How to integrate Honeyhive MCP with Claude Agent SDK

This guide walks you through connecting Honeyhive to the Claude Agent SDK using the Composio tool router. By the end, you'll have a working Honeyhive agent that can add new datapoints to your evaluation dataset, list all datasets in your honeyhive project, log a batch of model events for analysis through natural language commands. This guide will help you understand how to give your Claude Agent SDK agent real control over a Honeyhive account through Composio's Honeyhive MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Honeyhive is an AI observability and evaluation platform for analyzing LLM apps. It helps teams monitor, debug, and improve AI system reliability faster.

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Introduction

This guide walks you through connecting Honeyhive to the Claude Agent SDK using the Composio tool router. By the end, you'll have a working Honeyhive agent that can add new datapoints to your evaluation dataset, list all datasets in your honeyhive project, log a batch of model events for analysis through natural language commands.

This guide will help you understand how to give your Claude Agent SDK agent real control over a Honeyhive account through Composio's Honeyhive MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

Also integrate Honeyhive with

OpenAI Agents SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • Get and set up your Claude/Anthropic and Composio API keys
  • Install the necessary dependencies
  • Initialize Composio and create a Tool Router session for Honeyhive
  • Configure an AI agent that can use Honeyhive as a tool
  • Run a live chat session where you can ask the agent to perform Honeyhive operations

What is Claude Agent SDK?

The Claude Agent SDK is Anthropic's official framework for building AI agents powered by Claude. It provides a streamlined interface for creating agents with MCP tool support and conversation management.

Key features include:

  • Native MCP Support: Built-in support for Model Context Protocol servers
  • Permission Modes: Control tool execution permissions
  • Streaming Responses: Real-time response streaming for interactive applications
  • Context Manager: Clean async context management for sessions

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

The Honeyhive MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Honeyhive account. It provides structured and secure access to your AI observability platform, so your agent can perform actions like managing datasets, logging model and tool events, evaluating runs, and configuring project settings on your behalf.

  • Dataset management and organization: Create, retrieve, and delete datasets for your AI projects, helping you maintain organized and up-to-date evaluation data.
  • Efficient event logging: Log batches of model or external tool events, enabling comprehensive tracking and analysis of AI system interactions in real-time.
  • Data curation and cleanup: Add new datapoints to datasets or remove specific datapoints, ensuring your evaluation data remains accurate and relevant.
  • Streamlined evaluation workflows: Mark evaluation runs as completed and fetch project configuration details, making it easy to track progress and update run statuses automatically.

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

Composio's Composio SDK helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Composio SDK

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Composio SDK works

The Composio SDK follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Step by step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Composio API Key and Claude/Anthropic API Key
  • Primary know-how of Claude Agents SDK
  • A Honeyhive account
  • Some knowledge of Python
2

Getting API Keys for Claude/Anthropic and Composio

Claude/Anthropic API Key
  • Go to the Anthropic Console and create an API key. You'll need credits to use the models.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.
3

Install dependencies

npm install @anthropic-ai/claude-agent-sdk @composio/core dotenv

Install the Composio SDK and the Claude Agents SDK.

What's happening:

  • @composio/core provides Composio integration for Anthropic
  • @anthropic-ai/claude-agent-sdk is the core agent framework
  • dotenv/config loads environment variables
4

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
ANTHROPIC_API_KEY=your_anthropic_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID identifies the user for session management
  • ANTHROPIC_API_KEY authenticates with Anthropic/Claude
5

Import dependencies

import 'dotenv/config';
import readline from 'node:readline';
import { Composio } from '@composio/core';
import { query, type Options } from "@anthropic-ai/claude-agent-sdk";

dotenv.config();
What's happening:
  • We're importing all necessary libraries including the Claude Agent SDK and Composio
  • The dotenv.config() function loads environment variables from your .env file
  • This setup prepares the foundation for connecting Claude with Honeyhive functionality
6

Create a Composio instance and Tool Router session

async function chat() {
  const { COMPOSIO_API_KEY, USER_ID } = process.env;
  if (!COMPOSIO_API_KEY || !USER_ID) {
    throw new Error('COMPOSIO_API_KEY and USER_ID required in .env');
  }

  const composio = new Composio({ apiKey: COMPOSIO_API_KEY });

  // Create Tool Router session for Honeyhive
  const session = await composio.create(USER_ID, {
    toolkits: ['honeyhive'],
  });
  const mcpUrl = session?.mcp.url;
What's happening:
  • The function checks for the required COMPOSIO_API_KEY environment variable
  • We're creating a Composio instance using our API key
  • The create method creates a Tool Router session for Honeyhive
  • The returned url is the MCP server URL that your agent will use
7

Configure Claude Agent with MCP

const options: Options = {
  permissionMode: 'bypassPermissions',
  mcpServers: {
    composio: {
      type: 'http',
      url: mcpUrl,
      headers: { 'x-api-key': COMPOSIO_API_KEY }
    }
  },
  systemPrompt: 'You are a helpful assistant with access to Honeyhive tools via Composio.',
  maxTurns: 10,
};
What's happening:
  • We're configuring the Claude Agent options with the MCP server URL
  • permissionMode: 'bypassPermissions' allows the agent to execute operations without asking for permission each time
  • The system prompt instructs the agent that it has access to Honeyhive
  • maxTurns: 10 limits the conversation length to prevent excessive API usage
8

Create client and start chat loop

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

  console.log('\nChat started. Type "exit" to quit.\n');

  let isProcessing = false;

  async function ask(prompt: string) {
    isProcessing = true;
    rl.pause();

    process.stdout.write('Claude is thinking...');
    const stream = query({ prompt, options });

    let firstChunk = true;
    for await (const msg of stream) {
      const content = (msg as any).message?.content || (msg as any).content;
      if (Array.isArray(content)) {
        for (const block of content) {
          if (block.type === 'text' && block.text) {
            if (firstChunk) {
              process.stdout.write('\r\x1b[K');
              process.stdout.write('Claude: ');
              firstChunk = false;
            }
            process.stdout.write(block.text);
          }
        }
      }
    }
    process.stdout.write('\n\n');

    isProcessing = false;
    rl.resume();
    rl.prompt();
  }

  rl.on('line', async (line) => {
    if (isProcessing) return;

    const input = line.trim();
    if (input === 'exit') {
      rl.close();
      process.exit(0);
    }
    if (input) await ask(input);
    else rl.prompt();
  });

  await ask('What can you help me with?');
}
What's happening:
  • The readline interface is created to handle user input and output
  • The query function is used to send the user's input to the agent
  • The chat loop continues until the user types 'exit' or 'quit'
9

Run the application

try {
  await chat();
} catch (error) {
  console.error(error);
  process.exit(1);
}
What's happening:
  • The chat function is the entry point for the application
  • The try-catch block is used to handle any errors that occur

Complete Code

Here's the complete code to get you started with Honeyhive and Claude Agent SDK:

import 'dotenv/config';
import readline from 'node:readline';
import { Composio } from '@composio/core';
import { query, type Options } from "@anthropic-ai/claude-agent-sdk";

async function chat() {
  const { COMPOSIO_API_KEY, USER_ID } = process.env;
  if (!COMPOSIO_API_KEY || !USER_ID) {
    throw new Error('COMPOSIO_API_KEY and USER_ID required in .env');
  }

  const composio = new Composio({ apiKey: COMPOSIO_API_KEY });
  const session = await composio.create(USER_ID, {
    toolkits: ['honeyhive']
  });
  const mcp_url = session?.mcp.url;

  const options: Options = {
    permissionMode: 'bypassPermissions',
    mcpServers: {
      composio: {
        type: 'http',
        url: mcp_url,
        headers: { 'x-api-key': COMPOSIO_API_KEY }
      }
    },
    systemPrompt: 'You are a helpful assistant with access to Honeyhive tools via Composio.',
    maxTurns: 10,
  };

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

  console.log('\nChat started. Type "exit" to quit.\n');

  let isProcessing = false;

  async function ask(prompt: string) {
    isProcessing = true;
    rl.pause();

    process.stdout.write('Claude is thinking...');
    const stream = query({ prompt, options });

    let firstChunk = true;
    for await (const msg of stream) {
      const content = (msg as any).message?.content || (msg as any).content;
      if (Array.isArray(content)) {
        for (const block of content) {
          if (block.type === 'text' && block.text) {
            if (firstChunk) {
              process.stdout.write('\r\x1b[K');
              process.stdout.write('Claude: ');
              firstChunk = false;
            }
            process.stdout.write(block.text);
          }
        }
      }
    }
    process.stdout.write('\n\n');

    isProcessing = false;
    rl.resume();
    rl.prompt();
  }

  rl.on('line', async (line) => {
    if (isProcessing) return;

    const input = line.trim();
    if (input === 'exit') {
      rl.close();
      process.exit(0);
    }
    if (input) await ask(input);
    else rl.prompt();
  });

  await ask('What can you help me with?');
}

try {
  await chat();
} catch (error) {
  console.error(error);
  process.exit(1);
}

Conclusion

You've successfully built a Claude Agent SDK agent that can interact with Honeyhive through Composio's Tool Router.

Key features:

  • Native MCP support through Claude's agent framework
  • Streaming responses for real-time interaction
  • Permission bypass for smooth automated workflows
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.
TOOLS

Supported Tools

Every Honeyhive action and event your agent gets out of the box.

Add datapoints to dataset

Tool to add datapoints to a dataset.

Compare Experiment Runs

Tool to retrieve experiment comparison between two evaluation runs.

Compare Runs Events

Tool to compare events between two experiment runs side-by-side.

Batch Create Datapoints

Tool to create multiple datapoints in a single batch operation.

Create Batch Model Events

Tool to create multiple model events in a single request.

Create Batch Tool Events

Tool to log a batch of external API calls as tool events.

Create Configuration

Creates a new configuration in HoneyHive for managing LLM or pipeline settings.

Create Datapoint

Tool to create a new datapoint with input-output pairs.

Create Dataset

Tool to create a dataset.

Create Event

Tool to create a new event in HoneyHive to track execution of different parts of your application.

Create Metric

Tool to create a new metric in HoneyHive.

Create Model Event

Tool to create a new model event to log LLM call data.

Create Tool

Creates a new tool definition in a HoneyHive project.

Delete Datapoint

Tool to delete a specific datapoint by its ID.

Delete Dataset

Tool to delete a dataset by ID.

End Evaluation Run

Tool to update an evaluation run's status and metadata.

Get Configurations

Tool to retrieve a list of configurations.

Get Datasets

Retrieve datasets from HoneyHive for a specified project.

Get Events

Tool to query events with filters and projections from HoneyHive.

Get Events By Session ID

Tool to retrieve the complete tree of nested events for a specific session.

Get Events Chart

Tool to retrieve charting and analytics data for events over time.

Get Metrics

Retrieves all metrics associated with a HoneyHive project.

Get Projects

Tool to retrieve all projects in the HoneyHive account.

Get Evaluation Run Details

Tool to get details of an evaluation run by its UUID.

Get Run Metrics

Tool to get event metrics for an experiment run.

Get Evaluation Runs

Tool to retrieve a list of evaluation runs from HoneyHive.

Get Runs Schema

Tool to retrieve the schema for experiment runs in HoneyHive.

Get Session

Retrieve a complete session tree by session ID from HoneyHive.

List Tools

Tool to list all available Honeyhive tools.

Retrieve Datapoint

Retrieve a specific datapoint by its ID from HoneyHive.

Retrieve Datapoints

Retrieve datapoints from a HoneyHive project.

Retrieve Events

Retrieve and export events from a HoneyHive project.

Retrieve Experiment Result

Tool to retrieve the result of a specific experiment run.

Start Evaluation Run

Creates a new evaluation run to group and track multiple session events for analysis.

Start Session

Start a new HoneyHive session for tracing and observability.

Update Configuration

Tool to update an existing HoneyHive configuration.

Update Datapoint

Update an existing datapoint by ID.

Update Dataset

Tool to update an existing dataset.

Update Event

Update an existing HoneyHive event by ID.

Update Metric

Tool to update an existing metric.

Update Project

Updates an existing HoneyHive project's name or description.

Update Tool

Tool to update an existing tool in HoneyHive.

FRAMEWORKS

How to build Honeyhive MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Honeyhive MCP with OpenAI Agents SDK

Claude Code logo

Claude Code

Use Honeyhive MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Honeyhive MCP with Claude Cowork

Codex logo

Codex

Use Honeyhive MCP with Codex

OpenClaw logo

OpenClaw

Use Honeyhive MCP with OpenClaw

Hermes logo

Hermes

Use Honeyhive MCP with Hermes

CLI logo

CLI

Use Honeyhive MCP with CLI

Google ADK logo

Google ADK

Use Honeyhive MCP with Google ADK

LangChain logo

LangChain

Use Honeyhive MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Honeyhive MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Honeyhive MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Honeyhive MCP with LlamaIndex

CrewAI logo

CrewAI

Use Honeyhive MCP with CrewAI

FAQ

Frequently asked questions

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

Yes, you can. Claude Agent SDK 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 Honeyhive tools.

Yes, absolutely. You can configure which Honeyhive 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.

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 Honeyhive data and credentials are handled as safely as possible.

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As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

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Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

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