| name | akaunting-mcp-connector |
| description | MCP connector for Akaunting accounting platform – enables AI-powered financial management, reporting, and invoice automation through Claude |
| license | GPL |
| tags | ["business","accounting","mcp","akaunting","finance"] |
| difficulty | intermediate |
| time_to_master | 4-8 weeks |
| version | 1.0.0 |
Akaunting MCP Connector
Overview
This skill enables Claude to interact with Akaunting through the Model Context Protocol (MCP). It provides a bridge between Claude's AI capabilities and Akaunting's REST API, allowing natural language control of Akaunting operations, intelligent automation, and AI-powered assistance for Akaunting workflows.
When to Use This Skill
- Invoice and bill management via natural language
- Financial report generation and analysis
- Category and account management
- Tax calculation and compliance
- Cash flow forecasting and budgeting
Architecture
┌─────────────┐ ┌─────────────────┐ ┌──────────────────┐
│ Claude │────▶│ MCP Server │────▶│ Akaunting │
│ (Client) │◀────│ (TypeScript) │◀────│ (REST API )│
└─────────────┘ └─────────────────┘ └──────────────────┘
Core Concepts
MCP Server Setup
The connector implements an MCP server that exposes Akaunting operations as tools Claude can invoke. The server translates natural language intentions into REST API calls.
Key Endpoints/Interfaces
/api/invoices, /api/bills, /api/accounts, /api/categories, /api/reports
Implementation
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import { z } from "zod";
const server = new McpServer({
name: "akaunting-mcp-connector",
version: "1.0.0",
});
server.tool(
"list_resources",
"List and query Akaunting resources with optional filters",
{
query: z.string().optional().describe("Search query or filter"),
limit: z.number().optional().describe("Max results to return"),
},
async ({ query, limit }) => {
const response = await fetch(`${BASE_URL}/api/invoices`, {
headers: { "Authorization": `Bearer ${API_KEY}` },
});
const data = await response.json();
return {
: [{ : , : .(data, , ) }],
};
}
);
server.(
,
,
{
: z.().(),
: z.({}).().().(),
},
({ name, config }) => {
response = (, {
: ,
: {
: ,
: ,
},
: .({ name, ...config }),
});
data = response.();
{
: [{ : , : }],
};
}
);
server.(
,
,
{
: z.().(),
: z.().().(),
},
({ , timeframe }) => {
response = (, {
: { : },
});
data = response.();
{
: [{ : , : .(data, , ) }],
};
}
);
transport = ();
server.(transport);
Claude Desktop Configuration
{
"mcpServers": {
"akaunting-mcp-connector": {
"command": "node",
"args": ["path/to/akaunting-mcp-connector/index.js"],
"env": {
"AKAUNTING_API_KEY": "your-api-key",
"AKAUNTING_BASE_URL": "https://your-instance-url"
}
}
}
}
Best Practices
- Authentication: Store API keys securely using environment variables; never hardcode credentials
- Rate Limiting: Implement request throttling to respect Akaunting API rate limits
- Error Handling: Provide clear, actionable error messages for common failure scenarios
- Pagination: Handle paginated responses for large datasets efficiently
- Caching: Cache frequently accessed read-only data to reduce API calls
- Security: Validate all inputs before passing to the Akaunting API; sanitize outputs
- Logging: Log all API interactions for debugging and audit purposes
Example Prompts
"Generate a cash flow forecast for the next 3 months based on recurring invoices and bills"
Security Considerations
- All API credentials must be stored as environment variables
- Implement input validation and sanitization for all tool parameters
- Use HTTPS for all API communications
- Follow the principle of least privilege for API token permissions
- Audit log all write operations for compliance tracking
Resources
Changelog
| Version | Date | Changes |
|---|
| 1.0.0 | 2026-04-01 | Initial MCP connector skill |
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