECRET_NAMES` | List Secret Names | Tool to retrieve the list of secret names from a specific Doppler config. Use when you need to list available secret names without their values. | | `DOPPLER_UPDATE_DOPPLER_SECRETS` | Update Doppler Secrets | Tool to update secrets in a Doppler config. Use when you need to create or update secret values in a specific project and config. | | `DOPPLER_UPDATE_SECRET_NOTE` | Update Secret Note | Tool to update a note for a secret in Doppler. Use when you need to add or modify documentation for a specific secret. The note will be applied to the specified secret across all environments in the project. | | `DOPPLER_GET_WORKPLACE_INFORMATION` | Get Workplace Information | Tool to retrieve workplace information from Doppler. Use when you need to get workplace details including ID, name, billing email, and security email. | | `DOPPLER_GET_WORKPLACE_ROLE` | Get Workplace Role | Tool to retrieve workplace role information from Doppler. Use when you need to get details about a specific role including its permissions and metadata. | | `DOPPLER_LIST_WORKPLACE_ROLES` | List Workplace Roles | Tool to list all workplace roles in your Doppler workspace. Use when you need to retrieve available workplace roles for user management or permission configuration. | | `DOPPLER_LIST_WORKPLACE_PERMISSIONS` | List Workplace Permissions | Tool to retrieve all available workplace permissions in Doppler. Use when you need to view the list of permissions that can be assigned to workplace roles. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Doppler MCP server is an implementation of the Model Context Protocol that connects your AI agent to Doppler. It provides structured and secure access so your agent can perform Doppler 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: - Node.js and npm installed - A Composio account with API key - An OpenAI API key ### 1. Getting API Keys for OpenAI and Composio OpenAI API Key - Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) and create an API key. You'll need credits to use the models, or you can connect to another model provider. - Keep the API key safe. Composio API Key - Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs). - Navigate to your API settings and generate a new API key. - Store this key securely as you'll need it for authentication. ### 2. Install required dependencies First, install the necessary packages for your project. What you're installing: - @ai-sdk/openai: Vercel AI SDK's OpenAI provider - @ai-sdk/mcp: MCP client for Vercel AI SDK - @composio/core: Composio SDK for tool integration - ai: Core Vercel AI SDK - dotenv: Environment variable management ```bash npm install @ai-sdk/openai @ai-sdk/mcp @composio/core ai dotenv ``` ### 3. Set up environment variables Create a .env file in your project root. What's needed: - OPENAI_API_KEY: Your OpenAI API key for GPT model access - COMPOSIO_API_KEY: Your Composio API key for tool access - COMPOSIO_USER_ID: A unique identifier for the user session ```bash OPENAI_API_KEY=your_openai_api_key_here COMPOSIO_API_KEY=your_composio_api_key_here COMPOSIO_USER_ID=your_user_id_here ``` ### 4. Import required modules and validate environment What's happening: - We're importing all necessary libraries including Vercel AI SDK's OpenAI provider and Composio - The dotenv/config import automatically loads environment variables - The MCP client import enables connection to Composio's tool server ```typescript import "dotenv/config"; import { openai } from "@ai-sdk/openai"; import { Composio } from "@composio/core"; import * as readline from "readline"; import { streamText, type ModelMessage, stepCountIs } from "ai"; import { createMCPClient } from "@ai-sdk/mcp"; const composioAPIKey = process.env.COMPOSIO_API_KEY; const composioUserID = process.env.COMPOSIO_USER_ID; if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set"); if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set"); if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set"); const composio = new Composio({ apiKey: composioAPIKey, }); ``` ### 5. Create Tool Router session and initialize MCP client What's happening: - We're creating a Tool Router session that gives your agent access to Doppler tools - The create method takes the user ID and specifies which toolkits should be available - The returned mcp object contains the URL and authentication headers needed to connect to the MCP server - This session provides access to all Doppler-related tools through the MCP protocol ```typescript async function main() { // Create a tool router session for the user const session = await composio.create(composioUserID!, { toolkits: ["doppler"], }); const mcpUrl = session.mcp.url; ``` ### 6. Connect to MCP server and retrieve tools What's happening: - We're creating an MCP client that connects to our Composio Tool Router session via HTTP - The mcp.url provides the endpoint, and mcp.headers contains authentication credentials - The type: "http" is important - Composio requires HTTP transport - tools() retrieves all available Doppler tools that the agent can use ```typescript const mcpClient = await createMCPClient({ transport: { type: "http", url: mcpUrl, headers: session.mcp.headers, // Authentication headers for the Composio MCP server }, }); const tools = await mcpClient.tools(); ``` ### 7. Initialize conversation and CLI interface What's happening: - We initialize an empty messages array to maintain conversation history - A readline interface is created to accept user input from the command line - Instructions are displayed to guide the user on how to interact with the agent ```typescript let messages: ModelMessage[] = []; console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n"); console.log( "Ask any questions related to doppler, like summarize my last 5 emails, send an email, etc... :)))\n", ); const rl = readline.createInterface({ input: process.stdin, output: process.stdout, prompt: "> ", }); rl.prompt(); ``` ### 8. Handle user input and stream responses with real-time tool feedback What's happening: - We use streamText instead of generateText to stream responses in real-time - toolChoice: "auto" allows the model to decide when to use Doppler tools - stopWhen: stepCountIs(10) allows up to 10 steps for complex multi-tool operations - onStepFinish callback displays which tools are being used in real-time - We iterate through the text stream to create a typewriter effect as the agent responds - The complete response is added to conversation history to maintain context - Errors are caught and displayed with helpful retry suggestions ```typescript rl.on("line", async (userInput: string) => { const trimmedInput = userInput.trim(); if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) { console.log("\nGoodbye!"); rl.close(); process.exit(0); } if (!trimmedInput) { rl.prompt(); return; } messages.push({ role: "user", content: trimmedInput }); console.log("\nAgent is thinking...\n"); try { const stream = streamText({ model: openai("gpt-5"), messages, tools, toolChoice: "auto", stopWhen: stepCountIs(10), onStepFinish: (step) => { for (const toolCall of step.toolCalls) { console.log(`[Using tool: ${toolCall.toolName}]`); } if (step.toolCalls.length > 0) { console.log(""); // Add space after tool calls } }, }); for await (const chunk of stream.textStream) { process.stdout.write(chunk); } console.log("\n\n---\n"); // Get final result for message history const response = await stream.response; if (response?.messages?.length) { messages.push(...response.messages); } } catch (error) { console.error("\nAn error occurred while talking to the agent:"); console.error(error); console.log( "\nYou can try again or restart the app if it keeps happening.\n", ); } finally { rl.prompt(); } }); rl.on("close", async () => { await mcpClient.close(); console.log("\n๐Ÿ‘‹ Session ended."); process.exit(0); }); } main().catch((err) => { console.error("Fatal error:", err); process.exit(1); }); ``` ## Complete Code ```typescript import "dotenv/config"; import { openai } from "@ai-sdk/openai"; import { Composio } from "@composio/core"; import * as readline from "readline"; import { streamText, type ModelMessage, stepCountIs } from "ai"; import { createMCPClient } from "@ai-sdk/mcp"; const composioAPIKey = process.env.COMPOSIO_API_KEY; const composioUserID = process.env.COMPOSIO_USER_ID; if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set"); if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set"); if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set"); const composio = new Composio({ apiKey: composioAPIKey, }); async function main() { // Create a tool router session for the user const session = await composio.create(composioUserID!, { toolkits: ["doppler"], }); const mcpUrl = session.mcp.url; const mcpClient = await createMCPClient({ transport: { type: "http", url: mcpUrl, headers: session.mcp.headers, // Authentication headers for the Composio MCP server }, }); const tools = await mcpClient.tools(); let messages: ModelMessage[] = []; console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n"); console.log( "Ask any questions related to doppler, like summarize my last 5 emails, send an email, etc... :)))\n", ); const rl = readline.createInterface({ input: process.stdin, output: process.stdout, prompt: "> ", }); rl.prompt(); rl.on("line", async (userInput: string) => { const trimmedInput = userInput.trim(); if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) { console.log("\nGoodbye!"); rl.close(); process.exit(0); } if (!trimmedInput) { rl.prompt(); return; } messages.push({ role: "user", content: trimmedInput }); console.log("\nAgent is thinking...\n"); try { const stream = streamText({ model: openai("gpt-5"), messages, tools, toolChoice: "auto", stopWhen: stepCountIs(10), onStepFinish: (step) => { for (const toolCall of step.toolCalls) { console.log(`[Using tool: ${toolCall.toolName}]`); } if (step.toolCalls.length > 0) { console.log(""); // Add space after tool calls } }, }); for await (const chunk of stream.textStream) { process.stdout.write(chunk); } console.log("\n\n---\n"); // Get final result for message history const response = await stream.response; if (response?.messages?.length) { messages.push(...response.messages); } } catch (error) { console.error("\nAn error occurred while talking to the agent:"); console.error(error); console.log( "\nYou can try again or restart the app if it keeps happening.\n", ); } finally { rl.prompt(); } }); rl.on("close", async () => { await mcpClient.close(); console.log("\n๐Ÿ‘‹ Session ended."); process.exit(0); }); } main().catch((err) => { console.error("Fatal error:", err); process.exit(1); }); ``` ## Conclusion You've successfully built a Doppler agent using the Vercel AI SDK with streaming capabilities! This implementation provides a powerful foundation for building AI applications with natural language interfaces and real-time feedback. Key features of this implementation: - Real-time streaming responses for a better user experience with typewriter effect - Live tool execution feedback showing which tools are being used as the agent works - Dynamic tool loading through Composio's Tool Router with secure authentication - Multi-step tool execution with configurable step limits (up to 10 steps) - Comprehensive error handling for robust agent execution - Conversation history maintenance for context-aware responses You can extend this further by adding custom error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows. ## How to build Doppler MCP Agent with another framework - [ChatGPT](https://composio.dev/toolkits/doppler/framework/chatgpt) - [Antigravity](https://composio.dev/toolkits/doppler/framework/antigravity) - [OpenAI Agents SDK](https://composio.dev/toolkits/doppler/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/doppler/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/doppler/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/doppler/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/doppler/framework/codex) - [Cursor](https://composio.dev/toolkits/doppler/framework/cursor) - [VS Code](https://composio.dev/toolkits/doppler/framework/vscode) - [OpenCode](https://composio.dev/toolkits/doppler/framework/opencode) - [OpenClaw](https://composio.dev/toolkits/doppler/framework/openclaw) - [Hermes](https://composio.dev/toolkits/doppler/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/doppler/framework/cli) - [Google ADK](https://composio.dev/toolkits/doppler/framework/google-adk) - [LangChain](https://composio.dev/toolkits/doppler/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/doppler/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/doppler/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/doppler/framework/crew-ai) ## Related Toolkits - [Supabase](https://composio.dev/toolkits/supabase) - Supabase is an open-source backend platform offering scalable Postgres databases, authentication, storage, and real-time APIs. It lets developers build modern apps without managing infrastructure. - [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 MCP? With a standalone Doppler MCP server, the agents and LLMs can only access a fixed set of Doppler tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Doppler and many other apps based on the task at hand, all through a single MCP endpoint. ### Can I use Tool Router MCP with Vercel AI SDK v6? Yes, you can. Vercel AI SDK v6 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 tools. ### Can I manage the permissions and scopes for Doppler while using Tool Router? Yes, absolutely. You can configure which Doppler 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 data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) ยท [Composio docs](https://docs.composio.dev/llms.txt)