// Generate a benchmark report from stress test results (registration, API performance, search concurrency). Reads JSON result files and produces a markdown report suitable for docs/benchmarks/.
Generate a usage report for MCP Gateway Registry by SSHing into the telemetry bastion host, exporting telemetry data from DocumentDB, and producing a formatted markdown report with deployment insights.
Install (deploy) MCP Gateway & Registry on AWS using the Terraform aws-ecs stack (ECS Fargate, Aurora, DocumentDB, Keycloak). Asks whether you are running from an EC2 instance or a local laptop, confirms the required AWS IAM permissions are in place, clones the repository, bootstraps the toolchain (uv, AWS CLI, Terraform), configures terraform.tfvars, runs the two-stage terraform apply, and completes post-deployment setup. Does NOT create IAM roles itself — it tells you the permissions you need and offers to guide you through setting them up.
Create release notes for a new version tag. Gathers all commits, PRs, issues fixed, and breaking changes since a previous release. Creates the release notes markdown file, tags the repo, and pushes. Asks the user to confirm the base version to diff against.
Design and document new features with GitHub issue, low-level design (LLD), expert review, and testing plan. Creates structured documentation in .scratchpad/ with issue spec, technical design with diagrams and pseudo-code, multi-persona expert review, and a testing plan covering functional (curl and registry_management.py), backwards-compatibility, UX, ECS/terraform, and E2E API tests. Supports starting from a user description OR an existing GitHub issue URL. Folder naming: issue-{number}/ for existing issues, {feature-name}/ for new features.
Debug issues in the MCP Gateway Registry using first-principles thinking. Invoke when something is broken, timing out, returning errors, or behaving unexpectedly. Forces structured root-cause analysis before any code change is proposed.
Review a GitHub pull request using multiple expert personas. Takes a PR URL as input, analyzes the changes, and generates comprehensive review feedback from different perspectives (Merge Specialist, Frontend, Backend, Security, DevOps, AI/Agent, SRE, Chief Architect).
| name | benchmark-report |
| description | Generate a benchmark report from stress test results (registration, API performance, search concurrency). Reads JSON result files and produces a markdown report suitable for docs/benchmarks/. |
| license | Apache-2.0 |
| metadata | {"author":"mcp-gateway-registry","version":"1.0"} |
Generate a markdown benchmark report from stress test result files. The report documents the registry's performance characteristics under load, including registration throughput, API latency, and semantic search concurrency scaling.
tests/stress/results/<backend>/size-<N>/registration.json, api_perf.json, search_concurrency.jsonregistry_info (deployment configuration snapshot)/benchmark-report [RESULTS_DIR] [OUTPUT_PATH]
tests/stress/results/documentdb/size-100)docs/benchmarks/benchmark-report.md)/usr/bin/python3 .claude/skills/benchmark-report/generate_benchmark_report.py \
--results-dir tests/stress/results/documentdb/size-100 \
--output docs/benchmarks/benchmark-report.md
The script reads all three JSON files, extracts the key metrics, and produces a structured markdown report.
After generation:
The generated report includes:
registry_info (version, cloud, compute, storage, auth, embeddings, corpus size)registration.json (success rates, latency percentiles per entity type)api_perf.json (list endpoints and semantic search at k=5/10/50)search_concurrency.json (latency and throughput at concurrency 1/10/100)docs/benchmarks/
benchmark-report.md # The generated report (committed to repo)