Bring Accounts Receivable
to LangChain
Learn how to connect Invoiced to LangChain and start using 10 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
What is the Invoiced MCP Server?
Connect your Invoiced account to any AI agent and take full control of your accounts receivable orchestration and automated billing workflows through natural conversation.
What you can do
- Invoice Portfolio Orchestration — List and manage all issued invoices programmatically, retrieving detailed payment metadata and aging statuses
- Customer & Payment Intelligence — Programmatically retrieve directories of customers and access complete credit profiles and payment history in real-time
- A/R Workflow Architecture — Access your complete directory of payment plans and auto-pay settings to coordinate your organizational revenue
- Operational Monitoring — Access real-time status updates for paid invoices and track collection metrics directly through your agent for instant reporting
- Infrastructure Verification — Verify account-level API connectivity and monitor transaction volume directly through your agent for perfectly coordinated service scaling
How it works
1. Subscribe to this server
2. Retrieve your API Key from your Invoiced dashboard (Settings > API)
3. Start orchestrating your revenue growth from Claude, Cursor, or any MCP client
No more manual following up on overdue payments or missing billing updates. Your AI acts as your dedicated finance coordinator and accounts receivable architect.
Who is this for?
- Finance Managers — instantly retrieve invoice summaries and monitor collection goals using natural language commands
- Accounts Receivable Leads — verify individual customer metadata and track payment history without leaving your creative workspace
- Developers — integrate high-speed Invoiced billing data into custom ERP and accounting pipelines through simple AI queries
Built-in capabilities (10)
Verify Invoiced API connectivity
Create a customer
Pass line items as JSON array with name, quantity, and unit_cost. Create an invoice
Get customer details
Get invoice details
List all credit notes
List all customers
List all estimates
List all invoices
List all payments
Why LangChain?
LangChain's ecosystem of 500+ components combines seamlessly with Invoiced 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.
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The largest ecosystem of integrations, chains, and agents. combine Invoiced MCP tools with 500+ LangChain components
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Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
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LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
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Memory and conversation persistence let agents maintain context across Invoiced queries for multi-turn workflows
Invoiced in LangChain
Invoiced and 3,400+ other MCP servers. One platform. One governance layer.
Teams that connect Invoiced to LangChain through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 3,400+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Invoiced in LangChain
The Invoiced 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. All 10 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in LangChain only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* 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
How Vinkius secures
Invoiced for LangChain
Every tool call from LangChain to the Invoiced MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I create invoices directly from my AI agent?
Yes. Use the create_invoice tool with a customer ID and line items. The invoice is created instantly in your Invoiced account.
How do I track outstanding payments?
Use list_payments to see all payment transactions or list_invoices to review invoices with their payment status and outstanding balances.
Can I manage customers and credit notes?
Absolutely. Use create_customer to add new accounts, list_customers to browse, and list_credit_notes to review all issued credits.
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.
Can I trace MCP tool calls in LangSmith?
Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.
MultiServerMCPClient not found
Install: pip install langchain-mcp-adapters