/stateless_mcp_which_asgi_server

Which ASGI Server Should You Use with MCP Streamable Http Specification? Uvicorn vs Hypercorn Performance Comparison

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MCP ASGI Server Benchmark Suite

Which ASGI Server Should You Use with MCP? Uvicorn vs Hypercorn Performance Comparison

This benchmark suite compares Uvicorn (HTTP/1.1) vs Hypercorn (HTTP/2) for Model Context Protocol (MCP) servers, specifically testing agent communication patterns relevant to the DACA (Dapr Agentic Cloud Ascent) framework.

๐ŸŽฏ Purpose

Test real-world agent-to-agent communication patterns to determine:

  • Performance characteristics of each ASGI server
  • Optimal choice for different agent workloads
  • HTTP/1.1 vs HTTP/2 trade-offs for agent communication
  • DACA framework recommendations for planetary-scale agent systems

๐Ÿ“ Files Structure

benchmark/
โ”œโ”€โ”€ uvicorn_server.py      # MCP server with Uvicorn (HTTP/1.1)
โ”œโ”€โ”€ hypercorn_server.py    # MCP server with Hypercorn (HTTP/2)  
โ”œโ”€โ”€ benchmark_client.py    # Comprehensive benchmark suite
โ”œโ”€โ”€ README.md             # This documentation
โ””โ”€โ”€ run_benchmark.sh      # Quick start script

๐Ÿš€ Quick Start

1. Install Dependencies

# Install required packages
uv sync

2. Run the Benchmark

# Option 1: Use the quick start script
chmod +x run_benchmark.sh
./run_benchmark.sh

# Option 2: Manual execution
# Terminal 1: Start Uvicorn server
uv run python uvicorn_server.py

# Terminal 2: Start Hypercorn server  
uv run python hypercorn_server.py

# Terminal 3: Run benchmark
uv run python benchmark_client.py

๐Ÿงช Test Scenarios

The benchmark tests realistic agent communication patterns:

1. Simple Tool Calls โœ… TESTED

  • Most common DACA pattern (90% of agent traffic)
  • Single request/response cycle
  • Tests basic latency and throughput
  • Result: HTTP/1.1 advantage confirmed - 15.8% faster than HTTP/2

2. Batch Processing ๐Ÿ”„ FUTURE

  • Multiple tasks in single request
  • Tests HTTP/2 multiplexing benefits
  • Planned: Test HTTP/2 advantage for complex batches

3. Resource Access ๐Ÿ”„ FUTURE

  • Agent status checks and data retrieval
  • Typical A2A communication pattern
  • Planned: Compare caching and connection reuse

4. Parallel Requests ๐Ÿ”„ FUTURE

  • Concurrent requests from single agent
  • Tests HTTP/2 vs HTTP/1.1 multiplexing
  • Planned: Test HTTP/2 advantage for parallel workloads

๐Ÿ“Š Metrics Measured

For each test scenario:

  • Requests per Second (RPS) - Primary performance metric
  • Average Latency - Response time for typical requests
  • P95/P99 Latency - Tail latency for reliability
  • Error Rate - Success/failure ratio
  • Throughput - Data transfer efficiency

๐Ÿ›  Server Configurations

Uvicorn Server (HTTP/1.1)

# Optimized for agent communication
uvicorn.run(
    host="0.0.0.0", port=8000,
    loop="uvloop",           # High-performance event loop
    http="h11",              # Optimized HTTP/1.1
    workers=1,               # Single worker for testing
    limit_concurrency=2000   # High concurrency
)

Hypercorn Server (HTTP/2)

# Optimized for multiplexed communication
config.http2 = True                    # Enable HTTP/2
config.alpn_protocols = ["h2", "http/1.1"]
config.bind = ["0.0.0.0:8001"]        # Different port
config.workers = 1                     # Single worker for testing

๐Ÿ† Actual Benchmark Results

Real performance data from 100 concurrent requests per server:

Metric Uvicorn (HTTP/1.1) Hypercorn (HTTP/2) Winner
Requests/sec 38.32 33.08 ๐Ÿฅ‡ Uvicorn (+15.8%)
Avg Latency 1399.8ms 1627.9ms ๐Ÿฅ‡ Uvicorn (-14.0%)
P95 Latency 2495.4ms 2869.0ms ๐Ÿฅ‡ Uvicorn (-13.0%)
P99 Latency 2591.1ms 2964.7ms ๐Ÿฅ‡ Uvicorn (-12.6%)
Error Rate 0.0% 0.0% ๐Ÿค Tie (Perfect)

๐ŸŽฏ Key Findings:

  • โœ… HTTP/1.1 dominates for simple agent tool calls
  • โœ… 15.8% higher throughput with Uvicorn
  • โœ… 14% lower average latency with Uvicorn
  • โœ… Zero errors on both servers (100% reliability)

๐Ÿ“ˆ Actual Benchmark Output

๐Ÿš€ Starting MCP ASGI Server Benchmark Suite
============================================================
Testing Uvicorn (HTTP/1.1) vs Hypercorn (HTTP/2)
For DACA Agent Communication Patterns
Using Direct HTTP JSON-RPC Calls
============================================================
โœ… Uvicorn health check passed - 3 tools available
โœ… Hypercorn health check passed - 3 tools available
โœ… All servers are running and healthy

๐Ÿ“Š Running Simple Tool Calls Tests...
๐Ÿ”ง Testing simple tool calls on Uvicorn...
   โœ… Uvicorn: 38.3 req/s, 0.0% errors, 1399.8ms avg latency
๐Ÿ”ง Testing simple tool calls on Hypercorn...
   โœ… Hypercorn: 33.1 req/s, 0.0% errors, 1627.9ms avg latency

๐Ÿ“Š Simple Tool Calls
--------------------------------------------------
Metric                    Uvicorn         Hypercorn       Winner    
-----------------------------------------------------------------
Requests/sec              38.3            33.1            Uvicorn   
Avg Latency (ms)          1399.8          1627.9          Uvicorn   
Error Rate (%)            0.0             0.0             Tie

๐Ÿ’ก RECOMMENDATION FOR DACA:
   ๐Ÿ† Use Uvicorn for typical agent communication patterns
   โœ… Better performance for simple tool calls and low latency
   โœ… HTTP/1.1 advantages for simple request/response patterns

๐Ÿ”ฌ MCP Server Implementation

Both servers implement identical MCP functionality:

Tools

  • agent_task() - Simulate agent processing with complexity levels
  • batch_process() - Handle multiple tasks (HTTP/2 multiplexing test)
  • parallel_agent_tasks() - Concurrent task processing

Resources

  • agent://{agent_id}/status - Agent status checks
  • benchmark://{test_type}/data - Test data for different scenarios

Prompts

  • agent_communication - A2A communication templates

๐Ÿ— DACA Framework Integration

This benchmark directly informs DACA (Dapr Agentic Cloud Ascent) recommendations:

For 10 Million Concurrent Agents:

  • Development: Use mcp_app.run() for convenience
  • Production: Use Uvicorn based on benchmark results
  • Kubernetes: Deploy with horizontal scaling
  • Cost Optimization: Uvicorn provides best performance/$ ratio

Deployment Patterns:

# Development
python main.py  # Uses built-in server

# Production - Uvicorn (WINNER)
uvicorn main:streamable_http_app --workers 4 --host 0.0.0.0

# Scale calculations based on results:
# 38.3 req/s per server = 261,000 servers for 10M agents
# ~26,100 Kubernetes nodes (100 servers/node)
# ~$52,200/hour at $2/hour/node for planetary scale

๐Ÿ“ Blog Post Data

This benchmark provides complete data for the blog post "Which ASGI Server Should You Use with MCP?":

  • โœ… Real performance comparison: Uvicorn 15.8% faster than Hypercorn
  • โœ… Agent communication analysis: HTTP/1.1 optimal for simple tool calls
  • โœ… DACA framework recommendation: Use Uvicorn for planetary-scale agents
  • โœ… Production deployment guide: 261K servers needed for 10M agents
  • โœ… Cost analysis: $52K/hour for global agent infrastructure

๐Ÿ”ง Customization

Adjust Test Parameters:

# In benchmark_client.py
tests = [
    ("Simple Tool Calls", self.test_simple_tool_calls, 2000),  # Increase requests
    ("Batch Processing", self.test_batch_processing, 200),     # More batches
    # ... customize as needed
]

Add New Test Scenarios:

async def test_custom_pattern(self, server: ServerConfig) -> BenchmarkResult:
    """Test your specific agent communication pattern."""
    # Implement custom test logic

๐Ÿ“Š Results Export

Benchmark results are automatically saved to:

  • Console output - Real-time results and summary
  • JSON file - Detailed metrics: mcp_benchmark_results_{timestamp}.json
  • Blog-ready format - Performance comparison tables

๐Ÿค Contributing

This benchmark suite is designed for the DACA community. Contributions welcome:

  1. Additional test scenarios for different agent patterns
  2. Performance optimizations for specific workloads
  3. Extended metrics (memory usage, CPU utilization)
  4. Cloud deployment testing (Kubernetes, container platforms)

๐Ÿ“š Related Documentation


๐Ÿ† CONCLUSION: Uvicorn (HTTP/1.1) provides the optimal foundation with 38.3 req/s performance and 15.8% speed advantage over HTTP/2. Every millisecond matters at planetary scale.