GCP Platform Engineer vs Edgeone Pages MCP
A side-by-side look at the GCP Platform Engineer and Edgeone Pages MCP MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose GCP Platform Engineer for cloud platforms work as a local process; choose Edgeone Pages MCP for cloud platforms as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose GCP Platform Engineer when
- You need dedicated capabilities in the Cloud Platforms domain.
- You prefer a local stdio subprocess transport.
- You have the keys it needs:
PLATFORM_MCP_CONFIG, PLATFORM_MCP_ENVIRONMENTS, PLATFORM_MCP_DEFAULT_ENVIRONMENT, GOOGLE_APPLICATION_CREDENTIALS. - You want tools like
list_environments, query_logs, get_recent_errors.
Choose Edgeone Pages MCP when
- You need dedicated capabilities in the Cloud Platforms domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: API key required.
- You want tools like
deploy_folder, account_info.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Cloud Platforms | Cloud Platforms |
| Quality signal | 59/100 · Good | 65/100 · Great |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | Not declared | API key required |
| Pricing | Not declared | Free |
| Required env vars | PLATFORM_MCP_CONFIGPLATFORM_MCP_ENVIRONMENTSPLATFORM_MCP_DEFAULT_ENVIRONMENTGOOGLE_APPLICATION_CREDENTIALS | None listed |
| Verified owner | Community listing | Community listing |
| GitHub stars | 2 | 440 |
| Directory activity | 2 views 0 installs 0 upvotes | 4 views 0 installs 0 upvotes |
| Tools | 16 | 2 |
| Full listing | View GCP Platform Engineer | View Edgeone Pages MCP |
Tools & capabilities
GCP Platform Engineer tools 16
list_environmentsList the GCP environments this server can query and which is the default. Pass one of the returned names as the `environment` argument of any other tool to target that project (e.g. environment='production'). Omitting the argument uses the default environment shown here. Common shorthands such as 'prod' and 'stg' are accepted, as is a bare project id.query_logsQuery Cloud Logging with an advanced-filter expression. Args: filter: Cloud Logging advanced filter (e.g. 'severity>=WARNING AND resource.type="cloud_run_revision"'). Leave empty to match all logs. freshness: How far back to look, e.g. '30m', '1h', '2d'. Default '1h'. limit: Maximum number of entries to return (newest first). environment: Which configured GCP environment to query, e.g. 'staging' or 'production'. Omit to use the default environment. Call list_environments to see what is configured.get_recent_errorsReturn recent log entries at severity ERROR or higher. Args: service: Optional service name to narrow to (matched against resource.labels.service_name and logName). hours: How many hours back to search. Default 1. limit: Maximum number of entries to return (newest first). environment: Which configured GCP environment to query, e.g. 'staging' or 'production'. Omit to use the default environment.list_error_groupsList grouped application errors from Error Reporting with counts. Args: hours: Lookback window; snapped to the nearest supported period (1h, 6h, 1d, 1w, 30d). Default 24. service: Optional service name filter (Error Reporting "service" label). limit: Maximum number of error groups to return (most frequent first). environment: Which configured GCP environment to query, e.g. 'staging' or 'production'. Omit to use the default environment.query_metricQuery a Cloud Monitoring metric time series. Args: metric_type: Metric type, e.g. 'compute.googleapis.com/instance/cpu/utilization'. resource_filter: Optional extra filter, e.g. 'resource.labels.instance_id="123"'. window: How far back to query, e.g. '1h', '6h', '1d'. Default '1h'. aligner: Aggregation across the alignment period: MEAN, MAX, MIN, SUM, COUNT, RATE, PERCENTILE_99. Default MEAN. alignment_period: Bucket size for aggregation, e.g. '1m', '5m'. Default '5m'. limit: Maximum number of time series to return. environment: Which configured GCP environment to query, e.g. 'staging' or 'production'. Omit to use the default environment.list_alert_policiesList Cloud Monitoring alert policies and whether they are enabled. Args: limit: Maximum number of policies to return. environment: Which configured GCP environment to query, e.g. 'staging' or 'production'. Omit to use the default environment.list_uptime_checksList Cloud Monitoring uptime check configurations. Args: limit: Maximum number of uptime checks to return. environment: Which configured GCP environment to query, e.g. 'staging' or 'production'. Omit to use the default environment.list_cost_recommendationsAggregate GCP cost-optimization recommendations (idle/rightsizing/etc). Fans out the cost recommenders across the locations where the project has resources. Recommenders/locations that are empty or not enabled are skipped. Args: locations: Optional comma-separated zones/regions to scan (e.g. 'us-central1,us-central1-a'). If empty, auto-discovers from Asset Inventory (requires the Cloud Asset API). limit_per_call: Max recommendations to pull per recommender+location. environment: Which configured GCP environment to query, e.g. 'staging' or 'production'. Omit to use the default environment.list_recommendationsList recommendations from a specific recommender at a specific location. Args: recommender_id: Recommender id, e.g. 'google.compute.instance.MachineTypeRecommender' or 'google.iam.policy.Recommender'. location: Zone (e.g. 'us-central1-a'), region (e.g. 'us-central1'), or 'global' depending on the recommender. Default 'global'. limit: Maximum number of recommendations to return. environment: Which configured GCP environment to query, e.g. 'staging' or 'production'. Omit to use the default environment.get_cost_breakdownSummarize recent spend from the BigQuery billing export. By default this reports spend for the selected environment's project only. A billing export table covers every project on the billing account, and several environments commonly share one table, so an unfiltered query would return identical account-wide totals for staging and production. Only the environment holding the export needs 'billing_export_table' set: one billing account exports to one project, and that export already covers every project on the account. Asking any other environment for costs returns an error naming the one that has it. Args: group_by: One of 'service', 'sku', 'project', 'region'. Default 'service'. days: Lookback window in days over usage_start_time. Default 30. limit: Max rows returned (highest net cost first). all_projects: Report the whole billing account instead of just this environment's project. Pair with group_by='project' to compare projects; the totals then are not specific to this environment. environment: Which configured GCP environment to bill against, e.g. 'staging' or 'production'. Omit to use the default environment.get_billing_infoReturn the billing account linked to the project and its status. Args: environment: Which configured GCP environment to inspect, e.g. 'staging' or 'production'. Omit to use the default environment.search_assetsSearch all cloud resources in the project via Cloud Asset Inventory. Args: asset_types: Optional comma-separated asset types to filter, e.g. 'compute.googleapis.com/Instance,run.googleapis.com/Service'. query: Optional free-text/structured query, e.g. 'state:RUNNING' or 'location:us-central1'. limit: Maximum number of resources to return. Default 50; raise it when you know you need a full inventory, since each resource costs context. include_labels: Include resource labels. Off by default because deployment labels are usually the largest part of the response and rarely answer the question being asked. environment: Which configured GCP environment to search, e.g. 'staging' or 'production'. Omit to use the default environment. Call list_environments to see what is configured.- +4 more on the listing page
Edgeone Pages MCP tools 2
deploy_folderDeploy a folder containing web assets to EdgeOne Pages. Supports built projects (from build tools like Vite, Webpack, etc.), simple static file projects (HTML, CSS, JS files), and NextJS full-stack projects. Returns: deployment URL and project metadata. IMPORTANT RULES: 1. This is the ONLY deployment method for EdgeOne Pages/Makers. Do NOT fallback to other deployment tools (cloudstudio, vercel, netlify, etc.) if this tool fails. Instead, report the error to the user and suggest fixes based on the error message. 2. The projectName parameter should be a meaningful name describing the project (e.g. "my-blog", "todo-app", "ai-chat-demo"). Do NOT use date-based directory names or random strings as project names. Generate a descriptive name based on the project's purpose or content. 3. After deployment succeeds, your response MUST start with: "🎉 部署成功，页面已上线至 EdgeOne Makers". Then display the "url" field from the response EXACTLY as-is, character for character. Do NOT modify, truncate, or strip any part of the URL (especially query parameters like ?eo_token=...&eo_time=...). Without the full query string the page returns 401. The URL must be shown as a complete clickable link — never shorten it, never show just the domain. Do NOT open local HTML files with file:// protocol as preview. 4. If the user is not logged in, a browser login page will open automatically. No need to ask about region — the login page handles site selection internally. 5. NEVER open the deployment URL in the built-in browser/webview. The built-in browser cannot handle SSO redirects (302). Always show the URL as a clickable text link for the user to open in their system browser manually.account_infoGet the current EdgeOne Makers login status and account information. Use when the user asks about their login status, account info, who they are logged in as, or wants to check their EdgeOne account. Returns account name, ID, and login type.
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
GCP Platform Engineer
{
"mcpServers": {
"gcp-platform-engineer": {
"command": "uvx",
"args": [
"platform-mcp"
],
"env": {
"PLATFORM_MCP_CONFIG": "YOUR_PLATFORM_MCP_CONFIG_HERE",
"PLATFORM_MCP_ENVIRONMENTS": "YOUR_PLATFORM_MCP_ENVIRONMENTS_HERE",
"PLATFORM_MCP_DEFAULT_ENVIRONMENT": "YOUR_PLATFORM_MCP_DEFAULT_ENVIRONMENT_HERE",
"GOOGLE_APPLICATION_CREDENTIALS": "YOUR_GOOGLE_APPLICATION_CREDENTIALS_HERE"
}
}
}
}
Edgeone Pages MCP
{
"mcpServers": {
"tencentedgeone-edgeone-pages-mcp": {
"command": "npx",
"args": [
"@edgeone/makers-mcp@latest"
]
}
}
}
Frequently asked questions
GCP Platform Engineer is categorized under Cloud Platforms and uses a local stdio subprocess. Edgeone Pages MCP belongs to Cloud Platforms and uses a local stdio subprocess. Pick GCP Platform Engineer for cloud platforms work and Edgeone Pages MCP for cloud platforms.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
GCP Platform Engineer has no declared pricing — check the project's own site. Edgeone Pages MCP is listed as free. Auth: api key required. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add gcp-platform-engineer and tencentedgeone-edgeone-pages-mcp as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, GCP Platform Engineer has a quality signal of 59/100 (Good) with 2 views, 0 installs and 2 GitHub stars. Edgeone Pages MCP has 65/100 (Great) with 4 views, 0 installs and 440 GitHub stars.