Ayanza MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Ayanza through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
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Vinkius supports streamable HTTP and SSE.
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({
"ayanza": {
"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 Ayanza, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
asyncio.run(main())
* 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 Ayanza MCP Server
Orchestrate your team's rhythm with Ayanza, the AI-first project management platform designed for modern velocity. By connecting Ayanza to your AI agent, you transform project oversight from a manual chore into a natural conversation. Your agent gains the power to navigate complex task workflows, access team wikis, and manage project milestones without you ever opening a dashboard. It’s not just about tracking tasks; it’s about giving your agent the context it needs to act as a digital coordinator within your workspace.
LangChain's ecosystem of 500+ components combines seamlessly with Ayanza through native MCP adapters. Connect 10 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.
What you can do
- Task Orchestration — List, create, update, and delete tasks in Ayanza using natural language through your AI agent.
- Project Oversight — Get a comprehensive view of all projects or dive into specific project details to monitor progress effortlessly.
- Knowledge Retrieval — Access and list wiki pages to quickly find team documentation and shared knowledge.
- Workspace Management — View workspace users to understand team structure and assign tasks effectively.
- Dynamic Updates — Modify task descriptions and statuses in real-time to keep your team aligned and productive.
The Ayanza MCP Server exposes 10 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 Ayanza to LangChain via MCP
Follow these steps to integrate the Ayanza 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 10 tools from Ayanza via MCP
Why Use LangChain with the Ayanza MCP Server
LangChain provides unique advantages when paired with Ayanza through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Ayanza 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 Ayanza queries for multi-turn workflows
Ayanza + LangChain Use Cases
Practical scenarios where LangChain combined with the Ayanza MCP Server delivers measurable value.
RAG with live data: combine Ayanza tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Ayanza, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Ayanza tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Ayanza tool call, measure latency, and optimize your agent's performance
Ayanza MCP Tools for LangChain (10)
These 10 tools become available when you connect Ayanza to LangChain via MCP:
create_task
Create a new task in Ayanza
delete_task
Delete an Ayanza task
get_me
Get current authenticated user info
get_project
Get details for a specific Ayanza project
get_task
Get details for a specific Ayanza task
list_projects
List projects in Ayanza
list_tasks
List tasks in Ayanza
list_users
List users in the Ayanza workspace
list_wiki_pages
List wiki pages in Ayanza
update_task
Update an existing Ayanza task
Example Prompts for Ayanza in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Ayanza immediately.
"List all my tasks in Ayanza."
"Create a new task called 'Prepare Q4 presentation'."
"Show my wiki pages in Ayanza."
Troubleshooting Ayanza MCP Server with LangChain
Common issues when connecting Ayanza to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersAyanza + LangChain FAQ
Common questions about integrating Ayanza MCP Server with LangChain.
How does LangChain connect to MCP servers?
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?
Can I trace MCP tool calls in LangSmith?
Connect Ayanza with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Ayanza to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.