teamcenter-mcp-server-test 0.1.1

Authenticated MCP server for Teamcenter Knowledge Base APIs

Teamcenter MCP Server

SQLite-level simplicity for integrating AI assistants with Teamcenter Knowledge Base APIs.

Quick Start (Just Copy & Paste)

Continue.dev

Add to ~/.continue/config.json:

{
  "experimental": {
    "modelContextProtocolServers": [{
      "transport": {
        "type": "stdio",
        "command": "uvx",
        "args": ["teamcenter-mcp-server-test", "--base-url", "http://localhost:8000"]
      }
    }]
  }
}

VS Code

Add to .vscode/mcp.json:

{
  "servers": {
    "teamcenter": {
      "type": "stdio",
      "command": "uvx",
      "args": ["teamcenter-mcp-server-test", "--base-url", "http://localhost:8000"]
    }
  }
}

JetBrains IDEs

Add to ~/.mcp.json:

{
  "mcpServers": {
    "teamcenter": {
      "command": "uvx",
      "args": ["teamcenter-mcp-server-test", "--base-url", "http://localhost:8000"]
    }
  }
}

Usage

Ask your AI assistant:

• @MCP check if the Teamcenter knowledge base is healthy
• @MCP search for PLM workflow integration documentation
• @MCP find CAD model versioning guides

Production Setup

Replace http://localhost:8000 with your real Teamcenter API:

"args": ["teamcenter-mcp-server-test", "--base-url", "https://teamcenter.yourcompany.com"]

Testing (For Demo/Development)

Start mock API server:

git clone https://github.com/your-repo/mock-api
cd mock-api
uv run uvicorn main:app --reload

Server runs on http://localhost:8000 - use this URL in configs above.

---

Development (Advanced)

Click for development setup

Installation

curl -LsSf https://astral.sh/uv/install.sh | sh

Build Package

uv build

Run Tests

uv run pytest tests/ -v

Files Overview

• auth_mcp_stdio.py: Main MCP server
• main.py: Mock API server for development
• pyproject.toml: Package configuration