| name | dolibarr-mcp-connector |
| description | MCP connector for Dolibarr ERP/CRM – enables AI-powered business management, invoicing, and third-party relationship management through Claude |
| license | GPL |
| tags | ["business","erp","mcp","dolibarr","crm"] |
| difficulty | intermediate |
| time_to_master | 4-8 weeks |
| version | 1.0.0 |
Dolibarr MCP Connector
Overview
This skill enables Claude to interact with Dolibarr through the Model Context Protocol (MCP). It provides a bridge between Claude's AI capabilities and Dolibarr's REST API, allowing natural language control of Dolibarr operations, intelligent automation, and AI-powered assistance for Dolibarr workflows.
When to Use This Skill
- Third-party and contact management via AI
- Invoice and proposal creation automation
- Product and service catalog management
- Project and task tracking
- Bank reconciliation assistance
Architecture
┌─────────────┐ ┌─────────────────┐ ┌──────────────────┐
│ Claude │────▶│ MCP Server │────▶│ Dolibarr │
│ (Client) │◀────│ (TypeScript) │◀────│ (REST API )│
└─────────────┘ └─────────────────┘ └──────────────────┘
Core Concepts
MCP Server Setup
The connector implements an MCP server that exposes Dolibarr operations as tools Claude can invoke. The server translates natural language intentions into REST API calls.
Key Endpoints/Interfaces
/api/index.php/thirdparties, /api/index.php/invoices, /api/index.php/products, /api/index.php/projects
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: "dolibarr-mcp-connector",
version: "1.0.0",
});
server.tool(
"list_resources",
"List and query Dolibarr 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/index.php/thirdparties`, {
headers: { "Authorization": `Bearer ${API_KEY}` },
});
const data = await response.json();
return {
content: [{ type: "text", text: JSON.stringify(data, null, 2) }],
};
}
);
server.tool(
"create_resource",
"Create a new resource in Dolibarr",
{
name: z.string().describe("Resource name"),
config: z.object({}).passthrough().optional().describe("Resource configuration"),
},
async ({ name, config }) => {
const response = await fetch(`${BASE_URL}/api/index.php/thirdparties`, {
method: "POST",
headers: {
"Authorization": `Bearer ${API_KEY}`,
"Content-Type": "application/json",
},
body: JSON.stringify({ name, ...config }),
});
const data = await response.json();
return {
content: [{ type: "text", text: `Created: ${JSON.stringify(data)}` }],
};
}
);
server.tool(
"analyze",
"AI-powered analysis of Dolibarr data",
{
type: z.string().describe("Analysis type"),
timeframe: z.string().optional().describe("Time range for analysis"),
},
async ({ type, timeframe }) => {
const response = await fetch(`${BASE_URL}/api/index.php/thirdparties`, {
headers: { "Authorization": `Bearer ${API_KEY}` },
});
const data = await response.json();
return {
content: [{ type: "text", text: JSON.stringify(data, null, 2) }],
};
}
);
const transport = new StdioServerTransport();
await server.connect(transport);
Claude Desktop Configuration
{
"mcpServers": {
"dolibarr-mcp-connector": {
"command": "node",
"args": ["path/to/dolibarr-mcp-connector/index.js"],
"env": {
"DOLIBARR_API_KEY": "your-api-key",
"DOLIBARR_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 Dolibarr 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 Dolibarr API; sanitize outputs
- Logging: Log all API interactions for debugging and audit purposes
Example Prompts
"Create invoices for all pending orders from last month and send payment reminders"
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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