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Turn evaluations, Terraform plans, and AWS scans into architecture graphs and insights.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "byaml-mcp" yet — see the docs or source repo.
Generate a BYaML architecture graph from this Terraform plan and summarize the main resources and their relationships.
A BYaML architecture graph plus a brief summary of key infrastructure components and connections.
Using this AWS scan result, create an architecture graph and analyze which services could be affected if a critical resource fails.
An architecture graph with an explanation of impacted resources and dependency paths.
Create a BYaML architecture graph from this evaluation and summarize cost insights and the highest-priority remediation actions.
A graph, a cost summary, and a prioritized remediation plan.
A DevOps team can generate a BYaML architecture graph from a Terraform plan to understand resource relationships and assess blast radius before deployment. This helps surface risky changes earlier.
When a team has AWS scan results, it can turn them into an architecture graph and extract key insights. This is useful for reviewing cloud resource structure and dependencies.
During operations analysis or remediation work, teams can use evaluation inputs to generate cost summaries and remediation plans. This makes it easier to communicate impact and priorities internally.
It enables AI agents to generate BYaML architecture graphs from evaluations, Terraform plans, and AWS scans, then derive insights such as blast radius, cost summaries, and remediation plans.
No. The description explicitly says it can generate BYaML architecture graphs and related insights without writing YAML.
The provided information shows three input types: evaluations, Terraform plans, and AWS scans. For exact formats or installation details, see the source repository.
Scan AWS environments and generate architecture diagrams for infrastructure and security.
Give AI real-time Azure infrastructure access for ops checks, policy validation, and Terraform analysis.
Audit MCP configs for exposed access, secrets, models, and compliance AI-BOMs.
Query approved modules and generate compliant Azure Terraform infrastructure code.
Let MCP-compatible AI agents securely read and write architecture-map diagrams.
Turn OpenAPI specs into secure MCP servers with auth, policies, and auditing.