Concord CLM MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Concord CLM 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({
"concord-clm": {
"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 Concord CLM, 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 Concord CLM MCP Server
Connect your AI assistant to Concord, the Contract Lifecycle Management (CLM) platform that centralizes how your team drafts, negotiates, signs, and stores contracts.
LangChain's ecosystem of 500+ components combines seamlessly with Concord CLM 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
- Agreement Lookup — Search and retrieve any contract by name, ID or status directly through your AI chat.
- Signature Workflows — Send agreements out for e-signature to internal or external parties without leaving your conversation.
- Template-Based Creation — Create new agreements from pre-approved templates, automatically populating fields and routing them for review.
The Concord CLM 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 Concord CLM to LangChain via MCP
Follow these steps to integrate the Concord CLM 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 Concord CLM via MCP
Why Use LangChain with the Concord CLM MCP Server
LangChain provides unique advantages when paired with Concord CLM through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Concord CLM 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 Concord CLM queries for multi-turn workflows
Concord CLM + LangChain Use Cases
Practical scenarios where LangChain combined with the Concord CLM MCP Server delivers measurable value.
RAG with live data: combine Concord CLM tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Concord CLM, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Concord CLM tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Concord CLM tool call, measure latency, and optimize your agent's performance
Concord CLM MCP Tools for LangChain (10)
These 10 tools become available when you connect Concord CLM to LangChain via MCP:
create_agreement
Create a new agreement in Concord
get_agreement
Retrieve detailed information about a specific agreement
get_current_user
Retrieve details of the currently authenticated user
list_agreements
Retrieve a list of agreements from Concord CLM
list_signed_agreements
Quickly list all fully signed agreements
list_templates
Retrieve a list of document templates available in Concord
list_users
Retrieve a list of all users in your Concord organization
list_webhooks
Retrieve a list of configured webhooks
search_agreements_by_name
Find agreements by their name
send_for_signature
Trigger the signature process for a specific agreement
Example Prompts for Concord CLM in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Concord CLM immediately.
"Show me all signed contracts in Concord."
"Send agreement 'agr-4521' for signature."
"Check the status of agreement ID 'agr-8901'."
Troubleshooting Concord CLM MCP Server with LangChain
Common issues when connecting Concord CLM to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersConcord CLM + LangChain FAQ
Common questions about integrating Concord CLM 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 Concord CLM 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 Concord CLM to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.