| name | firefly-iii-mcp-connector |
| description | MCP connector for Firefly III personal finance – enables AI-powered transaction management, budgeting, and financial reporting through Claude |
| license | AGPL |
| tags | ["business","finance","mcp","firefly","budgeting"] |
| difficulty | beginner |
| time_to_master | 4-8 weeks |
| version | 1.0.0 |
Firefly Iii MCP Connector
Overview
This skill enables Claude to interact with Firefly Iii through the Model Context Protocol (MCP). It provides a bridge between Claude's AI capabilities and Firefly Iii's REST API, allowing natural language control of Firefly Iii operations, intelligent automation, and AI-powered assistance for Firefly Iii workflows.
When to Use This Skill
- Transaction categorization and tagging via AI
- Budget creation and monitoring
- Bill tracking and payment scheduling
- Financial goal tracking and projections
- Import/export and reconciliation
Architecture
┌─────────────┐ ┌─────────────────┐ ┌──────────────────┐
│ Claude │────▶│ MCP Server │────▶│ Firefly Iii │
│ (Client) │◀────│ (TypeScript) │◀────│ (REST API )│
└─────────────┘ └─────────────────┘ └──────────────────┘
Core Concepts
MCP Server Setup
The connector implements an MCP server that exposes Firefly Iii operations as tools Claude can invoke. The server translates natural language intentions into REST API calls.
Key Endpoints/Interfaces
/api/v1/transactions, /api/v1/budgets, /api/v1/accounts, /api/v1/bills, /api/v1/categories
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: "firefly-iii-mcp-connector",
version: "1.0.0",
});
server.tool(
"list_resources",
"List and query Firefly Iii 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/v1/transactions`, {
headers: { "Authorization": `Bearer ${API_KEY}` },
});
const data = await response.json();
{
: [{ : , : .(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": {
"firefly-iii-mcp-connector": {
"command": "node",
"args": ["path/to/firefly-iii-mcp-connector/index.js"],
"env": {
"FIREFLY_III_API_KEY": "your-api-key",
"FIREFLY_III_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 Firefly Iii 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 Firefly Iii API; sanitize outputs
- Logging: Log all API interactions for debugging and audit purposes
Example Prompts
"Categorize all uncategorized transactions from last month and update the monthly budget report"
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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