# How to integrate Jigsawstack MCP with LangChain ```json { "title": "How to integrate Jigsawstack MCP with LangChain", "toolkit": "Jigsawstack", "toolkit_slug": "jigsawstack", "framework": "LangChain", "framework_slug": "langchain", "url": "https://composio.dev/toolkits/jigsawstack/framework/langchain", "markdown_url": "https://composio.dev/toolkits/jigsawstack/framework/langchain.md", "updated_at": "2026-05-12T10:16:25.125Z" } ``` ## Introduction This guide walks you through connecting Jigsawstack to LangChain using the Composio tool router. By the end, you'll have a working Jigsawstack agent that can generate a logo from this business idea, analyze customer review sentiment for this product, convert this sales script into an audio file through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Jigsawstack account through Composio's Jigsawstack MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Jigsawstack with - [OpenAI Agents SDK](https://composio.dev/toolkits/jigsawstack/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/jigsawstack/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/jigsawstack/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/jigsawstack/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/jigsawstack/framework/codex) - [OpenClaw](https://composio.dev/toolkits/jigsawstack/framework/openclaw) - [Hermes](https://composio.dev/toolkits/jigsawstack/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/jigsawstack/framework/cli) - [Google ADK](https://composio.dev/toolkits/jigsawstack/framework/google-adk) - [Vercel AI SDK](https://composio.dev/toolkits/jigsawstack/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/jigsawstack/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/jigsawstack/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/jigsawstack/framework/crew-ai) ## TL;DR Here's what you'll learn: - Get and set up your OpenAI and Composio API keys - Connect your Jigsawstack project to Composio - Create a Tool Router MCP session for Jigsawstack - Initialize an MCP client and retrieve Jigsawstack tools - Build a LangChain agent that can interact with Jigsawstack - Set up an interactive chat interface for testing ## What is LangChain? LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context. Key features include: - Agent Framework: Build agents that can use tools and make decisions - MCP Integration: Connect to external services through Model Context Protocol adapters - Memory Management: Maintain conversation history across interactions - Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers ## What is the Jigsawstack MCP server, and what's possible with it? The Jigsawstack MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Jigsawstack account. It provides structured and secure access to Jigsawstack's suite of custom AI models, so your agent can perform actions like generating images, analyzing sentiment, converting text to speech, and running smart web searches on your behalf. - AI-powered image generation: Instantly create custom images from any text prompt, perfect for visual content, ideation, or creative tasks. - Text sentiment analysis: Have your agent classify the emotional tone of written content, detecting positive, negative, or neutral sentiment for feedback, moderation, or analytics. - Natural text-to-speech synthesis: Convert any text into clear, natural-sounding audio files, enabling voice experiences or accessibility features in your workflows. - Enhanced web search with AI summaries: Perform smart, geo-aware web searches and get concise, AI-generated overviews for quick research and information gathering. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `JIGSAWSTACK_CHECK_NSFW` | Check Image for NSFW Content | Tool to detect NSFW content in images. Use when you need to quickly detect nudity, violence, hentai, porn and other NSFW content in images. | | `JIGSAWSTACK_CHECK_PROFANITY` | Check Profanity | Tool to check text for profanity and inappropriate language. Use when you need to validate user-generated content, filter inappropriate language, or sanitize text input. | | `JIGSAWSTACK_CHECK_SPAM` | Check Spam | Tool to perform spam check analysis on text. Use when you need to detect spam content and get a spam confidence score. | | `JIGSAWSTACK_CHECK_SPELLING` | Check Spelling | Tool to check and correct spelling errors in text. Use when you need to validate text for spelling mistakes and get correction suggestions. | | `JIGSAWSTACK_CLASSIFY_CONTENT` | Classify Content | Tool to classify text and image datasets using custom labels. Use when you need to categorize content into predefined labels. | | `JIGSAWSTACK_CONVERT_HTML_TO_ANY` | Convert HTML to Image or PDF | Tool to convert HTML to images (PNG/JPEG/WEBP) or PDF, or capture website screenshots. Use when you need to generate visual representations of HTML content or web pages. | | `JIGSAWSTACK_CREATE_EMBEDDING_V2` | Create Embedding V2 | Tool to generate enhanced vector embeddings with speaker fingerprint support using the v2 model. Use when you need to create embeddings from text, images, audio, or PDF files. | | `JIGSAWSTACK_CREATE_PREDICTION` | Create Prediction | Tool to forecast time series data using AI-powered prediction. Use when you need to predict future values based on historical data patterns. | | `JIGSAWSTACK_CREATE_PROMPT` | Create Prompt | Tool to create a new prompt in the Prompt Engine for reusable LLM interactions. Use when you need to store and manage prompt templates with variable inputs. | | `JIGSAWSTACK_CREATE_VOICE_CLONE` | Create Voice Clone | Tool to create a cloned voice for text-to-speech synthesis. Use when you need to clone a voice from an audio sample for later use in TTS operations. | | `JIGSAWSTACK_DETECT_OBJECTS` | Detect Objects in Image | Tool to recognize and identify objects within an image using computer vision AI. Use when you need to detect and locate objects in images. | | `JIGSAWSTACK_EXTRACT_VOCR` | Extract Data with Vision OCR | Tool to recognize, describe and retrieve data within images with great accuracy using Vision OCR. Use when you need to extract text, data fields, or descriptions from images or PDFs. | | `JIGSAWSTACK_GET_SEARCH_SUGGESTIONS` | Get Search Suggestions | Tool to get real-time search suggestions for a given query. Use when you need to provide autocomplete suggestions or related search queries. | | `JIGSAWSTACK_GET_SENTIMENT` | Get Sentiment | Tool to retrieve sentiment analysis via GET request. Use when you need to classify text into positive, negative, or neutral sentiment using a GET endpoint. | | `JIGSAWSTACK_IMAGE_GENERATION` | Generate Image from Prompt | Tool to generate images from text prompts. Use when you need visual content created from a prompt. | | `JIGSAWSTACK_LIST_PROMPTS` | List Prompts | Tool to list all prompts stored in the Prompt Engine. Use when you need to retrieve or view stored prompts. | | `JIGSAWSTACK_RUN_PROMPT_BY_ID` | Run Prompt By ID | Tool to execute a stored prompt using its prompt engine ID. Use when you need to run a pre-configured prompt template with dynamic input values. | | `JIGSAWSTACK_SCRAPE_WEBSITE` | Scrape Website | Tool to scrape any website and extract structured data using AI-powered element prompts or CSS selectors. Use when you need to extract specific information from web pages without writing custom scraping code. Supports both URL-based scraping and direct HTML content parsing. | | `JIGSAWSTACK_SENTIMENT_ANALYSIS` | Sentiment Analysis | Tool to analyze text sentiment. Use when you need to classify text into positive, negative, or neutral sentiment. | | `JIGSAWSTACK_SUMMARIZE_TEXT` | Summarize Text | Tool to generate concise, intelligent summaries of text or documents with AI. Use when you need to condense long content into bullet points or paragraphs. | | `JIGSAWSTACK_TEXT_TO_SPEECH` | Text to Speech | Tool to convert text to natural-sounding speech. Use when you need to generate an audio file from text input. | | `JIGSAWSTACK_TRANSLATE_TEXT` | Translate Text | Tool to translate text from one language to another. Use when you need to convert text between different languages with automatic language detection support. | | `JIGSAWSTACK_WEB_SEARCH` | Web Search | Tool to perform AI-powered web search with AI overview and geo-aware results. Use when you need concise search results enriched with AI summary and location context. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Jigsawstack MCP server is an implementation of the Model Context Protocol that connects your AI agent to Jigsawstack. It provides structured and secure access so your agent can perform Jigsawstack 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 No description provided. ### 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 dependencies No description provided. ```python pip install composio-langchain langchain-mcp-adapters langchain python-dotenv ``` ```typescript npm install @composio/langchain @langchain/core @langchain/openai @langchain/mcp-adapters dotenv ``` ### 3. Set up environment variables Create a .env file in your project root. What's happening: - COMPOSIO_API_KEY authenticates your requests to Composio's API - COMPOSIO_USER_ID identifies the user for session management - OPENAI_API_KEY enables access to OpenAI's language models ```bash COMPOSIO_API_KEY=your_composio_api_key_here COMPOSIO_USER_ID=your_composio_user_id_here OPENAI_API_KEY=your_openai_api_key_here ``` ### 4. Import dependencies No description provided. ```python from langchain_mcp_adapters.client import MultiServerMCPClient from langchain.agents import create_agent from dotenv import load_dotenv from composio import Composio import asyncio import os load_dotenv() ``` ```typescript import { Composio } from '@composio/core'; import { LangchainProvider } from '@composio/langchain'; import { MultiServerMCPClient } from "@langchain/mcp-adapters"; import { createAgent } from "langchain"; import * as readline from 'readline'; import 'dotenv/config'; dotenv.config(); ``` ### 5. Initialize Composio client What's happening: - We're loading the COMPOSIO_API_KEY from environment variables and validating it exists - Creating a Composio instance that will manage our connection to Jigsawstack tools - Validating that COMPOSIO_USER_ID is also set before proceeding ```python async def main(): composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) if not os.getenv("COMPOSIO_API_KEY"): raise ValueError("COMPOSIO_API_KEY is not set") if not os.getenv("COMPOSIO_USER_ID"): raise ValueError("COMPOSIO_USER_ID is not set") ``` ```typescript const composioApiKey = process.env.COMPOSIO_API_KEY; const userId = process.env.COMPOSIO_USER_ID; if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set'); if (!userId) throw new Error('COMPOSIO_USER_ID is not set'); async function main() { const composio = new Composio({ apiKey: composioApiKey as string, provider: new LangchainProvider() }); ``` ### 6. Create a Tool Router session What's happening: - We're creating a Tool Router session that gives your agent access to Jigsawstack tools - The create method takes the user ID and specifies which toolkits should be available - The returned session.mcp.url is the MCP server URL that your agent will use - This approach allows the agent to dynamically load and use Jigsawstack tools as needed ```python # Create Tool Router session for Jigsawstack session = composio.create( user_id=os.getenv("COMPOSIO_USER_ID"), toolkits=['jigsawstack'] ) url = session.mcp.url ``` ```typescript const session = await composio.create( userId as string, { toolkits: ['jigsawstack'] } ); const url = session.mcp.url; ``` ### 7. Configure the agent with the MCP URL No description provided. ```python client = MultiServerMCPClient({ "jigsawstack-agent": { "transport": "streamable_http", "url": session.mcp.url, "headers": { "x-api-key": os.getenv("COMPOSIO_API_KEY") } } }) tools = await client.get_tools() agent = create_agent("gpt-5", tools) ``` ```typescript const client = new MultiServerMCPClient({ "jigsawstack-agent": { transport: "http", url: url, headers: { "x-api-key": process.env.COMPOSIO_API_KEY } } }); const tools = await client.getTools(); const agent = createAgent({ model: "gpt-5", tools }); ``` ### 8. Set up interactive chat interface No description provided. ```python conversation_history = [] print("Chat started! Type 'exit' or 'quit' to end the conversation.\n") print("Ask any Jigsawstack related question or task to the agent.\n") while True: user_input = input("You: ").strip() if user_input.lower() in ['exit', 'quit', 'bye']: print("\nGoodbye!") break if not user_input: continue conversation_history.append({"role": "user", "content": user_input}) print("\nAgent is thinking...\n") response = await agent.ainvoke({"messages": conversation_history}) conversation_history = response['messages'] final_response = response['messages'][-1].content print(f"Agent: {final_response}\n") ``` ```typescript let conversationHistory: any[] = []; console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n"); console.log("Ask any Jigsawstack related question or task to the agent.\n"); const rl = readline.createInterface({ input: process.stdin, output: process.stdout, prompt: 'You: ' }); 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; } conversationHistory.push({ role: "user", content: trimmedInput }); console.log("\nAgent is thinking...\n"); const response = await agent.invoke({ messages: conversationHistory }); conversationHistory = response.messages; const finalResponse = response.messages[response.messages.length - 1]?.content; console.log(`Agent: ${finalResponse}\n`); rl.prompt(); }); rl.on('close', () => { console.log('\n👋 Session ended.'); process.exit(0); }); ``` ### 9. Run the application No description provided. ```python if __name__ == "__main__": asyncio.run(main()) ``` ```typescript main().catch((err) => { console.error('Fatal error:', err); process.exit(1); }); ``` ## Complete Code ```python from langchain_mcp_adapters.client import MultiServerMCPClient from langchain.agents import create_agent from dotenv import load_dotenv from composio import Composio import asyncio import os load_dotenv() async def main(): composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY")) if not os.getenv("COMPOSIO_API_KEY"): raise ValueError("COMPOSIO_API_KEY is not set") if not os.getenv("COMPOSIO_USER_ID"): raise ValueError("COMPOSIO_USER_ID is not set") session = composio.create( user_id=os.getenv("COMPOSIO_USER_ID"), toolkits=['jigsawstack'] ) url = session.mcp.url client = MultiServerMCPClient({ "jigsawstack-agent": { "transport": "streamable_http", "url": url, "headers": { "x-api-key": os.getenv("COMPOSIO_API_KEY") } } }) tools = await client.get_tools() agent = create_agent("gpt-5", tools) conversation_history = [] print("Chat started! Type 'exit' or 'quit' to end the conversation.\n") print("Ask any Jigsawstack related question or task to the agent.\n") while True: user_input = input("You: ").strip() if user_input.lower() in ['exit', 'quit', 'bye']: print("\nGoodbye!") break if not user_input: continue conversation_history.append({"role": "user", "content": user_input}) print("\nAgent is thinking...\n") response = await agent.ainvoke({"messages": conversation_history}) conversation_history = response['messages'] final_response = response['messages'][-1].content print(f"Agent: {final_response}\n") if __name__ == "__main__": asyncio.run(main()) ``` ```typescript import { Composio } from '@composio/core'; import { LangchainProvider } from '@composio/langchain'; import { MultiServerMCPClient } from "@langchain/mcp-adapters"; import { createAgent } from "langchain"; import * as readline from 'readline'; import 'dotenv/config'; const composioApiKey = process.env.COMPOSIO_API_KEY; const userId = process.env.COMPOSIO_USER_ID; if (!composioApiKey) throw new Error('COMPOSIO_API_KEY is not set'); if (!userId) throw new Error('COMPOSIO_USER_ID is not set'); async function main() { const composio = new Composio({ apiKey: composioApiKey as string, provider: new LangchainProvider() }); const session = await composio.create( userId as string, { toolkits: ['jigsawstack'] } ); const url = session.mcp.url; const client = new MultiServerMCPClient({ "jigsawstack-agent": { transport: "http", url: url, headers: { "x-api-key": process.env.COMPOSIO_API_KEY } } }); const tools = await client.getTools(); const agent = createAgent({ model: "gpt-5", tools }); let conversationHistory: any[] = []; console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n"); console.log("Ask any Jigsawstack related question or task to the agent.\n"); const rl = readline.createInterface({ input: process.stdin, output: process.stdout, prompt: 'You: ' }); 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; } conversationHistory.push({ role: "user", content: trimmedInput }); console.log("\nAgent is thinking...\n"); const response = await agent.invoke({ messages: conversationHistory }); conversationHistory = response.messages; const finalResponse = response.messages[response.messages.length - 1]?.content; console.log(`Agent: ${finalResponse}\n`); rl.prompt(); }); rl.on('close', () => { console.log('\nSession ended.'); process.exit(0); }); } main().catch((err) => { console.error('Fatal error:', err); process.exit(1); }); ``` ## Conclusion You've successfully built a LangChain agent that can interact with Jigsawstack through Composio's Tool Router. Key features of this implementation: - Dynamic tool loading through Composio's Tool Router - Conversation history maintenance for context-aware responses - Async Python provides clean, efficient execution of agent workflows You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows. ## How to build Jigsawstack MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/jigsawstack/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/jigsawstack/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/jigsawstack/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/jigsawstack/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/jigsawstack/framework/codex) - [OpenClaw](https://composio.dev/toolkits/jigsawstack/framework/openclaw) - [Hermes](https://composio.dev/toolkits/jigsawstack/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/jigsawstack/framework/cli) - [Google ADK](https://composio.dev/toolkits/jigsawstack/framework/google-adk) - [Vercel AI SDK](https://composio.dev/toolkits/jigsawstack/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/jigsawstack/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/jigsawstack/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/jigsawstack/framework/crew-ai) ## Related Toolkits - [Composio](https://composio.dev/toolkits/composio) - Composio is an integration platform that connects AI agents with hundreds of business tools. It streamlines authentication and lets you trigger actions across services—no custom code needed. - [Composio search](https://composio.dev/toolkits/composio_search) - Composio search is a unified web search toolkit spanning travel, e-commerce, news, financial markets, images, and more. It lets you and your apps tap into up-to-date web data from a single, easy-to-integrate service. - [Perplexityai](https://composio.dev/toolkits/perplexityai) - Perplexityai delivers natural, conversational AI models for generating human-like text. Instantly get context-aware, high-quality responses for chat, search, or complex workflows. - [Browser tool](https://composio.dev/toolkits/browser_tool) - Browser tool is a virtual browser integration that lets AI agents interact with the web programmatically. It enables automated browsing, scraping, and action-taking from any AI workflow. - [Ai ml api](https://composio.dev/toolkits/ai_ml_api) - Ai ml api is a suite of AI/ML models for natural language and image tasks. It provides fast, scalable access to advanced AI capabilities for your apps and workflows. - [Aivoov](https://composio.dev/toolkits/aivoov) - Aivoov is an AI-powered text-to-speech platform offering 1,000+ voices in over 150 languages. Instantly turn written content into natural, human-like audio for any application. - [All images ai](https://composio.dev/toolkits/all_images_ai) - All-Images.ai is an AI-powered image generation and management platform. It helps you create, search, and organize images effortlessly with advanced AI capabilities. - [Anthropic administrator](https://composio.dev/toolkits/anthropic_administrator) - Anthropic administrator is an API for managing Anthropic organizational resources like members, workspaces, and API keys. It helps you automate admin tasks and streamline resource management across your Anthropic organization. - [Api labz](https://composio.dev/toolkits/api_labz) - Api labz is a platform offering a suite of AI-driven APIs and workflow tools. It helps developers automate tasks and build smarter, more efficient applications. - [Apipie ai](https://composio.dev/toolkits/apipie_ai) - Apipie ai is an AI model aggregator offering a single API for accessing top AI models from multiple providers. It helps developers build cost-efficient, latency-optimized AI solutions without juggling multiple integrations. - [Astica ai](https://composio.dev/toolkits/astica_ai) - Astica ai provides APIs for computer vision, NLP, and voice synthesis. Integrate advanced AI features into your app with a single API key. - [Bigml](https://composio.dev/toolkits/bigml) - BigML is a machine learning platform that lets you build, train, and deploy predictive models from your data. Its intuitive interface and robust API make machine learning accessible and efficient. - [Botbaba](https://composio.dev/toolkits/botbaba) - Botbaba is a platform for building, managing, and deploying conversational AI chatbots across messaging channels. It streamlines chatbot automation, making it easier to integrate AI into customer interactions. - [Botpress](https://composio.dev/toolkits/botpress) - Botpress is an open-source platform for building, deploying, and managing chatbots. It helps teams automate conversations and deliver rich, interactive messaging experiences. - [Chatbotkit](https://composio.dev/toolkits/chatbotkit) - Chatbotkit is a platform for building and managing AI-powered chatbots using robust APIs and SDKs. It lets you easily add conversational AI to your apps for better user engagement. - [Cody](https://composio.dev/toolkits/cody) - Cody is an AI assistant built for businesses, trained on your company's knowledge and data. It delivers instant answers and insights, tailored for your team. - [Context7 MCP](https://composio.dev/toolkits/context7_mcp) - Context7 MCP delivers live, version-specific code docs and examples right from the source. It helps developers and AI agents instantly retrieve authoritative programming info—no more out-of-date docs. - [Customgpt](https://composio.dev/toolkits/customgpt) - CustomGPT.ai lets you build and deploy chatbots tailored to your own data and business needs. Get precise and context-aware AI conversations without writing code. - [Datarobot](https://composio.dev/toolkits/datarobot) - Datarobot is a machine learning platform that automates model development, deployment, and monitoring. It empowers organizations to quickly gain predictive insights from large datasets. - [Deepgram](https://composio.dev/toolkits/deepgram) - Deepgram is an AI-powered speech recognition platform for accurate audio transcription and understanding. It enables fast, scalable speech-to-text with advanced audio intelligence features. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Jigsawstack MCP? With a standalone Jigsawstack MCP server, the agents and LLMs can only access a fixed set of Jigsawstack tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Jigsawstack and many other apps based on the task at hand, all through a single MCP endpoint. ### Can I use Tool Router MCP with LangChain? Yes, you can. LangChain 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 Jigsawstack tools. ### Can I manage the permissions and scopes for Jigsawstack while using Tool Router? Yes, absolutely. You can configure which Jigsawstack 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 Jigsawstack data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)