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Cerebrium Skills MCP Server

Developer ToolsLow Risk9.7MCP RegistryRemote
Free

Server data from the Official MCP Registry

Search the Cerebrium docs: deployment, cerebrium.toml, hardware, endpoints. Also sends feedback.

About

Search the Cerebrium docs: deployment, cerebrium.toml, hardware, endpoints. Also sends feedback.

Remote endpoints: streamable-http: https://cerebrium.ai/docs/mcp

Security Report

9.7
Low Risk9.7Low Risk

Valid MCP server (1 strong, 0 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry.

3 tools verified · Open access · 1 issue found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Required

This plugin requests these system permissions. Most are normal for its category.

file_system

Check that this permission is expected for this type of plugin.

HTTP Network Access

Connects to external APIs or services over the internet.

Shell Command Execution

Runs commands on your machine. Be cautious — only use if you trust this plugin.

How to Connect

Remote Plugin

No local installation needed. Your AI client connects to the remote endpoint directly.

Add this to your MCP configuration to connect:

{
  "mcpServers": {
    "ai-cerebrium-docs": {
      "url": "https://cerebrium.ai/docs/mcp"
    }
  }
}

Documentation

View on GitHub

From the project's GitHub README.

Cerebrium agent skills

Official Agent Skills and hosted docs MCP for Cerebrium, the serverless GPU and CPU platform for real-time AI workloads. The skills teach a coding agent to write a valid cerebrium.toml, pick hardware and a region, deploy, call the endpoint, and debug the result without leaving the terminal. The MCP gives it live search over the documentation.

Works with Claude Code, Codex, Cursor, GitHub Copilot, Windsurf, Cline and anything else that reads the Agent Skills format.

Install

Any agent (installs the skills into every detected harness):

npx skills add CerebriumAI/cerebrium-skills -g -y
npx add-mcp https://cerebrium.ai/docs/mcp -n cerebrium-docs -g -y

Claude Code (one plugin bundles the skills and the docs MCP):

/plugin marketplace add CerebriumAI/cerebrium-skills
/plugin install cerebrium@cerebrium

Codex:

codex plugin marketplace add CerebriumAI/cerebrium-skills

Gemini CLI (one extension bundles the skills and the docs MCP):

gemini extensions install https://github.com/CerebriumAI/cerebrium-skills

Cursor loads the repository directly as an Agent Plugin: the root plugin.json and mcp.json are the open-standard manifests, so no Cursor-specific install step is needed.

Or agent-driven: paste this into the agent of your choice.

Install the Cerebrium agent toolkit following instructions from
github.com/CerebriumAI/cerebrium-skills: use `npx skills add` and `npx add-mcp`,
global and auto-confirmed for all agents (-g -y).

Then create an account and authenticate the CLI once:

# create an account at https://dashboard.cerebrium.ai (also where API keys are created)
pip install cerebrium   # or: brew tap cerebriumai/tap && brew install cerebrium
cerebrium login

Compute is billed per second: see pricing for current rates and any starting credit.

In CI, skip login and set CEREBRIUM_SERVICE_ACCOUNT_TOKEN instead.

What is in here

One skill, structured for progressive disclosure: agents load the ~120-line core (skills/cerebrium/SKILL.md, the workflow, the safety rules, the endpoint shapes) when a Cerebrium task appears, and pull in a reference file only when the task needs it.

ReferenceLoaded when the task involves
references/cli.mdAny cerebrium command: full surface, flags, non-interactive auth, CI/CD, which commands cost money.
references/config.mdcerebrium.toml: every key, the default the API applies when it is omitted, accepted ranges, rebuild triggers.
references/hardware.mdThe 13 accepted compute identifiers, per-GPU and per-plan limits, preference lists, regional availability, storage.
references/troubleshooting.mdFailed builds, queueing, reverted settings, the cold-start playbook.

The docs MCP (hosted at https://cerebrium.ai/docs/mcp) searches and reads the published documentation, and accepts documentation feedback: search_cerebrium, query_docs_filesystem_cerebrium, and submit_feedback. No account access, no key needed. It is declared twice on purpose, because the two formats are not interchangeable: .mcp.json is the Claude Code convention, and mcp.json at the repository root is the path the Agent Plugins standard requires, with that standard's streamable-http transport name.

The plugin metadata is likewise declared per host: .claude-plugin/ for Claude Code, .agents/plugins/ for Codex, root plugin.json for Agent Plugins clients such as Cursor, and gemini-extension.json for the Gemini CLI. server.json is the MCP registry entry.

Try it

  • "Deploy this FastAPI app to Cerebrium on an H100 with auth enabled, then follow the logs."
  • "My Cerebrium app queues requests under load. Work out why and fix the config."
  • "Which GPU and region fit a 13B vLLM model on Cerebrium, and what should the cerebrium.toml be?"

Related surfaces

  • Any docs page as markdown: append .md to the URL
  • Page index: https://cerebrium.ai/docs/llms.txt
  • Runnable examples: CerebriumAI/examples

Accuracy

Every default, enum, flag and signature here was read out of the CLI source and the API validator rather than copied from a docs page. See CONTRIBUTING.md for where to check each kind of claim, and keep it that way.

MIT licensed.

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