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Konfig MCP Engine

Konfig MCP Engine

โšก Konfig MCP Engine

License: MIT MCP Compatible Tests Zero Dependencies Node Version

Enterprise OpenAPI v3.0 / v3.1 to Live Model Context Protocol (MCP) Generator & Tool Bridge.
Transform existing enterprise Swagger/OpenAPI specifications into typed, agent-ready MCP tools on the fly โ€” zero code, zero boilerplate, zero hallucinated parameters.


๐Ÿ’ก The Problem

Enterprise architectures run on thousands of REST endpoints documented via OpenAPI / Swagger. However, bringing these APIs to autonomous AI agents (Claude Code, Cursor, Antigravity, AutoGen, CrewAI) currently requires:

  1. Manual Glue Code: Handcrafting boilerplate MCP servers for each microservice.

  2. Schema Inconsistencies: Parameter types, headers, and request bodies often get mistranslated, causing LLM tool call failures.

  3. Maintenance Hell: Every upstream API update breaks hardcoded tool implementations.

Konfig MCP Engine bridges this gap: Derived from years of production-grade AST engineering at Konfig (Ex-C3-AI), it dynamically ingests OpenAPI v3.0 and v3.1 specs and transforms them in-memory into fully validated, typed Model Context Protocol tool schemas with zero external dependencies.


Related MCP server: API-to-MCP Converter

โšก Key Capabilities

  • ๐Ÿš€ Instant OpenAPI to MCP Transformation: Ingests raw OpenAPI JSON objects or files and outputs JSON-RPC 2.0 MCP tools/list schemas instantly.

  • ๐ŸŽฏ Strict Schema Mapping: Maps path parameters, query parameters, headers, and application/json request bodies directly to compliant JSON Schema v7 definitions.

  • ๐Ÿชถ Zero External Dependencies: Built with pure ECMAScript standard libraries (node:readline, node:fs). Zero bloat, instant startup, hermetic execution.

  • ๐Ÿ›ก๏ธ Anti-Carbonara Architecture: Clean separation of concerns:

    • src/core/: Pure deterministic transformation logic (100% in-memory, no I/O side effects).

    • src/cli/: Lightweight command-line interface for pipelines and automation.

    • src/mcp/: Native Stdio JSON-RPC 2.0 server for Claude Desktop, Cursor, and Antigravity.

  • ๐Ÿค– Autonomous Multi-Agent Friendly: Agents can dynamically discover API capabilities at runtime by passing any OpenAPI spec into konfig_transform_openapi.


๐Ÿค– Model Context Protocol (MCP) Setup

Add to Claude Desktop / Cursor / Antigravity

Add the engine to your claude_desktop_config.json or Antigravity MCP settings:

{
  "mcpServers": {
    "konfig-mcp-engine": {
      "command": "node",
      "args": ["/path/to/konfig_mcp_engine/src/mcp/server.js"]
    }
  }
}

Or run via npx (when installed from npm):

{
  "mcpServers": {
    "konfig-mcp-engine": {
      "command": "npx",
      "args": ["-y", "konfig-mcp-engine"]
    }
  }
}

Available MCP Tools

Tool Name

Description

Parameters

konfig_transform_openapi

Transforms an OpenAPI 3.0/3.1 specification JSON object into ready-to-call MCP Tool schemas for AI agents.

spec (object, required): Parsed OpenAPI v3 spec

Example Tool Invocation

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "konfig_transform_openapi",
    "arguments": {
      "spec": {
        "openapi": "3.0.0",
        "info": { "title": "Petstore API", "version": "1.0.0" },
        "paths": {
          "/pets": {
            "get": {
              "operationId": "listPets",
              "summary": "List all pets",
              "parameters": [
                { "name": "limit", "in": "query", "schema": { "type": "integer" } }
              ]
            }
          }
        }
      }
    }
  }
}

๐Ÿ’ป CLI Usage

You can also use Konfig MCP Engine directly from the command line:

# Generate MCP Tools JSON from an OpenAPI specification
node src/cli/index.js generate path/to/openapi.json

Or when installed globally:

konfig-mcp generate ./swagger.json > mcp-tools.json

๐Ÿงช Testing & Verification

Run the hermetic test suite:

npm test

Expected output:

โ–ถ Konfig MCP Engine
  โœ” transforms OpenAPI endpoints into MCP tools
  โœ” handles empty or invalid specs gracefully
  โœ” handles MCP handshake, notifications, and ping
โœ” Konfig MCP Engine (5ms)

๐Ÿ›๏ธ Architecture

konfig_mcp_engine/
โ”œโ”€โ”€ src/
โ”‚   โ”œโ”€โ”€ core/
โ”‚   โ”‚   โ”œโ”€โ”€ transformer.js    # Pure OpenAPI -> MCP Tool AST Transformer
โ”‚   โ”‚   โ””โ”€โ”€ index.js          # Core module export
โ”‚   โ”œโ”€โ”€ cli/
โ”‚   โ”‚   โ””โ”€โ”€ index.js          # CLI entry point (konfig-mcp)
โ”‚   โ””โ”€โ”€ mcp/
โ”‚       โ””โ”€โ”€ server.js         # Stdio JSON-RPC 2.0 MCP Server
โ”œโ”€โ”€ tests/
โ”‚   โ””โ”€โ”€ transformer.test.js   # Unit & Integration tests
โ”œโ”€โ”€ package.json
โ”œโ”€โ”€ server.json               # MCP Registry Schema
โ”œโ”€โ”€ smithery.yaml             # Smithery deployment config
โ””โ”€โ”€ Dockerfile

๐Ÿ“œ Origin & Heritage

This project is part of the Diamantenschmiede (Pioneer #7) open-source initiative, refining and advancing abandoned or sunset software into hardened, zero-dependency tools for the modern agentic era.

Based on foundational AST research from konfig-dev/konfig (MIT, Copyright (c) 2021-2024 Konfig Inc.).


๐Ÿ“„ License

MIT ยฉ 2026 tastenkasperle (Diamantenschmiede) & Konfig Inc.

Available Tools

1 tool
konfig_transform_openapiB

Transforms an OpenAPI 3.0/3.1 specification JSON object into ready-to-call MCP Tool schemas for AI agents.

Inputs: spec (required).

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelogโ€ฆ

    TDQS

    B3.4/5.0

    Scored across 1 tool

    Disambiguation5/5

    There is only one tool, so there is no possibility of confusion or misselection. Its purpose is stated precisely: transform an OpenAPI spec into MCP tool schemas.

    Naming Consistency4/5

    The single tool uses a clear snake_case verb_noun pattern with a namespace prefix (konfig_transform_openapi). Consistency cannot really be violated with one tool, but the naming is readable and predictable.

    Tool Count3/5

    A single tool is thin for something branded as an 'Engine'; it covers only the transform step of what could be a larger workflow. Still, the narrow stated purpose makes one tool defensible, so it sits at borderline rather than clearly wrong.

    Completeness3/5

    The surface covers transformation but offers no validation, listing, batch processing, or reverse conversion, leaving agents to handle errors and preprocessing themselves. It is usable for its core task but has notable gaps around it.

    Maintenance

    ActivityMaintained
    ResponsivenessNo recent community issues

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