How to integrate Gitlab MCP with LangChain

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Introduction

This guide walks you through connecting Gitlab to LangChain using the Composio tool router. By the end, you'll have a working Gitlab agent that can create new gitlab group for qa team, open bug issue in frontend project, create branch from latest main commit, archive completed api migration project through natural language commands.

This guide will help you understand how to give your LangChain agent real control over a Gitlab account through Composio's Gitlab 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 and set up your OpenAI and Composio API keys
  • Connect your Gitlab project to Composio
  • Create a Tool Router MCP session for Gitlab
  • Initialize an MCP client and retrieve Gitlab tools
  • Build a LangChain agent that can interact with Gitlab
  • 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 Gitlab MCP server, and what's possible with it?

The Gitlab MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Gitlab account. It provides structured and secure access to your repositories, projects, and issues, so your agent can perform actions like creating projects, managing issues, handling branches, and automating DevOps workflows on your behalf.

  • Project and group automation: Instantly create new Gitlab projects or organize your workspaces by setting up project groups—all without manual clicks.
  • Issue creation and tracking: Have your agent report bugs, request features, or open new issues in specific projects to keep your team on top of tasks.
  • Branch management: Let your agent create repository branches from any commit or base branch, making it easy to streamline your development process.
  • Project lifecycle management: Archive completed projects or delete unneeded ones, keeping your workspace clean and up to date with minimal effort.
  • Commit and job insights: Retrieve commit references, determine commit sequence in project history, or erase job artifacts and logs for deeper CI/CD control.

Supported Tools & Triggers

Tools
Archive ProjectTool to archive a project.
Create GitLab GroupTool to create a new group in gitlab.
Create ProjectTool to create a new project in gitlab.
Create Project IssueTool to create a new issue in a gitlab project.
Create Repository BranchTool to create a new branch in a project.
Delete ProjectTool to delete a gitlab project by its id.
Download Project AvatarTool to download a project’s avatar image.
Erase JobTool to erase the content of a specified job within a project.
Get Commit ReferencesTool to get all references (branches or tags) a commit is pushed to.
Get Commit SequenceTool to get the sequence number of a commit in a project by following parent links from the given commit.
Get Group DetailsTool to retrieve information about a specific group by its id.
Get Group MemberTool to retrieve details for a specific group member.
Get GroupsGet groups
Get Job DetailsTool to retrieve details of a single job by its id within a specified project.
Get Merge Request NotesTool to fetch comments on a merge request.
Get ProjectTool to get a single project by id or url-encoded path.
Get Project LanguagesTool to list programming languages used in a project with percentages.
Get Project MemberTool to retrieve details for a specific project member.
Get Project Member AllTool to retrieve details for a specific project member (including inherited and invited members).
Get Merge Request CommitsTool to get commits of a merge request.
Get Project Merge RequestsTool to retrieve a list of merge requests for a specific project.
Get ProjectsTool to list all projects accessible to the authenticated user.
List Merge Request DiffsTool to list all diff versions of a merge request.
Get Repository BranchTool to retrieve information about a specific branch in a project.
Get Repository BranchesRetrieves a list of repository branches for a project.
Get Single CommitTool to get a specific commit identified by the commit hash or name of a branch or tag.
Get Single PipelineTool to retrieve details of a single pipeline by its id within a specified project.
Get UserTool to retrieve information about a specific user by their id.
Get User PreferencesTool to get the current user's preferences.
Get UsersTool to retrieve a list of users from gitlab.
Get User StatusTool to get a user's status by id.
Get User StatusTool to get the current user's status.
Get User Support PINTool to get details of the current user's support pin.
Import project membersTool to import members from one project to another.
List All Group MembersTool to list all members of a group including direct, inherited, and invited members.
List All Project MembersTool to list all members of a project (direct, inherited, invited).
List Billable Group MembersTool to list billable members of a top-level group (including its subgroups and projects).
List Group MembersTool to list direct members of a group.
List Pending Group MembersTool to list pending members of a group and its subgroups and projects.
List Pipeline JobsTool to retrieve a list of jobs for a specified pipeline within a project.
List Project GroupsTool to list ancestor groups of a project.
List Project Invited GroupsTool to list groups invited to a project.
List Project PipelinesTool to retrieve a list of pipelines for a specified project.
List Project Shareable GroupsTool to list groups that can be shared with a project.
List Project Repository TagsTool to retrieve a list of repository tags for a specified project.
List Project Transfer LocationsTool to list namespaces available for project transfer.
List project usersTool to list users of a project.
List Repository CommitsTool to get a list of repository commits in a project.
List User ProjectsTool to list projects owned by a specific user.
Create Support PINTool to create a support pin for your authenticated user.
Update User PreferencesTool to update the current user's preferences.
Set User StatusTool to set the current user's status.
Share Project With GroupTool to share a project with a group.
Start Housekeeping TaskTool to start the housekeeping task for a project.

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 this tutorial, make sure you have:
  • Python 3.10 or higher installed on your system
  • A Composio account with an API key
  • An OpenAI API key
  • Basic familiarity with Python and async programming

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

pip install composio-langchain langchain-mcp-adapters langchain python-dotenv

Install the required packages for LangChain with MCP support.

What's happening:

  • composio-langchain provides Composio integration for LangChain
  • langchain-mcp-adapters enables MCP client connections
  • langchain is the core agent framework
  • python-dotenv loads environment variables

Set up environment variables

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

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

Import dependencies

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()
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with Gitlab functionality through MCP

Initialize Composio client

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")
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 Gitlab tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

# Create Tool Router session for Gitlab
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['gitlab']
)

url = session.mcp.url
What's happening:
  • We're creating a Tool Router session that gives your agent access to Gitlab 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 Gitlab tools as needed

Configure the agent with the MCP URL

client = MultiServerMCPClient({
    "gitlab-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)
What's happening:
  • We're creating a MultiServerMCPClient that connects to our Gitlab MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • get_tools() retrieves all available Gitlab tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model

Set up interactive chat interface

conversation_history = []

print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Gitlab 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")
What's happening:
  • We initialize an empty conversation_history list to maintain context across interactions
  • A while loop continuously accepts user input from the command line
  • When a user types a message, it's added to the conversation history and sent to the agent
  • The agent processes the request using the ainvoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully

Run the application

if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • We call the main() function using asyncio.run() to start the application

Complete Code

Here's the complete code to get you started with Gitlab and LangChain:

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=['gitlab']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "gitlab-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 Gitlab 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())

Conclusion

You've successfully built a LangChain agent that can interact with Gitlab 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 Gitlab MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Gitlab MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Gitlab MCP with Claude Agent SDK

Google ADK

Google ADK

Use Gitlab MCP with Google ADK

Vercel AI SDK

Vercel AI SDK

Use Gitlab MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Gitlab MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Gitlab MCP with LlamaIndex

CrewAI

CrewAI

Use Gitlab MCP with CrewAI

FAQ

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

With a standalone Gitlab MCP server, the agents and LLMs can only access a fixed set of Gitlab tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Gitlab 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 Gitlab tools.

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

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

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