Moretes Architect MCP

Reliability

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How to connect

Add it to any MCP client that supports remote servers.

{
  "mcpServers": {
    "moretes-architect-mcp": {
      "type": "http",
      "url": "https://mcp.moretes.com/mcp"
    }
  }
}

48 tools

• architect_panel

  Convene architect personas (solution, enterprise, business, data, infrastructure, software, AI, security, governance, FinOps) on a subject: each returns its questions, checks, deliverables and the workbench tools to call. Lens, not a verdict.

• code_review_architecture

  Heuristic architecture and security scan of source code pasted as text (any language): secrets, insecure calls, SQL built by concatenation, disabled TLS, hardcoded endpoints, missing timeouts and retry hazards. Not a linter or SAST replacement.

• dependency_manifest_review

  Review a dependency manifest (package.json, requirements.txt, pyproject, go.mod, pom.xml, Gemfile, Cargo.toml as text) for unpinned ranges, git or URL sources, wildcard versions and missing lockfile hints.

• requirements_check

  Turn a workload brief into explicit requirements, gaps and research questions. No inferred SLA or budget.

• architecture_pattern

  Select a reference architecture by explicit workload pattern; returns tradeoffs, questions and Mermaid. provider maps the AWS services to Azure, GCP, OCI or open source equivalents.

• service_compare

  Compare curated AWS service families against user constraints. No automatic winner or fabricated scores.

• decision_record

  Generate an ADR from explicit alternatives, decision and consequences. Does not invent acceptance.

• well_architected_review

  Organize evidence by six pillars. A met control without evidence is unknown, never certified.

• threat_model

  Create STRIDE review prompts for explicitly supplied assets and trust boundaries. Review aid, not a scanner.

• failure_rehearsal

  Design a controlled failure drill with observable success criteria and stop conditions; never executes it.

• capacity_plan

  Calculate concurrency and daily data volume from explicit traffic assumptions. No service sizing guarantee.

• cost_model

  Calculate an auditable scenario using caller-supplied unit rates and source URLs. Does not guess AWS prices or credit coverage.

• slo_budget

  Calculate an availability error budget for a chosen period.

• migration_plan

  Prepare phased discovery, pilot, migration and rollback gates; includes AWS Transform integration discovery.

• architecture_diagram

  Build Mermaid from explicit nodes and edges. Sanitizes labels and rejects dangling edges.

• implementation_plan

  Turn an architecture decision into a delivery checklist with validation gates.

• agent_tool_contract

  Design a per-operation authorization and recovery contract for an agent tool.

• c4_model

  Build C4 context or container diagrams (Mermaid) from explicit people, systems, containers and relations. Validates endpoints; no infrastructure discovery.

• sequence_diagram

  Build a Mermaid sequence diagram from participants and ordered messages, with optional activation, notes and alt/loop blocks. Rejects unknown participants.

• service_equivalents

  Map a cloud capability to equivalent managed services on AWS, Azure, Google Cloud, OCI and open source. Names as of the snapshot date; verify current naming, regions and pricing before deciding.

• data_classification

  Classify data elements, map them to regulation hints (LGPD, GDPR, PCI DSS, HIPAA) and list handling controls and open questions. Review aid, not legal advice.

• openapi_review

  Heuristic review of an OpenAPI 3.x document (JSON): security, pagination, error responses, idempotency, versioning and documentation gaps. Not a linter replacement.

• event_contract

  Design an event contract: envelope fields, schema evolution rules, idempotency, ordering, DLQ and replay decisions for a named business event. Deterministic template with open questions.

• latency_budget

  Split an end-to-end latency objective across hops and show which hops exceed their share. Pure arithmetic over caller-supplied estimates.

• queue_sizing

  Size consumers with Little's law and stable Erlang C: utilization, wait probability, backlog drain time and target consumers. At most 100,000 total concurrent slots (consumers × concurrency).

• dr_strategy

  Compare disaster recovery tiers (backup-and-restore, pilot light, warm standby, active-active) against RTO, RPO and data constraints; returns feasible tiers and required capabilities, not a guarantee.

• retry_policy

  Compute an exponential backoff schedule with jitter, the worst-case wait and whether it fits a deadline; adds idempotency and circuit-breaker guidance.

• storage_growth

  Project storage volume and relative cost over time from ingest, retention, compression, replication and growth; suggests tiering thresholds.

• finops_unit_economics

  Compute cost per unit (request, customer, transaction), fixed versus variable split and the volume at which the marginal cost crosses a target. Caller supplies costs; no provider prices are guessed.

• postmortem

  Generate a blameless postmortem document from incident facts: timeline, impact, detection, contributing factors and owned action items. Rejects action items without owner and due date.

• runbook

  Generate an operational runbook from service facts: alerts, diagnostic steps, remediation, rollback, escalation and verification. Template with explicit placeholders for what the caller did not provide.

• agent_eval_plan

  Design an evaluation plan for an AI agent: golden set sizing, metrics, judge rubric, red-team cases and regression cadence from explicit capabilities and risks.

• prompt_injection_checklist

  Enumerate injection paths and controls for an agent from its tools and untrusted data sources; produces a checklist with status to fill, not a scan.

• rag_pipeline_plan

  Plan a retrieval-augmented generation pipeline from corpus facts: chunking, embedding, indexing, authorization, evaluation and cost drivers, with open questions. No vendor is chosen for you.

• mcp_server_review

  Heuristic safety review of ANOTHER MCP server from its tools/list output: tool-poisoning text, missing annotations, risky parameters, free-form schemas, name shadowing and context cost. Paste the JSON your client shows.

• mcp_config_review

  Review an MCP client configuration JSON (mcpServers map) for unpinned packages, inline secrets, plain HTTP, auto-approved tools and unreviewed enablement.

• iam_policy_review

  Inspect an IAM document for broad grants: AWS policy JSON (default), Azure custom role definition or Google Cloud IAM policy bindings (provider). Heuristic only; the provider analyzers are authoritative.

• cloudformation_review

  Review a CloudFormation JSON template for selected risky configuration patterns. Intrinsic functions are flagged for human review.

• terraform_plan_review

  Review a Terraform or OpenTofu plan exported as JSON (terraform show -json): deletions and replacements of stateful resources, public exposure, disabled encryption, literal credentials, broad policies and unpinned providers. Any provider; heuristic.

• kubernetes_manifest_review

  Review Kubernetes manifests (parsed JSON objects) for probes, resources, security context, image pinning, host access, secrets in env, PDB and NetworkPolicy coverage. No cluster access.

Security scan

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