# How to integrate Linkly MCP with LangChain ```json { "title": "How to integrate Linkly MCP with LangChain", "toolkit": "Linkly", "toolkit_slug": "linkly", "framework": "LangChain", "framework_slug": "langchain", "url": "https://composio.dev/toolkits/linkly/framework/langchain", "markdown_url": "https://composio.dev/toolkits/linkly/framework/langchain.md", "updated_at": "2026-10-12T14:15:48.908Z" } ``` ## Introduction This guide walks you through connecting Linkly to LangChain using the Composio tool router. By the end, you'll have a working Linkly agent that can create a tracking link for new product, list all active tracking links, add a retargeting tag to a link through natural language commands. This guide will help you understand how to give your LangChain agent real control over a Linkly account through Composio's Linkly MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Linkly with - [Claude Code](https://composio.dev/toolkits/linkly/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/linkly/framework/claude-cowork) - [OpenAI Agents SDK](https://composio.dev/toolkits/linkly/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/linkly/framework/claude-agents-sdk) - [Codex](https://composio.dev/toolkits/linkly/framework/codex) - [OpenClaw](https://composio.dev/toolkits/linkly/framework/openclaw) - [Hermes](https://composio.dev/toolkits/linkly/framework/hermes-agent) - [Atomic Agent](https://composio.dev/toolkits/linkly/framework/atomic-agent) - [Google ADK](https://composio.dev/toolkits/linkly/framework/google-adk) - [Vercel AI SDK](https://composio.dev/toolkits/linkly/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/linkly/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/linkly/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/linkly/framework/crew-ai) - [Pydantic AI](https://composio.dev/toolkits/linkly/framework/pydantic-ai) - [AutoGen](https://composio.dev/toolkits/linkly/framework/autogen) ## TL;DR Here's what you'll learn: - Get and set up your OpenAI and Composio API keys - Connect your Linkly project to Composio - Create a Tool Router MCP session for Linkly - Initialize an MCP client and retrieve Linkly tools - Build a LangChain agent that can interact with Linkly - 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 Linkly MCP server, and what's possible with it? The Linkly MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Linkly account. It provides structured and secure access to your shortened links, workspaces, and webhook subscriptions, so your agent can create, update, find, list, and delete links on your behalf. - Short link creation and updates: Have your agent create new shortened links or update existing links for your campaigns. - Link lookup and review: Instruct your agent to find a specific shortened link and retrieve its current details. - Link inventory management: Let the agent list links across your account so you can review and manage them. - Workspace discovery: Direct your agent to list the Linkly workspaces available to you before managing their links. - Link and webhook cleanup: Have your agent delete unwanted links, review webhook subscriptions for a link, or remove a webhook subscription from a workspace. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `LINKLY_CREATE_OR_UPDATE_LINK` | Create or Update Link | Tool to create a new shortened link or update an existing one in Linkly. Use when you need to generate a trackable short URL with custom parameters, UTM tracking, retargeting pixels, or Open Graph metadata. To create a new link, provide url and workspace_id. To update an existing link, provide id and the fields you want to change. | | `LINKLY_DELETE_LINK` | Delete Link | Tool to delete a specific link by ID from a workspace. Use when you need to permanently remove a link. This action is permanent and cannot be undone. | | `LINKLY_DELETE_LINKS` | Delete Links | Tool to delete one or more links by their IDs. This action is permanent and cannot be undone. Use when you need to remove links from a workspace. | | `LINKLY_EXPORT_LINKS` | Export Links | Tool to export all links in a workspace as JSON or CSV. Use when you need to retrieve all links for backup, analysis, or migration purposes. | | `LINKLY_GET_CLICK_COUNTERS` | Get Click Counters by Dimension | Tool to retrieve click analytics grouped by a specific dimension (counter). Returns aggregated counts for each unique value of the selected dimension. Use when you need to analyze click patterns by country, platform, browser, referrer, ISP, link, or URL parameters. | | `LINKLY_GET_CLICKS` | Get Click Analytics | Tool to retrieve click analytics for a workspace. Filter by link, date range, country, and more. Returns time-series data suitable for charting. | | `LINKLY_GET_LINK` | Get Link Details | Tool to retrieve detailed information about a specific link by its ID. Use when you need to fetch link configuration, UTM parameters, or click statistics. | | `LINKLY_GET_LINK_BY_ID` | Get Link By ID | Tool to retrieve details for a specific link by ID. Use when you need to fetch information about a shortened link, including its destination URL, click statistics, and configuration settings. | | `LINKLY_LIST_DOMAINS` | List Domains | Tool to retrieve all custom domains configured for a workspace. Use when you need to see available domains for creating short links. | | `LINKLY_LIST_LINKS` | List Links | Tool to get a paginated list of all links in a workspace. Supports search, sorting, and pagination. Returns link details including click statistics. Use when you need to retrieve or search through links. | | `LINKLY_LIST_LINK_WEBHOOKS` | List Link Webhooks | Tool to retrieve all webhook subscriptions for a specific link. Use when you need to see what webhooks are configured for a link. | | `LINKLY_LIST_WORKSPACES` | List Workspaces | Tool to retrieve all workspaces the authenticated user has access to. Use this to discover available workspace IDs for other API calls. | | `LINKLY_LIST_WORKSPACE_WEBHOOKS` | List workspace webhooks | Tool to list all webhook subscriptions for a specific workspace. Use when you need to retrieve or view the configured webhooks for a workspace. | | `LINKLY_SUBSCRIBE_WEBHOOK_TO_LINK` | Subscribe webhook to link | Tool to subscribe a webhook URL to receive notifications when a specific link is clicked. Use when you need to track click events for a shortened link. | | `LINKLY_SUBSCRIBE_WEBHOOK_TO_WORKSPACE` | Subscribe Webhook to Workspace | Tool to subscribe a webhook URL to receive click notifications from a Linkly workspace. Use when you need to set up real-time notifications for link clicks. The webhook will receive POST requests containing click data including country, platform, browser, and other analytics information whenever any link in the workspace is clicked. | | `LINKLY_UNSUBSCRIBE_WEBHOOK_FROM_LINK` | Unsubscribe Webhook from Link | Tool to remove a webhook subscription from a link. Use when you need to stop receiving webhook events for a specific link. | | `LINKLY_UNSUBSCRIBE_WEBHOOK_FROM_WORKSPACE` | Unsubscribe Webhook From Workspace | Tool to remove a webhook subscription from a workspace. Use when you need to unsubscribe a webhook URL from receiving events for a specific workspace. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Linkly MCP server is an implementation of the Model Context Protocol that connects your AI agent to Linkly. It provides structured and secure access so your agent can perform Linkly 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 Linkly 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 Linkly 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 Linkly tools as needed ```python # Create Tool Router session for Linkly session = composio.create( user_id=os.getenv("COMPOSIO_USER_ID"), toolkits=['linkly'] ) url = session.mcp.url ``` ```typescript const session = await composio.create( userId as string, { toolkits: ['linkly'] } ); const url = session.mcp.url; ``` ### 7. Configure the agent with the MCP URL No description provided. ```python client = MultiServerMCPClient({ "linkly-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({ "linkly-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 Linkly 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 Linkly 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=['linkly'] ) url = session.mcp.url client = MultiServerMCPClient({ "linkly-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 Linkly 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: ['linkly'] } ); const url = session.mcp.url; const client = new MultiServerMCPClient({ "linkly-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 Linkly 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 Linkly 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 Linkly MCP Agent with another framework - [Claude Code](https://composio.dev/toolkits/linkly/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/linkly/framework/claude-cowork) - [OpenAI Agents SDK](https://composio.dev/toolkits/linkly/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/linkly/framework/claude-agents-sdk) - [Codex](https://composio.dev/toolkits/linkly/framework/codex) - [OpenClaw](https://composio.dev/toolkits/linkly/framework/openclaw) - [Hermes](https://composio.dev/toolkits/linkly/framework/hermes-agent) - [Atomic Agent](https://composio.dev/toolkits/linkly/framework/atomic-agent) - [Google ADK](https://composio.dev/toolkits/linkly/framework/google-adk) - [Vercel AI SDK](https://composio.dev/toolkits/linkly/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/linkly/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/linkly/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/linkly/framework/crew-ai) - [Pydantic AI](https://composio.dev/toolkits/linkly/framework/pydantic-ai) - [AutoGen](https://composio.dev/toolkits/linkly/framework/autogen) ## Related Toolkits - [Reddit](https://composio.dev/toolkits/reddit) - Reddit is a social news platform with thriving user-driven communities (subreddits). It's the go-to place for discussion, content sharing, and viral marketing. - [Facebook](https://composio.dev/toolkits/facebook) - Facebook is a social media and advertising platform for businesses and creators. It helps you connect, share, and manage content across your public Facebook Pages. - [Linkedin](https://composio.dev/toolkits/linkedin) - LinkedIn is a professional networking platform for connecting, sharing content, and engaging with business opportunities. It's the go-to place for building your professional brand and unlocking new career connections. - [Active campaign](https://composio.dev/toolkits/active_campaign) - ActiveCampaign is a marketing automation and CRM platform for managing email campaigns, sales pipelines, and customer segmentation. It helps businesses engage customers and drive growth through smart automation and targeted outreach. - [ActiveTrail](https://composio.dev/toolkits/active_trail) - ActiveTrail is a user-friendly email marketing and automation platform. It helps you reach subscribers and automate campaigns with ease. - [Adobe Marketing Agent MCP](https://composio.dev/toolkits/adobe_marketing_agent_mcp) - Adobe Marketing Agent MCP is Adobe's hosted MCP service that exposes marketing context, preferences, and agent capabilities. Use it to provide agents with campaign, audience, and analytics context via a managed integration. - [Ahrefs](https://composio.dev/toolkits/ahrefs) - Ahrefs is an SEO and marketing platform for site audits, keyword research, and competitor insights. It helps you improve search rankings and drive organic traffic. - [AimTell](https://composio.dev/toolkits/aimtell) - AimTell is a web push notification platform for managing websites, subscribers, campaigns, segments, and delivery analytics. Use it to send targeted browser notifications and measure engagement across your web push campaigns. - [Amcards](https://composio.dev/toolkits/amcards) - AMCards lets you create and mail personalized greeting cards online. Build stronger customer relationships with easy, automated card campaigns. - [AWeber](https://composio.dev/toolkits/aweber) - AWeber is an email marketing platform for creating campaigns, lists, and landing pages. It helps businesses automate email outreach and measure subscriber engagement. - [Beamer](https://composio.dev/toolkits/beamer) - Beamer is a news and changelog platform for in-app announcements and feature updates. It helps companies boost user engagement by sharing news where users are most active. - [Beehiiv](https://composio.dev/toolkits/beehiiv) - Beehiiv is a newsletter platform for creating and managing publications and subscribers. It helps grow audience engagement and monetize your mailing list. - [Benchmark email](https://composio.dev/toolkits/benchmark_email) - Benchmark Email is a platform for creating, sending, and tracking email campaigns. It's built to help you engage audiences and analyze results—all in one place. - [Bigmailer](https://composio.dev/toolkits/bigmailer) - BigMailer is an email marketing platform for managing multiple brands with white-labeling and automation. It helps teams streamline campaigns and simplify integration with Amazon SES. - [Bitly](https://composio.dev/toolkits/bitly) - Bitly is a link management platform for shortening, customizing, sharing, and tracking links and QR codes. It helps teams create branded links and measure engagement across campaigns. - [BlueFox Email](https://composio.dev/toolkits/bluefox_email) - BlueFox Email is an email API for managing contacts, subscriber lists, and sending transactional and triggered messages. Use it to reliably send transactional and triggered emails and manage subscribers at scale. - [Brandfetch](https://composio.dev/toolkits/brandfetch) - Brandfetch is an API that delivers company logos, colors, and visual branding assets. It helps marketers and developers keep brand visuals consistent everywhere. - [Braze](https://composio.dev/toolkits/braze) - Braze is a customer engagement platform for managing user data, messaging, campaigns, and analytics. Use it to deliver targeted, multi-channel messaging and analyze campaign performance. - [Brevo](https://composio.dev/toolkits/brevo) - Brevo is an all-in-one email and SMS marketing platform for transactional messaging, automation, and CRM. It helps businesses engage customers and streamline communications through powerful campaign tools. - [Buffer](https://composio.dev/toolkits/buffer) - Buffer is a social media management platform for planning, creating, scheduling, and publishing posts across connected channels. It helps teams keep content organized and publish consistently without jumping between social apps. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Linkly MCP? With a standalone Linkly MCP server, the agents and LLMs can only access a fixed set of Linkly tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Linkly 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 Linkly tools. ### Can I manage the permissions and scopes for Linkly while using Tool Router? Yes, absolutely. You can configure which Linkly 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 Linkly data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)