Affinda MCP Server for LangChain 5 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Affinda through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
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({
"affinda": {
"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 Affinda, 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 Affinda MCP Server
Connect your Affinda account to your AI agent to unlock powerful intelligent document processing (IDP). From automatically extracting details from resumes and invoices to auditing document statuses across your workspaces, your agent handles structured data extraction through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with Affinda through native MCP adapters. Connect 5 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
- Automated Document Parsing — Upload PDFs or images of resumes, invoices, and passports for high-accuracy JSON extraction
- Workspace Oversight — List and audit documents within your specific workspaces to maintain organizational control
- Extraction Model Management — List available document types (Resume, Invoice, Receipt, etc.) supported by your account
- Real-time Status Tracking — Retrieve the parsing status and technical metadata for any uploaded document
- Metadata Insights — Quickly identify processing errors or missing data across your document library directly from chat
The Affinda MCP Server exposes 5 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 Affinda to LangChain via MCP
Follow these steps to integrate the Affinda 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 5 tools from Affinda via MCP
Why Use LangChain with the Affinda MCP Server
LangChain provides unique advantages when paired with Affinda through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Affinda 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 Affinda queries for multi-turn workflows
Affinda + LangChain Use Cases
Practical scenarios where LangChain combined with the Affinda MCP Server delivers measurable value.
RAG with live data: combine Affinda tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Affinda, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Affinda tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Affinda tool call, measure latency, and optimize your agent's performance
Affinda MCP Tools for LangChain (5)
These 5 tools become available when you connect Affinda to LangChain via MCP:
create_document
Defaults to synchronous waiting for the output. Upload and parse a PDF or image into Affinda via its public URL for high-accuracy JSON extraction
get_document
Retrieve the fully structured JSON data and status for a specific processed document in Affinda
list_document_types
Retrieve exactly which parsing models the Affinda account supports (e.g. Resume, Invoice, Passport)
list_documents
Retrieve all parsed documents in an Affinda workspace with their processing status
list_workspaces
Retrieve all container workspaces for documents created within your Affinda account
Example Prompts for Affinda in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Affinda immediately.
"List all documents in my 'HR Recruitment' workspace."
"Parse this resume URL: https://example.com/cv.pdf using the 'resume' model."
"List the available document types in my account."
Troubleshooting Affinda MCP Server with LangChain
Common issues when connecting Affinda to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersAffinda + LangChain FAQ
Common questions about integrating Affinda 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 Affinda 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 Affinda to LangChain
Get your token, paste the configuration, and start using 5 tools in under 2 minutes. No API key management needed.