Skip to main content
Glama

MCP Server Project

A secure Model Context Protocol (MCP) server providing HTTP endpoints for AI agent tool execution. Built with Python 3.12+, Starlette, and FastMCP.

Quick Start

# Clone and setup
git clone https://github.com/sdirishguy/mcp_server_project.git
cd mcp_server_project
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt

# Run server
uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload

# Test
curl http://localhost:8000/health

Docker

docker-compose up -d
curl http://localhost:8000/health

Configuration

Required environment variables:

JWT_SECRET="your-secret-key-32-chars-minimum"    # Required for production
ADMIN_USERNAME="admin"                            # Default admin user
ADMIN_PASSWORD="secure-password"                  # Change from default

Optional configuration:

SERVER_PORT=8000
MCP_BASE_WORKING_DIR="./shared_host_folder"
ENVIRONMENT="development"                         # development|staging|production
ALLOW_ARBITRARY_SHELL_COMMANDS="false"           # Security: disabled by default
CORS_ORIGINS="http://localhost:3000,https://yourdomain.com"

# API Keys for LLM tools
OPENAI_API_KEY="sk-..."
GEMINI_API_KEY="..."

Authentication

Get a token:

curl -X POST http://localhost:8000/api/auth/login \
  -H "Content-Type: application/json" \
  -d '{"username":"admin","password":"admin123"}'

Use token:

curl -H "Authorization: Bearer YOUR_TOKEN" http://localhost:8000/api/protected

Available Tools

Tool

Description

file_system_create_directory

Create directories (sandboxed)

file_system_write_file

Write text files

file_system_read_file

Read text files

file_system_list_directory

List directory contents

execute_shell_command

Execute shell commands (filtered)

llm_generate_code_openai

Generate code via OpenAI API

llm_generate_code_gemini

Generate code via Gemini API

API Endpoints

  • GET /health - Health check

  • GET /metrics - Prometheus metrics

  • POST /api/auth/login - Authentication

  • POST /mcp/mcp.json/ - MCP JSON-RPC (requires auth)

  • POST /api/adapters/{type} - Create data adapters

  • GET /docs - Interactive API documentation

Security Features

  • JWT-based authentication with configurable providers

  • Path traversal prevention for file operations

  • Shell command filtering and sandboxing

  • Rate limiting on authentication endpoints

  • Security headers (HSTS, CSP, etc.)

  • CORS configuration

  • Audit logging for all operations

Development

Run tests:

pytest -q  # 53 passing, 21 skipped (FastMCP lifespan issue)

Testing

Run tests: pytest -q (53 passing, 21 skipped due to FastMCP lifespan integration)

The skipped tests require proper ASGI lifespan management which TestClient doesn't provide by default. Production server works correctly.

Linting:

pre-commit install
pre-commit run --all-files

Production Deployment

  1. Set strong JWT_SECRET (32+ characters)

  2. Change default ADMIN_PASSWORD

  3. Set ENVIRONMENT=production

  4. Configure appropriate CORS_ORIGINS

  5. Use HTTPS termination at load balancer

  6. Monitor /health and /metrics endpoints

See PRODUCTION_READINESS_REPORT.md for detailed checklist.

Architecture

  • FastMCP: Tool execution via Model Context Protocol

  • Starlette: Async web framework with middleware

  • Pydantic: Configuration management and validation

  • Prometheus: Metrics collection

  • JWT: Stateless authentication

  • Audit Logging: Structured event logging

License

MIT

F
license - not found
-
quality - not tested
B
maintenance

Maintenance

Maintainers
Response time
Release cycle
1Releases (12mo)

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/sdirishguy/mcp_server_project'

If you have feedback or need assistance with the MCP directory API, please join our Discord server