mayankcubastion1/mcp-server

XMCP

XMCP is a [Model Context Protocol (MCP)] server exposing selected HRMS portal APIs over HTTP so they can be safely consumed by LLM and chatbot applications.

Features

• Health check endpoint at /health.
• Holiday data proxy at /holidays?year=YYYY forwarding to the HRMS app/employees/holidays API.
• Leave records proxy at /leaves?fyId=<financial_year_id> forwarding to the HRMS attendance/leaves/my-leaves API.
• Apply leave proxy at /leaves/apply forwarding POST requests to the HRMS attendance/leaves/apply API.
• Attendance proxy at /attendance/my-attendance.
• Feedback endpoints for adding feedback, viewing RM feedbacks and listing levels.
• Ticket management endpoints for viewing, drafting and submitting tickets.
• Team management ledger endpoint at /team-management/ledger.
• All HRMS calls transparently forward the incoming Authorization: Bearer <token> header.
• Built with FastAPI and packaged using Docker.

Configuration

Create a .env file (see .env.example) or set environment variables:

• HRMS_API_BASE_URL – base URL of the HRMS portal APIs (e.g. https://devxnet2api.cubastion.net/api/v2).

Every request to the MCP server must include a valid Authorization header containing the user's bearer token, which is forwarded unchanged to the HRMS APIs.

Development

Install dependencies:

pip install -e .[dev]

Run the application locally:

uvicorn xmcp.main:app --reload

Example requests (replace $TOKEN with the user's bearer token):

curl 'http://localhost:8000/holidays?year=2025' -H "Authorization: Bearer $TOKEN"
curl 'http://localhost:8000/leaves?fyId=roxq0g78pis7ia9' -H "Authorization: Bearer $TOKEN"
curl -X POST 'http://localhost:8000/leaves/apply' \
  -H 'Content-Type: application/json' \
  -H "Authorization: Bearer $TOKEN" \
  -d '{"type":"Debit","category":"Leave","leaveCount":2,"leaveDate":"2025-08-24","comments":"Not feeling well","status":"Pending Approval"}'

Testing

The repository includes unit tests under tests/:

• test_health.py
• test_holidays.py
• test_leaves.py
• test_apply_leave.py

Run all tests with:

pytest

Docker

Build the container image:

docker build -t xmcp .

Run the server in Docker:

docker run -p 8000:8000 xmcp

The service will be available at http://localhost:8000.

Packaging and Distribution

The project includes a pyproject.toml that declares the MCP server as a standard Python package using the Hatchling build backend. All runtime dependencies and optional development tools are listed there, which allows the application to be installed or built in a consistent way.

Benefits

• Unified metadata and dependency management make the project installable via pip and buildable into wheel or source distributions.
• Optional dev dependencies keep development tooling separate from runtime requirements.

Build and publish

You can now build distributable artifacts and publish them to an index such as PyPI:

python -m build   # or: hatch build

Install the package in other environments:

pip install .               # from the project root
# or, after publishing
pip install xmcp

These packages can be used in CI/CD pipelines, Docker images, or any other environment where the MCP server needs to be reused or integrated.

Code Structure and Adding new APIs

Endpoints and tools are organized by domain under xmcp/:

• leaves/
• feedback/
• tickets/
• attendance/
• miscellaneous/
• team_management/

To add a new API within a group:

1. Define Pydantic models in the group's models.py describing the request and response bodies.
2. Add a client method in the group's client.py that calls the HRMS endpoint, accepts an auth_header argument, and returns the typed models.
3. Create a route in the group's router.py that accepts the necessary parameters, requires the Authorization header, and calls the client method.
4. Document the endpoint in this README and add a corresponding test under tests/ that patches the new client method.
5. Run pytest before committing to verify everything works.

Following this pattern allows the MCP server to expand as additional HRMS APIs are exposed.

Using from LangChain

The module xmcp.tools exposes helpers to register the MCP endpoints as tools. Framework-agnostic specifications can be adapted to LangChain, LangGraph or any other agentic runtime. StructuredTool from LangChain is being deprecated, but we still provide helpers for backward compatibility.

# Framework-agnostic definitions
from xmcp.tools import create_tool_specs

specs = create_tool_specs(
    base_url="http://localhost:8000",
    auth_header_getter=lambda: "Bearer <token>",
)

# Convert to LangChain StructuredTool instances (deprecated but supported)
from xmcp.tools import create_langchain_tools

tools = create_langchain_tools(
    base_url="http://localhost:8000",
    auth_header_getter=lambda: "Bearer <token>",
)

# tools now contains StructuredTool instances for all available endpoints
# (e.g. get_holidays, get_leaves, apply_leave, get_attendance, add_feedback, get_tickets, ...)

Each specification returns the JSON response from the corresponding MCP endpoint and can be supplied to any agent framework that supports structured tool calling.