Temps

Temps MCP Server: Manage Infrastructure via AI

February 18, 2026 (5mo ago)

Written by Temps Team

Last updated February 18, 2026 (5mo ago)

Back to all posts

Temps

Temps MCP Server: Manage Infrastructure via AI

February 18, 2026 (5mo ago)

Written by Temps Team

Last updated February 18, 2026 (5mo ago)

The fastest way to give an AI agent full control of your deployment infrastructure is the Temps MCP Server — a Model Context Protocol integration that exposes 224 tools across 30 categories, from triggering deployments and reading analytics to provisioning Redis and querying error stacks. Install it with npx @temps-sdk/mcp, point it at your Temps instance, and your AI agent can manage servers in plain English.

The Temps MCP Server turns Claude, Cursor, Windsurf, and any MCP-compatible client into a full infrastructure operator. Instead of switching between browser tabs to deploy, check errors, and scale environments, you describe what you need in natural language and the agent handles the rest.

What Is the Temps MCP Server?

The Model Context Protocol (MCP) is an open standard that lets AI assistants call tools on external systems. The Temps MCP Server implements this standard for the entire Temps platform — deployments, analytics, services, domains, monitoring, error tracking, backups, and more.

Three verified claims about the Temps MCP Server:

224 tools, 30 categories — covers every operation you can perform via the Temps dashboard or CLI, from triggering a deployment to querying per-country visitor breakdowns.
Category filtering built in — load only the tools you need (e.g., --tools deployments,analytics) to reduce context and improve tool selection accuracy.
Free to self-host, ~$6/mo on Temps Cloud — the MCP server ships with Temps, which is Apache 2.0 and free to self-host. Temps Cloud runs on Hetzner at cost + 30%, with no per-seat fees.

How Do You Set Up the Temps MCP Server?

Step 1: Get an API Key

Create an API key from your Temps dashboard under Settings > API Keys, or via CLI:

bunx @temps-sdk/cli apikeys create --name "mcp-agent" --role admin

Step 2: Configure Your AI Client

Claude Desktop — add to claude_desktop_config.json:

{
  "mcpServers": {
    "temps": {
      "command": "npx",
      "args": ["@temps-sdk/mcp"],
      "env": {
        "TEMPS_API_URL": "https://your-temps-instance.com",
        "TEMPS_API_KEY": "tk_your_api_key"
      }
    }
  }
}

Claude Code — add to .mcp.json in your project root:

{
  "mcpServers": {
    "temps": {
      "command": "npx",
      "args": ["@temps-sdk/mcp"],
      "env": {
        "TEMPS_API_URL": "https://your-temps-instance.com",
        "TEMPS_API_KEY": "tk_your_api_key"
      }
    }
  }
}

Cursor — add to .cursor/mcp.json:

{
  "mcpServers": {
    "temps": {
      "command": "npx",
      "args": ["@temps-sdk/mcp", "--tools", "deployments,analytics"],
      "env": {
        "TEMPS_API_URL": "https://your-temps-instance.com",
        "TEMPS_API_KEY": "tk_your_api_key"
      }
    }
  }
}

Also works with Windsurf, Cline, OpenCode, OpenAI Codex, and any other MCP-compatible client.

Step 3: Start Asking

No special syntax required. Ask your AI agent to manage infrastructure in natural language.

224 Tools Across 30 Categories

The MCP server covers every part of the Temps platform:

Category	What you can do
Deployments	Trigger, roll back, pause, resume, cancel. Stream build logs with parsed pipeline stages.
Environments	Create staging/production environments, manage env vars, scale replicas, update resource limits.
Analytics	Query visitors, sessions, page views, bounce rates. Break down by country, browser, device, UTM parameters, referrer, and 15+ other properties.
Containers	List, start, stop, restart. Get resource metrics and runtime logs.
Domains & SSL	Add custom domains, verify DNS, renew SSL certificates, manage ACME challenges.
Services	Provision and manage PostgreSQL, Redis, S3, and MongoDB.
Backups	Configure schedules, manage S3 sources, trigger manual backups.
Monitoring	Create uptime monitors, check status, view response time history.
Error Tracking	List error groups, view stack traces, get error dashboards and stats.
Security	Run vulnerability scans, manage IP access rules, configure security policies.
And more	Webhooks, DNS providers, funnels, incidents, audit logs, notifications, load balancer routes, proxy logs, API keys, users.

Load Only What You Need

224 tools is a lot of context for an AI agent. The server supports category filtering — load only the tools relevant to your workflow:

{
  "mcpServers": {
    "temps": {
      "command": "npx",
      "args": ["@temps-sdk/mcp", "--tools", "deployments,analytics,projects"],
      "env": {
        "TEMPS_API_URL": "https://your-instance.example.com",
        "TEMPS_API_KEY": "tk_..."
      }
    }
  }
}

This loads ~33 tools instead of 224. Your AI agent responds faster, selects the right tool more reliably, and uses less context.

You can also filter via environment variable:

TEMPS_MCP_TOOLS=deployments,analytics npx @temps-sdk/mcp

Run npx @temps-sdk/mcp --help to see all 30 available categories.

Real Conversations

Here's what it looks like in practice.

"What's the bounce rate on our pricing page?"

You: What's the bounce rate on /pricing for the last 7 days?

Agent: [calls get_page_detail with page_path="/pricing"]

Page Detail: /pricing

| Metric           | Value  |
| ---              | ---    |
| Unique Visitors  | 1,847  |
| Total Page Views | 2,312  |
| Avg Time on Page | 42.3s  |
| Bounce Rate      | 68.2%  |
| Entry Rate       | 31.5%  |
| Exit Rate        | 45.1%  |

Top Referrers:
| Referrer          | Visits | %     |
| google.com        | 892    | 38.6% |
| twitter.com       | 341    | 14.7% |
| (direct)          | 289    | 12.5% |

"Deploy to production and show me the logs"

You: Deploy my-app to production and stream the build logs

Agent: [calls trigger_deployment]
       [calls get_deployment_logs]

Deployment #87 — Pipeline Stages

| # | Stage        | Status     | Duration |
| 1 | Clone        | success    | 3s       |
| 2 | Build        | success    | 45s      |
| 3 | Push Image   | success    | 12s      |
| 4 | Deploy       | success    | 8s       |
| 5 | Health Check | success    | 5s       |

All stages passed. Deployment is live.

"Scale staging to 3 replicas"

You: Scale the staging environment to 3 replicas

Agent: [calls scale_environment with replicas=3]

Environment scaled. Staging now running 3 replicas.

"Show me recent errors"

You: Show me the last 10 error groups from production

Agent: [calls list_error_groups with limit=10]

Error Groups (Production)

| Error                              | Count | Last Seen |
| TypeError: Cannot read property    | 124   | 2 min ago |
| UnhandledPromiseRejection          | 31    | 8 min ago |
| RangeError: Maximum call stack     | 7     | 1 hr ago  |

Analytics Deep Dive

The 14 analytics tools deserve special attention. You can query traffic data the same way you'd ask a colleague:

"How many unique visitors did we get today?" — get_unique_counts
"Show me hourly traffic for the last week" — get_hourly_visits
"What are the top pages?" — get_page_paths
"What's the bounce rate on /docs?" — get_page_detail
"Where is our traffic coming from?" — get_property_breakdown with group_by=referrer_hostname
"Which browsers are our users on?" — get_property_breakdown with group_by=browser
"Show me UTM campaign performance" — get_property_breakdown with group_by=utm_campaign
"Where are users dropping off?" — get_page_flow
"What's our overall engagement rate?" — get_general_stats
"Who's on the site right now?" — get_active_visitors

21 properties available for breakdowns: country, city, region, browser, device_type, operating_system, referrer_hostname, page_path, channel, language, utm_source, utm_medium, utm_campaign, utm_term, utm_content, and more.

Temps MCP Server vs Alternatives

There are a few other ways to give an AI agent infrastructure access. Here's how they compare:

	Temps MCP Server	Custom MCP Implementation	Direct API Calls
Setup time	5 minutes	Days to weeks	Hours
Coverage	224 tools, full platform	Whatever you build	Manual per endpoint
Analytics access	Built-in, 14 tools	Not included	Requires separate integration
Self-hosted	Yes (free, Apache 2.0)	Depends	Yes
Cost	Included with Temps	Engineering time	API costs only
Tool discovery	Automatic via MCP	Manual	Manual

vs custom MCP server on another platform: If you're running on Heroku, Railway, or Render, you'd need to build each tool yourself — no built-in analytics, no session replay, no integrated error tracking. The Temps MCP Server ships those as first-class tools because Temps includes those features natively.

vs direct API calls in agent prompts: Telling your AI agent the API endpoints and having it call fetch() works for one-off tasks but breaks down at scale. The MCP protocol gives agents structured tool definitions, typed parameters, and error handling that raw API calls lack.

Quotable fact: The Temps MCP Server exposes the same infrastructure operations that Temps engineers use internally — 224 tools generated directly from the Temps OpenAPI spec, kept in sync with every release.

Bug Fixes in This Release

This release also includes fixes that improve reliability:

Environment scaling — scale_environment and update_environment_resources now use the correct HTTP method (PUT instead of PATCH). Resource fields corrected from string to integer types.
Deployment logs — get_deployment_logs now properly parses JSONL responses and renders a pipeline stage summary with formatted log output.
CLI package name — Documentation corrected from @temps/cli to @temps-sdk/cli.

Open Source

The MCP server is part of the Temps ecosystem and fully open source under Apache 2.0. Inspect the code, contribute tools, or fork it for your own platform.

The Temps MCP Server is available now. Install with npx @temps-sdk/mcp and start managing your infrastructure from any AI agent.

Back to all posts

What Is the Temps MCP Server?

Three verified claims about the Temps MCP Server:

224 tools, 30 categories — covers every operation you can perform via the Temps dashboard or CLI, from triggering a deployment to querying per-country visitor breakdowns.
Category filtering built in — load only the tools you need (e.g., --tools deployments,analytics) to reduce context and improve tool selection accuracy.
Free to self-host, ~$6/mo on Temps Cloud — the MCP server ships with Temps, which is Apache 2.0 and free to self-host. Temps Cloud runs on Hetzner at cost + 30%, with no per-seat fees.

How Do You Set Up the Temps MCP Server?

Step 1: Get an API Key

Create an API key from your Temps dashboard under Settings > API Keys, or via CLI:

bunx @temps-sdk/cli apikeys create --name "mcp-agent" --role admin

Step 2: Configure Your AI Client

Claude Desktop — add to claude_desktop_config.json:

{
  "mcpServers": {
    "temps": {
      "command": "npx",
      "args": ["@temps-sdk/mcp"],
      "env": {
        "TEMPS_API_URL": "https://your-temps-instance.com",
        "TEMPS_API_KEY": "tk_your_api_key"
      }
    }
  }
}

Claude Code — add to .mcp.json in your project root:

{
  "mcpServers": {
    "temps": {
      "command": "npx",
      "args": ["@temps-sdk/mcp"],
      "env": {
        "TEMPS_API_URL": "https://your-temps-instance.com",
        "TEMPS_API_KEY": "tk_your_api_key"
      }
    }
  }
}

Cursor — add to .cursor/mcp.json:

{
  "mcpServers": {
    "temps": {
      "command": "npx",
      "args": ["@temps-sdk/mcp", "--tools", "deployments,analytics"],
      "env": {
        "TEMPS_API_URL": "https://your-temps-instance.com",
        "TEMPS_API_KEY": "tk_your_api_key"
      }
    }
  }
}

Also works with Windsurf, Cline, OpenCode, OpenAI Codex, and any other MCP-compatible client.

Step 3: Start Asking

No special syntax required. Ask your AI agent to manage infrastructure in natural language.

224 Tools Across 30 Categories

The MCP server covers every part of the Temps platform:

Category	What you can do
Deployments	Trigger, roll back, pause, resume, cancel. Stream build logs with parsed pipeline stages.
Environments	Create staging/production environments, manage env vars, scale replicas, update resource limits.
Analytics	Query visitors, sessions, page views, bounce rates. Break down by country, browser, device, UTM parameters, referrer, and 15+ other properties.
Containers	List, start, stop, restart. Get resource metrics and runtime logs.
Domains & SSL	Add custom domains, verify DNS, renew SSL certificates, manage ACME challenges.
Services	Provision and manage PostgreSQL, Redis, S3, and MongoDB.
Backups	Configure schedules, manage S3 sources, trigger manual backups.
Monitoring	Create uptime monitors, check status, view response time history.
Error Tracking	List error groups, view stack traces, get error dashboards and stats.
Security	Run vulnerability scans, manage IP access rules, configure security policies.
And more	Webhooks, DNS providers, funnels, incidents, audit logs, notifications, load balancer routes, proxy logs, API keys, users.

Load Only What You Need

224 tools is a lot of context for an AI agent. The server supports category filtering — load only the tools relevant to your workflow:

{
  "mcpServers": {
    "temps": {
      "command": "npx",
      "args": ["@temps-sdk/mcp", "--tools", "deployments,analytics,projects"],
      "env": {
        "TEMPS_API_URL": "https://your-instance.example.com",
        "TEMPS_API_KEY": "tk_..."
      }
    }
  }
}

This loads ~33 tools instead of 224. Your AI agent responds faster, selects the right tool more reliably, and uses less context.

You can also filter via environment variable:

TEMPS_MCP_TOOLS=deployments,analytics npx @temps-sdk/mcp

Run npx @temps-sdk/mcp --help to see all 30 available categories.

Real Conversations

Here's what it looks like in practice.

"What's the bounce rate on our pricing page?"

You: What's the bounce rate on /pricing for the last 7 days?

Agent: [calls get_page_detail with page_path="/pricing"]

Page Detail: /pricing

| Metric           | Value  |
| ---              | ---    |
| Unique Visitors  | 1,847  |
| Total Page Views | 2,312  |
| Avg Time on Page | 42.3s  |
| Bounce Rate      | 68.2%  |
| Entry Rate       | 31.5%  |
| Exit Rate        | 45.1%  |

Top Referrers:
| Referrer          | Visits | %     |
| google.com        | 892    | 38.6% |
| twitter.com       | 341    | 14.7% |
| (direct)          | 289    | 12.5% |

"Deploy to production and show me the logs"

You: Deploy my-app to production and stream the build logs

Agent: [calls trigger_deployment]
       [calls get_deployment_logs]

Deployment #87 — Pipeline Stages

| # | Stage        | Status     | Duration |
| 1 | Clone        | success    | 3s       |
| 2 | Build        | success    | 45s      |
| 3 | Push Image   | success    | 12s      |
| 4 | Deploy       | success    | 8s       |
| 5 | Health Check | success    | 5s       |

All stages passed. Deployment is live.

"Scale staging to 3 replicas"

You: Scale the staging environment to 3 replicas

Agent: [calls scale_environment with replicas=3]

Environment scaled. Staging now running 3 replicas.

"Show me recent errors"

You: Show me the last 10 error groups from production

Agent: [calls list_error_groups with limit=10]

Error Groups (Production)

| Error                              | Count | Last Seen |
| TypeError: Cannot read property    | 124   | 2 min ago |
| UnhandledPromiseRejection          | 31    | 8 min ago |
| RangeError: Maximum call stack     | 7     | 1 hr ago  |

Analytics Deep Dive

The 14 analytics tools deserve special attention. You can query traffic data the same way you'd ask a colleague:

"How many unique visitors did we get today?" — get_unique_counts
"Show me hourly traffic for the last week" — get_hourly_visits
"What are the top pages?" — get_page_paths
"What's the bounce rate on /docs?" — get_page_detail
"Where is our traffic coming from?" — get_property_breakdown with group_by=referrer_hostname
"Which browsers are our users on?" — get_property_breakdown with group_by=browser
"Show me UTM campaign performance" — get_property_breakdown with group_by=utm_campaign
"Where are users dropping off?" — get_page_flow
"What's our overall engagement rate?" — get_general_stats
"Who's on the site right now?" — get_active_visitors

Temps MCP Server vs Alternatives

There are a few other ways to give an AI agent infrastructure access. Here's how they compare:

	Temps MCP Server	Custom MCP Implementation	Direct API Calls
Setup time	5 minutes	Days to weeks	Hours
Coverage	224 tools, full platform	Whatever you build	Manual per endpoint
Analytics access	Built-in, 14 tools	Not included	Requires separate integration
Self-hosted	Yes (free, Apache 2.0)	Depends	Yes
Cost	Included with Temps	Engineering time	API costs only
Tool discovery	Automatic via MCP	Manual	Manual

Quotable fact: The Temps MCP Server exposes the same infrastructure operations that Temps engineers use internally — 224 tools generated directly from the Temps OpenAPI spec, kept in sync with every release.

Bug Fixes in This Release

This release also includes fixes that improve reliability:

Environment scaling — scale_environment and update_environment_resources now use the correct HTTP method (PUT instead of PATCH). Resource fields corrected from string to integer types.
Deployment logs — get_deployment_logs now properly parses JSONL responses and renders a pipeline stage summary with formatted log output.
CLI package name — Documentation corrected from @temps/cli to @temps-sdk/cli.

Open Source

The MCP server is part of the Temps ecosystem and fully open source under Apache 2.0. Inspect the code, contribute tools, or fork it for your own platform.

The Temps MCP Server is available now. Install with npx @temps-sdk/mcp and start managing your infrastructure from any AI agent.