How to integrate Rkvst MCP with CrewAI

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Introduction

This guide walks you through connecting Rkvst to CrewAI using the Composio tool router. By the end, you'll have a working Rkvst agent that can download attachment from latest asset event, show details of asset by uuid, retrieve metadata for a specific event, get public asset event information through natural language commands.

This guide will help you understand how to give your CrewAI agent real control over a Rkvst account through Composio's Rkvst MCP server.

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

TL;DR

Here's what you'll learn:
  • Get a Composio API key and configure your Rkvst connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Rkvst
  • Build a conversational loop where your agent can execute Rkvst operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

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

The Rkvst MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Rkvst account. It provides structured and secure access to your supply chain evidence data, so your agent can perform actions like retrieving asset details, verifying event authenticity, downloading attachments, and managing chain of custody records on your behalf.

  • Asset and event retrieval: Instantly fetch detailed information about assets, events, or public assets by their unique identifiers, including historical state data.
  • Chain of custody verification: Have your agent review event metadata and associated trails to ensure data authenticity and transparency throughout your supply chain.
  • Download evidence attachments: Let your agent securely download raw binary attachments associated with supply chain events for auditing or record-keeping.
  • App and member inspection: Effortlessly pull configuration and credential details for app registrations or retrieve member and IAM subject information to monitor access and permissions.
  • Tenancy and blob management: Retrieve tenancy details or access specific data blobs related to your supply chain records for better oversight and control.

Supported Tools & Triggers

Tools
Download Event AttachmentTool to download an attachment from a specified event on an asset.
Get App RegistrationTool to retrieve details for a given app registration id.
Get AssetTool to retrieve details for a given asset.
Get BlobTool to retrieve details of a blob by id.
Get EventTool to retrieve details of a specified event.
Get IAM SubjectTool to retrieve iam subject details.
Get MemberTool to retrieve details for a given member id.
Get Public AssetTool to retrieve details for a public asset.
Get Public Asset EventTool to retrieve a specific public asset event.
Get TenancyTool to retrieve details for a specific tenancy.
List App RegistrationsTool to list all app registrations.
List Asset EventsTool to list events for a specified asset.
List AssetsTool to list all assets with optional pagination and filters.
List IAM SubjectsTool to list iam subjects.
List MembersTool to list all tenant members.
List Public Asset EventsTool to list events for a specific public asset.
List Public AssetsTool to list all public assets.
List TenanciesTool to list all tenancies.
Promote MemberTool to promote a tenant member to owner role.
Retrieve asset attachment metadataTool to retrieve metadata for an attachment on a specified asset.
Retrieve CapsTool to retrieve resource limit quotas for a specified service.
Retrieve Event Attachment MetadataTool to retrieve metadata for an attachment on a specified event.
Retrieve Public Asset Attachment MetadataTool to retrieve metadata for an attachment on a specified public asset.
Retrieve Public Event Attachment MetadataTool to retrieve metadata for an attachment on a public asset event.
Search EventsTool to search events matching filter criteria with pagination.
Update App RegistrationTool to update an application's display name or custom claims.

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

What is Tool Router?

Composio's Tool Router 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 Tool Router

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

How the Tool Router works

The Tool Router 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

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Rkvst connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard 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.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.

Install dependencies

bash
pip install composio crewai crewai-tools python-dotenv
What's happening:
  • composio connects your agent to Rkvst via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools includes MCP helpers
  • python-dotenv loads environment variables from .env

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model

Import dependencies

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional import if you plan to adapt tools
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Rkvst MCP URL

Create a Composio Tool Router session for Rkvst

python
composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
session = composio.create(
    user_id=os.getenv("USER_ID"),
    toolkits=["rkvst"],
)
url = session.mcp.url
What's happening:
  • You create a Rkvst only session through Composio
  • Composio returns an MCP HTTP URL that exposes Rkvst tools

Configure the LLM

python
llm = LLM(
    model="gpt-5-mini",
    api_key=os.getenv("OPENAI_API_KEY"),
)
What's happening:
  • CrewAI will call this LLM for planning and responses
  • You can swap in a different model if needed

Attach the MCP server and create the agent

python
toolkit_agent = Agent(
    role="Rkvst Assistant",
    goal="Help users interact with Rkvst through natural language commands",
    backstory=(
        "You are an expert assistant with access to Rkvst tools. "
        "You can perform various Rkvst operations on behalf of the user."
    ),
    mcps=[
        MCPServerHTTP(
            url=url,
            streamable=True,
            cache_tools_list=True,
            headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
        ),
    ],
    llm=llm,
    verbose=True,
    max_iter=10,
)
What's happening:
  • MCPServerHTTP connects the agent to the Rkvst MCP endpoint
  • cache_tools_list saves a tools catalog for faster subsequent runs
  • verbose helps you see what the agent is doing

Add a REPL loop with Task and Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to perform Rkvst operations.\n")

conversation_context = ""

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Based on the conversation history:\n{conversation_context}\n\n"
            f"Current user request: {user_input}\n\n"
            f"Please help the user with their Rkvst related request."
        ),
        expected_output="A helpful response addressing the user's request",
        agent=toolkit_agent,
    )

    crew = Crew(
        agents=[toolkit_agent],
        tasks=[task],
        verbose=False,
    )

    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's happening:
  • You build a simple chat loop and keep a running context
  • Each user turn becomes a Task handled by the same agent
  • Crew executes the task and returns a response

Run the application

python
if __name__ == "__main__":
    main()
What's happening:
  • Standard Python entry point so you can run python crewai_rkvst_agent.py

Complete Code

Here's the complete code to get you started with Rkvst and CrewAI:

python
# file: crewai_rkvst_agent.py
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()

def main():
    # Initialize Composio and create a Rkvst session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["rkvst"],
    )
    url = session.mcp.url

    # Configure LLM
    llm = LLM(
        model="gpt-5-mini",
        api_key=os.getenv("OPENAI_API_KEY"),
    )

    # Create Rkvst assistant agent
    toolkit_agent = Agent(
        role="Rkvst Assistant",
        goal="Help users interact with Rkvst through natural language commands",
        backstory=(
            "You are an expert assistant with access to Rkvst tools. "
            "You can perform various Rkvst operations on behalf of the user."
        ),
        mcps=[
            MCPServerHTTP(
                url=url,
                streamable=True,
                cache_tools_list=True,
                headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
            ),
        ],
        llm=llm,
        verbose=True,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Try asking the agent to perform Rkvst operations.\n")

    conversation_context = ""

    while True:
        user_input = input("You: ").strip()

        if user_input.lower() in ["exit", "quit", "bye"]:
            print("\nGoodbye!")
            break

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Based on the conversation history:\n{conversation_context}\n\n"
                f"Current user request: {user_input}\n\n"
                f"Please help the user with their Rkvst related request."
            ),
            expected_output="A helpful response addressing the user's request",
            agent=toolkit_agent,
        )

        crew = Crew(
            agents=[toolkit_agent],
            tasks=[task],
            verbose=False,
        )

        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

if __name__ == "__main__":
    main()

Conclusion

You now have a CrewAI agent connected to Rkvst through Composio's Tool Router. The agent can perform Rkvst operations through natural language commands. Next steps:
  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations

How to build Rkvst MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Rkvst MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Rkvst MCP with Claude Agent SDK

Google ADK

Google ADK

Use Rkvst MCP with Google ADK

LangChain

LangChain

Use Rkvst MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Rkvst MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Rkvst MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Rkvst MCP with LlamaIndex

FAQ

What are the differences in Tool Router MCP and Rkvst MCP?

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

Can I use Tool Router MCP with CrewAI?

Yes, you can. CrewAI 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 Rkvst tools.

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

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

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