Openlayer Skills MCP Server

Openlayer Skills

Agent Skills that teach AI coding assistants (Claude Code, Cursor, GitHub Copilot, etc.) how to integrate apps with Openlayer — the AI evaluation and observability platform.

Coding agents produce significantly better results with the skill installed, because they are conditioned to follow Openlayer's current best practices instead of guessing from memory (outdated SDK calls, wrong env vars, invented test configs).

Skills

Installation

Claude Code plugin

claude plugin marketplace add openlayer-ai/openlayer-skills
claude plugin install openlayer@openlayer

Cursor plugin

/add-plugin openlayer

GitHub Copilot

GitHub Copilot reads .github/plugin/plugin.json and the same skills and .mcp.json as Claude Code.

In VS Code, add the marketplace to your settings.json, then install Openlayer from the Extensions view (search @agentPlugins):

{
  "chat.plugins.marketplaces": ["openlayer-ai/openlayer-skills"]
}

In the Copilot CLI:

copilot plugin marketplace add openlayer-ai/openlayer-skills
copilot plugin install openlayer@openlayer

Other agents

Codex, Gemini CLI, Windsurf, opencode, and dozens more install through the skills CLI:

npx skills add openlayer-ai/openlayer-skills --skill "openlayer"

For claude.ai, Copilot's cloud coding agent and code review, a manual symlink, or anything else, see the installation guide — it is the source of truth and stays current as these tools change.

Prerequisites

An Openlayer account and an API key:

export OPENLAYER_API_KEY=...
# self-hosted / local only:
export OPENLAYER_BASE_URL=https://api.openlayer.com/v1

Find your API key in the Openlayer app under Workspace settings → API keys (see https://docs.openlayer.com/workspace-and-projects/find-your-api-key).

Usage

Once installed, the agent uses the skill automatically when relevant — for example:

• Adding Openlayer tracing/monitoring to an LLM or agent app
• Setting up offline evals (openlayer.json + tests.json) and pushing commits
• Creating tests from the catalog and configuring guardrails
• Gating CI/CD on eval results
• Debugging failing tests via the Openlayer MCP fix-loop
• Querying projects, pipelines, test results, or looking up Openlayer docs

MCP server

The plugin also connects your agent to the hosted Openlayer MCP server at https://mcp.openlayer.com/mcp. The first time a tool is used, you sign in to Openlayer with OAuth and pick a workspace. The agent can then read projects, data sources, traces, tests, results, and governance rules in that workspace, and create or update them when you ask. Write and delete tools ask for confirmation.

Tool calls go only to Openlayer's API. Nothing is sent anywhere else. See the privacy policy. Self hosted deployments should point the server at their own URL, as the MCP docs describe.

Feedback & Requests

Something not working as expected, or want a new use case covered? Open an issue at https://github.com/openlayer-ai/openlayer-skills/issues or email support@openlayer.com.