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aws / awslabs-aws-diagram-mcp-server
Install & Compatibility
Where this runs
tested against v? · pip install
Install × environment matrix
Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux
muslpy 3.10–3.920 runs
build_error
glibcpy 3.10–3.920 runs
build_error
Code
Verified usage
Verified import paths — ran on the pinned version, not inferred.
mcp_server
✓ import mcp_server
This library is primarily a server application intended to be run via 'python -m mcp_server'. Direct programmatic import of its internal modules is generally not required for typical usage, which involves interacting with its HTTP API.
This quickstart demonstrates how to interact with the AWS Diagram MCP Server's API. First, ensure the server is installed (`pip install awslabs-aws-diagram-mcp-server`) and running in a separate terminal (`python -m mcp_server`). The client code then uses the `requests` library (`pip install requests`) to send a `diagrams` DSL string to the server's `/diagram` endpoint and saves the generated image locally.
import os
import requests # pip install requests
# --- Step 1: Run the MCP Server (in a separate terminal/process) ---
# The server application must be running for the client code below to work.
# In your terminal, run:
# pip install awslabs-aws-diagram-mcp-server
# python -m mcp_server
# By default, it listens on http://127.0.0.1:8000.
# You can configure host/port via environment variables (e.g., before running 'python -m mcp_server'):
# export MCP_SERVER_PORT=8001
# export MCP_SERVER_HOST=0.0.0.0
# --- Step 2: Client interaction example ---
server_host = os.environ.get('MCP_SERVER_HOST', '127.0.0.1')
server_port = os.environ.get('MCP_SERVER_PORT', '8000')
server_url = f"http://{server_host}:{server_port}"
print(f"Attempting to connect to MCP Server at {server_url}")
try:
# Check if the server is healthy
health_response = requests.get(f"{server_url}/health")
health_response.raise_for_status()
print("Server is healthy and reachable!")
# Example of sending a diagram DSL to generate an image
diagram_dsl = '''
from diagrams import Diagram, Cluster
from diagrams.aws.compute import EC2
from diagrams.aws.network import VPC
with Diagram("Simple Web Service", show=False, filename="simple_web_service"):
with Cluster("Web Servers"):
web = EC2("Web Instance")
vpc = VPC("MyVPC")
web >> vpc
'''
headers = {"Content-Type": "application/json"}
# The /diagram endpoint accepts a POST request with the DSL and desired output format.
# The `filename` in Diagram() constructor is respected by the server.
payload = {"diagram_source_code": diagram_dsl, "output_format": "png"}
diagram_response = requests.post(f"{server_url}/diagram", json=payload)
diagram_response.raise_for_status()
# The server returns the image content directly
output_filename = "simple_web_service.png"
with open(output_filename, "wb") as f:
f.write(diagram_response.content)
print(f"Diagram '{output_filename}' generated successfully!")
except requests.exceptions.ConnectionError:
print(f"Error: Could not connect to MCP server at {server_url}. Make sure it is running (e.g., 'python -m mcp_server') and accessible.")
except requests.exceptions.HTTPError as e:
print(f"HTTP Error from server: {e.response.status_code} - {e.response.text}")
except Exception as e:
print(f"An unexpected error occurred: {e}")
Debug
Known issues
gotchaThis package installs a server application, not a library meant for direct import of typical diagram-generating functions into your own script. You primarily run it as a module (`python -m mcp_server`) and interact with it via its HTTP API.fixFocus on interacting with the server's API (e.g., via `requests` or `curl`) after starting it, rather than trying to `import` and call functions directly within your application for diagram generation.
affects: All versions
gotchaThe server requires Python 3.12 or higher. Attempting to install or run with earlier Python versions will result in installation failures or runtime errors.fixEnsure your development and deployment environments use Python 3.12 or a newer compatible version. Tools like `pyenv` or `conda` can help manage multiple Python versions.
affects: <1.0.0 (and potentially early 1.x before 3.12 was enforced)
deprecatedConfiguration parameters, especially environment variable names for server settings like host and port, might change between major or minor versions. Always refer to the specific version's README or official documentation for accurate configuration details.fixConsult the `mcp-server` documentation on GitHub for the exact version you are using to verify configuration options, e.g., `MCP_SERVER_PORT` or `MCP_SERVER_HOST`.
affects: Potentially between 0.x and 1.x or future major versions.
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Version history
1.0.23latest on PyPI · released Mar 9, 2026
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Dependencies
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