# How to integrate Linkhut MCP with Mastra AI

```json
{
  "title": "How to integrate Linkhut MCP with Mastra AI",
  "toolkit": "Linkhut",
  "toolkit_slug": "linkhut",
  "framework": "Mastra AI",
  "framework_slug": "mastra-ai",
  "url": "https://composio.dev/toolkits/linkhut/framework/mastra-ai",
  "markdown_url": "https://composio.dev/toolkits/linkhut/framework/mastra-ai.md",
  "updated_at": "2026-05-12T10:17:42.375Z"
}
```

## Introduction

This guide walks you through connecting Linkhut to Mastra AI using the Composio tool router. By the end, you'll have a working Linkhut agent that can add this article as a private bookmark, list all bookmarks tagged with 'research', update the note on your saved github link through natural language commands.
This guide will help you understand how to give your Mastra AI agent real control over a Linkhut account through Composio's Linkhut MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Linkhut with

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

## TL;DR

Here's what you'll learn:
- Set up your environment so Mastra, OpenAI, and Composio work together
- Create a Tool Router session in Composio that exposes Linkhut tools
- Connect Mastra's MCP client to the Composio generated MCP URL
- Fetch Linkhut tool definitions and attach them as a toolset
- Build a Mastra agent that can reason, call tools, and return structured results
- Run an interactive CLI where you can chat with your Linkhut agent

## What is Mastra AI?

Mastra AI is a TypeScript framework for building AI agents with tool support. It provides a clean API for creating agents that can use external services through MCP.
Key features include:
- MCP Client: Built-in support for Model Context Protocol servers
- Toolsets: Organize tools into logical groups
- Step Callbacks: Monitor and debug agent execution
- OpenAI Integration: Works with OpenAI models via @ai-sdk/openai

## What is the Linkhut MCP server, and what's possible with it?

The Linkhut MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Linkhut account. It provides structured and secure access to all your saved bookmarks, so your agent can organize, tag, retrieve, and manage your URLs and references exactly how you want.
- Bookmark organization and retrieval: Effortlessly ask your agent to fetch, list, or filter all bookmarks, including details like tags, notes, and timestamps.
- Automated link saving: Let your agent add new bookmarks for important websites, articles, or resources—tagged and noted for easy discovery later.
- Tag management and insights: Have your agent pull a list of all used tags, track how often tags appear, and help you keep your bookmark library organized.
- Bookmark editing and updates: Direct your agent to modify titles, descriptions, or tags for any saved link so your collection always stays current and relevant.
- Bookmark cleanup and removal: Ask your agent to delete obsolete or unwanted bookmarks, keeping your Linkhut workspace clean and focused.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `LINKHUT_ADD_BOOKMARK` | Add bookmark | Adds a new bookmark to LinkHut. The bookmark can be marked as private/public and read/unread, with optional tags and notes. |
| `LINKHUT_DELETE_BOOKMARK` | Delete bookmark | This tool allows users to delete a bookmark from their Linkhut account by providing the bookmark URL. It operates independently and only requires the URL parameter to identify and remove the bookmark. |
| `LINKHUT_GET_ALL_TAGS` | Get all tags | Retrieves a list of all tags and their usage counts for the authenticated user. No additional parameters required besides authentication. |
| `LINKHUT_GET_BOOKMARKS` | Get bookmarks | Retrieves bookmarks from the user's Linkhut account with optional filtering. This tool fetches bookmarks from Linkhut and supports filtering by: - Tag: Filter by one or more tags (space-separated) - Date: Filter by a specific date (ISO8601 format) - URL: Get a specific bookmark by its exact URL - Meta: Request additional metadata about bookmarks Returns a list of bookmarks with details including URL, title/description, tags, extended notes, timestamp, privacy status (shared), and read status (toread). |
| `LINKHUT_UPDATE_BOOKMARK` | Update Bookmark | This tool allows users to update an existing bookmark in LinkHut. The tool updates the metadata of a bookmark including its title, description, and tags. |

## Supported Triggers

None listed.

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

The Linkhut MCP server is an implementation of the Model Context Protocol that connects your AI agent to Linkhut. It provides structured and secure access so your agent can perform Linkhut 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 starting, make sure you have:
- Node.js 18 or higher
- A Composio account with an active API key
- An OpenAI API key
- Basic familiarity with TypeScript

### 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 need credits or a connected billing setup to use the models.
- Store the key somewhere safe.
Composio API Key
- Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Go to Settings and copy your API key.
- This key lets your Mastra agent talk to Composio and reach Linkhut through MCP.

### 2. Install dependencies

Install the required packages.
What's happening:
- @composio/core is the Composio SDK for creating MCP sessions
- @mastra/core provides the Agent class
- @mastra/mcp is Mastra's MCP client
- @ai-sdk/openai is the model wrapper for OpenAI
- dotenv loads environment variables from .env
```bash
npm install @composio/core @mastra/core @mastra/mcp @ai-sdk/openai 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
- COMPOSIO_USER_ID tells Composio which user this session belongs to
- OPENAI_API_KEY lets the Mastra agent call OpenAI models
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here
```

### 4. Import libraries and validate environment

What's happening:
- dotenv/config auto loads your .env so process.env.* is available
- openai gives you a Mastra compatible model wrapper
- Agent is the Mastra agent that will call tools and produce answers
- MCPClient connects Mastra to your Composio MCP server
- Composio is used to create a Tool Router session
```typescript
import "dotenv/config";
import { openai } from "@ai-sdk/openai";
import { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) 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 as string,
});
```

### 5. Create a Tool Router session for Linkhut

What's happening:
- create spins up a short-lived MCP HTTP endpoint for this user
- The toolkits array contains "linkhut" for Linkhut access
- session.mcp.url is the MCP URL that Mastra's MCPClient will connect to
```typescript
async function main() {
  const session = await composio.create(
    composioUserID as string,
    {
      toolkits: ["linkhut"],
    },
  );

  const composioMCPUrl = session.mcp.url;
  console.log("Linkhut MCP URL:", composioMCPUrl);
```

### 6. Configure Mastra MCP client and fetch tools

What's happening:
- MCPClient takes an id for this client and a list of MCP servers
- The headers property includes the x-api-key for authentication
- getTools fetches the tool definitions exposed by the Linkhut toolkit
```typescript
const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      nasdaq: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

console.log("Fetching MCP tools from Composio...");
const composioTools = await mcpClient.getTools();
console.log("Number of tools:", Object.keys(composioTools).length);
```

### 7. Create the Mastra agent

What's happening:
- Agent is the core Mastra agent
- name is just an identifier for logging and debugging
- instructions guide the agent to use tools instead of only answering in natural language
- model uses openai("gpt-5") to configure the underlying LLM
```typescript
const agent = new Agent({
    name: "linkhut-mastra-agent",
    instructions: "You are an AI agent with Linkhut tools via Composio.",
    model: "openai/gpt-5",
  });
```

### 8. Set up interactive chat interface

What's happening:
- messages keeps the full conversation history in Mastra's expected format
- agent.generate runs the agent with conversation history and Linkhut toolsets
- maxSteps limits how many tool calls the agent can take in a single run
- onStepFinish is a hook that prints intermediate steps for debugging
```typescript
let messages: AiMessageType[] = [];

console.log("Chat started! Type 'exit' or 'quit' to end.\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({
    id: crypto.randomUUID(),
    role: "user",
    content: trimmedInput,
  });

  console.log("\nAgent is thinking...\n");

  try {
    const response = await agent.generate(messages, {
      toolsets: {
        linkhut: composioTools,
      },
      maxSteps: 8,
    });

    const { text } = response;

    if (text && text.trim().length > 0) {
      console.log(`Agent: ${text}\n`);
        messages.push({
          id: crypto.randomUUID(),
          role: "assistant",
          content: text,
        });
      }
    } catch (error) {
      console.error("\nError:", error);
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    console.log("\nSession ended.");
    await mcpClient.disconnect();
    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 { Agent } from "@mastra/core/agent";
import { MCPClient } from "@mastra/mcp";
import { Composio } from "@composio/core";
import * as readline from "readline";

import type { AiMessageType } from "@mastra/core/agent";

const openaiAPIKey = process.env.OPENAI_API_KEY;
const composioAPIKey = process.env.COMPOSIO_API_KEY;
const composioUserID = process.env.COMPOSIO_USER_ID;

if (!openaiAPIKey) 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 as string });

async function main() {
  const session = await composio.create(composioUserID as string, {
    toolkits: ["linkhut"],
  });

  const composioMCPUrl = session.mcp.url;

  const mcpClient = new MCPClient({
    id: composioUserID as string,
    servers: {
      linkhut: {
        url: new URL(composioMCPUrl),
        requestInit: {
          headers: session.mcp.headers,
        },
      },
    },
    timeout: 30_000,
  });

  const composioTools = await mcpClient.getTools();

  const agent = new Agent({
    name: "linkhut-mastra-agent",
    instructions: "You are an AI agent with Linkhut tools via Composio.",
    model: "openai/gpt-5",
  });

  let messages: AiMessageType[] = [];

  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: "> ",
  });

  rl.prompt();

  rl.on("line", async (input: string) => {
    const trimmed = input.trim();
    if (["exit", "quit"].includes(trimmed.toLowerCase())) {
      rl.close();
      return;
    }

    messages.push({ id: crypto.randomUUID(), role: "user", content: trimmed });

    const { text } = await agent.generate(messages, {
      toolsets: { linkhut: composioTools },
      maxSteps: 8,
    });

    if (text) {
      console.log(`Agent: ${text}\n`);
      messages.push({ id: crypto.randomUUID(), role: "assistant", content: text });
    }

    rl.prompt();
  });

  rl.on("close", async () => {
    await mcpClient.disconnect();
    process.exit(0);
  });
}

main();
```

## Conclusion

You've built a Mastra AI agent that can interact with Linkhut through Composio's Tool Router.
You can extend this further by:
- Adding other toolkits like Gmail, Slack, or GitHub
- Building a web-based chat interface around this agent
- Using multiple MCP endpoints to enable cross-app workflows

## How to build Linkhut MCP Agent with another framework

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

## Related Toolkits

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

## Frequently Asked Questions

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

With a standalone Linkhut MCP server, the agents and LLMs can only access a fixed set of Linkhut tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Linkhut and many other apps based on the task at hand, all through a single MCP endpoint.

### Can I use Tool Router MCP with Mastra AI?

Yes, you can. Mastra AI 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 Linkhut tools.

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

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

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)
