INFATON MCP Server is a 1C:Enterprise platform server offering 51 specialized tools for AI assistants to interact with 1C databases. It facilitates comprehensive data operations, administrative tasks, and business logic execution via the JSON-RPC 2.0 protocol.

MCP35: INFATON MCP Server is a 1C:Enterprise platform server offering 51… (★ 29, MIT)

Features

01Provides 51 specialized tools for interacting with 1C:Enterprise databases.

02Utilizes JSON-RPC 2.0 protocol for communication with AI assistants.

03Supports a wide range of 1C:Enterprise configurations (ERP, UPP, Accounting, etc.).

04Includes a Node.js stdio wrapper for easy integration with popular AI clients like Claude Desktop and Cursor.

05Implements critical security features including HTTPS enforcement, dedicated user requirements, and fine-grained tool access control.

Why choose it

+Provides 51 specialized tools for interacting with 1C:Enterprise databases.

+Enabling AI assistants to read and write data in 1C:Enterprise databases.

+Covers 3 supported environments or platforms, which is helpful for broader deployment needs.

+Ships with a public repository and a MIT license, which makes adoption and review easier.

Trade-offs

!There are at least 8 related tools in the same category, so the best choice is easier to make after side-by-side comparison.

Compatibility

1C:Enterprise Platform

Runtime

Verified via docs

1C:Enterprise Configurations

Supported Applications

Verified via docs

Node.js

Client Wrapper

Verified via docs

Quick start

$ npx infaton-mcp

Use cases

↳Enabling AI assistants to read and write data in 1C:Enterprise databases.

↳Automating routine business operations and workflows within the 1C system.

↳Generating complex reports and analytics directly from 1C data.

↳Performing administrative tasks and auditing event logs in 1C:Enterprise.

↳Integrating 1C:Enterprise with external AI-driven systems for advanced business intelligence.

How it compares

≈MCP35 sits in the API Integration category, so it makes more sense to evaluate it alongside tools like awesome-mcp-servers instead of in isolation.

≈If your main need is closer to "Enabling AI assistants to read and write data in 1C:Enterprise databases.", that use case is a better lens for comparison than broad feature checklists alone.

≈MCP35 uses a MIT license, and community traction are both easier to judge in category context.