Can my AI agent list all workspaces and drill into specific project details?

Absolutely. Use `list_workspaces` to browse all your organizational workspaces, then `list_projects` to see every project within a workspace. Your agent returns full metadata including member counts, settings, and creation dates — all without leaving your conversation.

I need to set up a new project with custom workflows and labels — can I do it all conversationally?

Yes. Tell your agent to create the project, then ask it to configure the workflow columns and create color-coded labels. The agent chains `create_project`, `list_workflows`, and `create_label` tools automatically to set up your board exactly as you describe it.

Does this integration let me modify or delete projects?

This core integration focuses on workspace exploration, project creation, and configuration management — including workflows and labels. For task-level operations like CRUD, subtasks, and checklists, use the dedicated GitScrum Tasks integration. All actions respect your GitScrum account permissions.

GitScrum MCP Server for LangChain 16 tools — connect in under 2 minutes

Name: GitScrum
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 16 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect GitScrum through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "gitscrum": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using GitScrum, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About GitScrum MCP Server

What you can do

Browse workspaces — list all your organizational workspaces and retrieve details for each one
Manage projects — list, create, and inspect projects with full metadata including members and settings
Configure workflows — view and manage Kanban column definitions and workflow templates
Organize with labels — list, create, and update color-coded labels to categorize work
Access your profile — retrieve the authenticated user's profile across all workspaces

LangChain's ecosystem of 500+ components combines seamlessly with GitScrum through native MCP adapters. Connect 16 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

The GitScrum MCP Server exposes 16 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect GitScrum to LangChain via MCP

Follow these steps to integrate the GitScrum MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 16 tools from GitScrum via MCP

Why Use LangChain with the GitScrum MCP Server

LangChain provides unique advantages when paired with GitScrum through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine GitScrum MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across GitScrum queries for multi-turn workflows

GitScrum + LangChain Use Cases

Practical scenarios where LangChain combined with the GitScrum MCP Server delivers measurable value.

RAG with live data: combine GitScrum tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query GitScrum, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain GitScrum tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every GitScrum tool call, measure latency, and optimize your agent's performance

GitScrum MCP Tools for LangChain (16)

These 16 tools become available when you connect GitScrum to LangChain via MCP:

create_project

Create a new project

create_workspace

Create a new workspace

find_project

Find a project by name

get_me

Get authenticated user profile

get_project

Get project details

get_task

Get task details by UUID

get_workspace

Get workspace details

list_labels

List labels in a project

list_project_members

List members in a project

list_projects

List projects in a workspace

list_tasks

Filter by status (todo, in-progress, done). Essential for understanding project scope and workload. List tasks in a project

list_workflows

List workflows (columns) in a project

list_workspaces

List all GitScrum workspaces

my_role

Get my role in the workspace

project_stats

Get project statistics

workspace_stats

Get workspace statistics

Example Prompts for GitScrum in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with GitScrum immediately.

"Show me all the workspaces I have access to on GitScrum."

"Create a new project called 'Mobile App v2' in the acme-eng workspace with a description."

"What labels are available in the web-app project?"

Troubleshooting GitScrum MCP Server with LangChain

Common issues when connecting GitScrum to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

GitScrum + LangChain FAQ

Common questions about integrating GitScrum MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.