GitHub
by github
GitHub’s official server lets AI read and manage code, issues and pull requests in your account. Use GitHub’s hosted version or run it locally with Docker.
Computer or cloud★ 34,245MITUpdated 3 days ago
Install
Cloud DevOps MCP Server
Overview
Description from the maker (original English)
Cloud DevOps analysis with guarded Git, infrastructure, cloud and observability operations.
PopNx MCP’s three pillars
These three are never merged into one score: opinions, measurements and popularity are different things.
- User voiceiNo reviews yetReviews open together with accounts in a later step
- Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
- UsageiNot measured yet★ –
What you can do with it
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
- Connection: Runs on your computer
- Transport: stdio
- Category: Developer tools
Install
Pick the AI app you use, then copy the settings.
Before you install
- Basic checks: 1 of 1 passed
- Runs on your computer with your user’s permissions (files, network, apps).
- The registry lists no key to fill in.
You need
- npmNode.js installed (for the npx command)
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"cloud-devops": {
"command": "npx",
"args": [
"-y",
"cloud-devops-mcp-server"
]
}
}
}Run this in your terminal
claude mcp add cloud-devops -- npx -y cloud-devops-mcp-serverOr copy the settings yourself
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"cloud-devops": {
"command": "npx",
"args": [
"-y",
"cloud-devops-mcp-server"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Or copy the settings yourself
Paste into .vscode/mcp.json in your project
{
"servers": {
"cloud-devops": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"cloud-devops-mcp-server"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
What it can do
Runs on your computer; the tool list appears in your AI app after you install it.
Basic checksi
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026
- ✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account alexcgodwin, which owns the repo
- … Not checked yet
Still maintained
We have not read this repo from GitHub yet
- … Not checked yet
Has a licence
We have not read this repo from GitHub yet
- – Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
- – Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
- … Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints
Compared with others in Developer toolsi
- More stars than 0% of the other 1386 servers in this category
- Published to the registry more recently than 61% of the other 1386 servers in this category
- Basic checks equal to or better than 100% of the other 1386 servers in this category
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
Common questions
Is Cloud DevOps MCP Server safe?
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
What keys or codes does it need?
The registry does not list a required key, though some servers ask you to sign in on first use.
Does it run on my computer or in the cloud?
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
Is it still maintained?
The GitHub repo last changed –, and the latest version (0.14.0) reached the registry 35 days ago.
Which apps can use it?
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
What can I use instead?
In the same category: GitHub, Desktop Commander, Cloudflare MCP
Alternatives
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Desktop Commander
by wonderwhy-er
MCP server for terminal commands, file operations, and process management
Runs on your computer★ 10,225MITUpdated 15 days ago
Install
Cloudflare MCP
by cloudflare
Cloudflare MCP servers
Runs in the cloud★ 4,446Apache-2.0Updated 14 months ago
Install
README from the maker
Open the README
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
Cloud DevOps MCP Server
Cloud DevOps MCP Server is a Model Context Protocol v2 server by Alex C. Godwin. It provides evidence-backed Cloud DevOps analysis across infrastructure, identity, Kubernetes, CI/CD, SRE and software supply-chain controls.
The v0.14 line adds an opt-in OpsChugex change-intelligence and blast-radius gateway. The public MCP forwards bounded planned-change, topology and readiness evidence to a host-configured private OpsChugex service and returns change risk, impacted topology nodes, representative blast paths, blockers, warnings and evidence gaps. Proprietary dependency propagation, risk weighting and blocker rules are not included in this public MIT repository.
The v0.13 line adds an opt-in OpsChugex advanced FinOps gateway. The public MCP forwards bounded cloud-cost, utilization and Kubernetes allocation evidence to a host-configured private OpsChugex service and returns optimization opportunities, cost anomalies, low/high savings ranges, confidence, cost correlations and evidence gaps. Proprietary savings factors, anomaly thresholds, prioritization and deduplication are not included in this public MIT repository.
The v0.12 line adds an opt-in OpsChugex cloud security posture gateway. The public MCP forwards bounded cloud asset, identity, secret and network-reachability evidence to a host-configured private OpsChugex service and returns security score, risk level, ordered findings, attack paths, evidence gaps and recommendations. Proprietary security rules, severity thresholds, scoring and attack-path correlation are not included in this public MIT repository.
The v0.11 line adds an opt-in OpsChugex policy and governance gateway. The public MCP sends bounded resource evidence and approved exception metadata to a host-configured private OpsChugex service and returns pass, review or block decisions with control findings and evidence gaps. Proprietary profiles, rules, weights and exception-processing logic are not included in this public MIT repository.
The v0.10 line adds an opt-in OpsChugex root-cause intelligence gateway. The public MCP sends bounded incident evidence to a host-configured private OpsChugex service and returns evidence-ranked probable causes, contradictions, limitations and next checks. Proprietary ranking and correlation rules are not included in this public MIT repository.
The v0.9 line adds an opt-in distributed-tracing and SLO-intelligence plane for Grafana Tempo and Jaeger v3 trace reads, service dependency mapping, tracing coverage assessment, multi-window SLO burn-rate analysis and trace/SLO incident correlation. The v0.8 production-observability and operations-intelligence plane remains available for Prometheus, Grafana, CloudWatch Logs Insights, Kubernetes health, GitHub Actions diagnosis, cloud health, FinOps and drift. Live AWS, Azure and GCP access remains bounded and read-only. Cloud mutation remains intentionally unavailable.
Table of contents
- Why this exists
- Tools
- Architecture
- Quickstart
- Install from npm
- MCP clients
- Configuration
- Authenticated Streamable HTTP
- Public release verification
- Example tool input
- Demo outputs
- Docker
- Development
- Security model
- Roadmap
- Author
Why this exists
AI assistants are more useful in engineering work when they can call focused tools with clear inputs and consistent outputs. This server provides a Cloud DevOps tool layer for:
- Cross-domain release-risk correlation across infrastructure, identity, runtime and delivery.
- Infrastructure-as-code deployment risk analysis.
- Production incident runbook generation.
- CI/CD delivery readiness review.
- SLO error budget calculations.
- AWS IAM least-privilege review.
- AWS, Azure and GCP identity policy packs.
- Terraform destructive-change, public exposure and encryption security analysis.
- Kubernetes workload production readiness and security-policy analysis.
- GitHub Actions workflow security and deployment review.
- CycloneDX/SPDX SBOM quality and software supply-chain correlation.
- Optional authenticated Streamable HTTP serving for self-hosted remote access.
- Optional allowlisted live AWS/Azure/GCP inventory, observability, FinOps and drift signals.
- Optional Grafana Tempo and Jaeger v3 trace reads, service dependency maps and SLO burn-rate intelligence.
- Optional OpsChugex private root-cause intelligence across metrics, logs, traces, Kubernetes, cloud, Terraform and CI/CD evidence.
- Optional OpsChugex private policy and governance intelligence for development, staging, production and regulated profiles.
- Optional OpsChugex private cloud security posture intelligence for exposure, identity, secrets and attack-path analysis.
- Optional OpsChugex private advanced FinOps intelligence for rightsizing, anomaly detection, Kubernetes/cloud cost correlation and savings-range analysis.
- Optional OpsChugex private change intelligence for pre-change dependency propagation, blast-radius mapping, blockers and rollback/readiness analysis.
Tools
| Tool | Purpose |
|---|---|
assess_cloud_change_bundle | Correlates Terraform, IAM, Kubernetes and GitHub Actions evidence into one deployment-risk assessment with cross-domain change paths. |
assess_terraform_change | Scores Terraform/IaC risk and can derive evidence from raw Terraform plan JSON. |
build_incident_runbook | Produces a practical incident response runbook for a service, symptom, environment and severity. |
review_cicd_pipeline | Reviews CI/CD maturity while separating failed controls from unknown evidence. |
estimate_slo_error_budget | Calculates downtime and request-failure budgets with consistency validation. |
review_iam_policy | Parses IAM policy JSON and detects wildcard scope and privilege-escalation paths. |
review_kubernetes_deployment | Parses Kubernetes YAML for probes, resources, disruption protection, image and exposure risks. |
review_github_actions_workflow | Parses workflow YAML for triggers, immutable action pins, permissions, caching and concurrency. |
review_cloud_identity_policy | Applies AWS IAM, Azure RBAC or GCP IAM policy packs to raw policy JSON. |
review_terraform_security | Reviews Terraform plan JSON for destructive changes, public exposure, encryption, deletion protection and wildcard IAM. |
review_kubernetes_security | Reviews privileged mode, host access, service accounts, capabilities, seccomp, root filesystems and NetworkPolicy. |
review_software_supply_chain | Correlates CycloneDX/SPDX SBOM quality with CI action pinning, image immutability, signatures and provenance. |
Optional live multi-cloud reads
When explicitly enabled, six additional tools provide allowlisted AWS/Azure/GCP identity verification, bounded inventory, managed Kubernetes discovery, observability configuration summaries, FinOps waste signals and drift reporting. No cloud mutation commands are exposed. AWS general inventory is sourced from the Resource Groups Tagging API, so untagged AWS resources may not appear in that inventory or AWS drift comparison.
Optional production observability intelligence
When explicitly enabled, twelve additional tools provide bounded Prometheus queries, Grafana alert summaries, CloudWatch Logs Insights queries, Kubernetes pod-health summaries, GitHub Actions failure diagnosis, cross-signal incident correlation, cloud-health assessment, deployment/incident correlation, observability coverage assessment, FinOps correlation, cross-runtime drift analysis and operations briefs. Endpoints, cloud scopes, log groups, cluster contexts, namespaces and repositories are allowlisted. The layer is read-only and exposes no alert mutation, deployment mutation or arbitrary shell execution.
Optional distributed tracing and SLO intelligence
When explicitly enabled, six additional v0.9 tools provide bounded Tempo/Jaeger trace search and retrieval, service dependency mapping, tracing coverage assessment, multi-window SLO burn-rate analysis and trace/SLO incident correlation. Remote tracing endpoints must be allowlisted and use HTTPS unless loopback. Backend credentials stay in host environment variables. Trace search windows and result sizes are bounded, and the plane exposes no trace ingestion, sampling mutation or telemetry deletion.
Optional OpsChugex root-cause intelligence
When explicitly enabled, v0.10 exposes diagnose_root_cause. The tool accepts bounded evidence from metrics, logs, traces, Kubernetes, cloud, Terraform and CI/CD, then calls a host-configured private OpsChugex service. The public MCP contains no proprietary ranking rules, accepts no service URL or credential as tool input, and performs no remediation. Evidence scores represent evidence strength rather than statistical probability.
Optional OpsChugex policy and governance intelligence
When explicitly enabled, v0.11 exposes assess_governance_policy. The tool accepts bounded factual resource evidence plus optional owner-attributed, time-bounded exceptions and forwards them to the private OpsChugex policy engine. It returns pass, review, or block with control findings and evidence gaps.
The public MCP contains no proprietary governance profiles, policy rules, scoring weights, exception evaluation logic or enforcement capability. The service URL and token remain host-side and cannot be supplied as MCP arguments.
Optional OpsChugex cloud security posture intelligence
When explicitly enabled, v0.12 exposes assess_cloud_security_posture. The tool accepts bounded asset, identity, secret and network-reachability evidence and forwards it to the private OpsChugex security engine. It returns a security score, risk level, ordered findings, correlated attack paths, evidence gaps and recommended next actions.
The public MCP contains no proprietary security detection thresholds, severity rules, scoring logic or attack-path algorithm. It cannot rotate credentials, change IAM, modify network controls, alter encryption settings or remediate infrastructure.
Optional OpsChugex advanced FinOps intelligence
When explicitly enabled, v0.13 exposes analyze_advanced_finops. The tool accepts bounded cloud-cost, utilization and Kubernetes allocation evidence and forwards it to the private OpsChugex FinOps engine. It returns optimization opportunities, anomalies, savings ranges, confidence, cost correlations and evidence gaps.
The public MCP contains no proprietary savings factors, anomaly thresholds, prioritization rules, confidence algorithm or portfolio deduplication logic. It does not resize resources, terminate workloads, purchase commitments, change Kubernetes requests or perform billing actions.
Optional OpsChugex change intelligence and blast-radius analysis
When explicitly enabled, v0.14 exposes analyze_change_blast_radius. T
Only the beginning is shown; read the rest in the repo