by comet-ml
Model Context Protocol (MCP) server for Opik, the open-source LLM observability and evaluation platform, built by Comet. Read traces, log scores, and manage prompts from Claude Code, Cursor, or VS Code.
# Add to your Claude Code skills
git clone https://github.com/comet-ml/opik-mcpGuides for using mcp servers skills like opik-mcp.
Last scanned: 5/30/2026
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"issues": [],
"status": "PASSED",
"scannedAt": "2026-05-30T15:37:48.474Z",
"npmAuditRan": true,
"pipAuditRan": true
}opik-mcp is an open-source mcp servers skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by comet-ml. Model Context Protocol (MCP) server for Opik, the open-source LLM observability and evaluation platform, built by Comet. Read traces, log scores, and manage prompts from Claude Code, Cursor, or VS Code. It has 217 GitHub stars.
Yes. opik-mcp passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/comet-ml/opik-mcp" and add it to your Claude Code skills directory (see the Installation section above).
opik-mcp is primarily written in Python. It is open-source under comet-ml on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other MCP Servers skills you can browse and compare side by side. Open the MCP Servers category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh opik-mcp against similar tools.
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⚠️ Third-Party Software Notice
This skill is third-party open-source software developed and hosted independently on GitHub. SkillsLLM is an informational directory and does not control or maintain the underlying repository.
Any security checks, ratings, or warnings displayed by SkillsLLM are automated and limited in scope. They do not constitute a security certification or guarantee that the software is safe, error-free, or free from malicious code, vulnerabilities, compromised dependencies, or prompt-injection risks.
Review the source code, permissions, dependencies, and configuration before installing or running any third-party skill. Use is at your own risk. To the maximum extent permitted by applicable law, SkillsLLM is not liable for losses arising from third-party software.
The official Model Context Protocol (MCP) server for Opik, the open-source LLM observability and evaluation platform, built by Comet. Plug your AI host (Claude Code, Cursor, VS Code Copilot, MCP Inspector) directly into your Opik workspace: read traces, log scores, save prompt versions, and ask Ollie, Opik's in-product AI assistant, investigative questions, all from the chat.
Built for LLM engineers who already run Opik and want to drive it from the same AI assistant they code with.
Migrating from the old
npx opik-mcp? The TypeScript server is deprecated and sunsets on 2026-11-15. Swapnpx -y opik-mcpforuvx opik-mcp@latestin your MCP client config. Full guide:legacy/typescript/MIGRATION.md.
You: "Why did the experiment 'gpt-4o-rerank-v3' regress on factuality?"
Claude: → ask_ollie → reads experiment + traces → "Three traces failed because…"
You: "Score trace 7f2e… 0.9 on helpfulness with reason 'great recovery'."
Claude: → write(score.create) → done
opik-mcp is a Python package (requires Python 3.13+). The recommended way to
run it is uvx, which fetches and runs the latest published version on demand —
no global install, no virtualenv juggling.
Install uv once:
curl -LsSf https://astral.sh/uv/install.sh | sh # macOS / Linux
# or: brew install uv
You'll need two things from your Opik workspace:
OPIK_API_KEY — get it from comet.com/api/my/settings/.OPIK_WORKSPACE — your workspace name (lowercase, as it appears in the URL). E.g. https://www.comet.com/acme-ai/... → OPIK_WORKSPACE=acme-ai. COMET_WORKSPACE is accepted as a deprecated alias.Cloud, with an API key: set it unless your account default is the one you want. Left out, the server sends
default, which Comet resolves to your account's default workspace. That works, but if you actually work in a named workspace you will be pointed at a different one with nothing to tell you — your reads come back from the wrong place rather than failing.Cloud, over OAuth: leave it unset. The workspace comes from the token you authorized, and the server ignores this setting entirely.
Local / open source: leave it unset. Open source Opik has a single workspace named
defaultand no way to create others, which is exactly what the fallback gives you.Self-hosted Comet: set it. Unlike open source, these deployments have real named workspaces, and the same silent-wrong-workspace risk applies.
Whichever applies, make sure the value is actually substituted. Snippets in the wild ship placeholders like
<your-workspace>or${input:OPIK_WORKSPACE}; pasted as-is, those are not workspace names. The server now refuses them outright rather than letting the backend answer with an auth error that explains nothing.
Add the server with one command:
claude mcp add --transport stdio opik-mcp \
--env OPIK_API_KEY=<your-key> \
--env OPIK_WORKSPACE=<your-workspace> \
-- uvx opik-mcp
Or edit ~/.claude.json directly:
{
"mcpServers": {
"opik-mcp": {
"type": "stdio",
"command": "uvx",
"args": ["opik-mcp"],
"env": {
"OPIK_API_KEY": "<your-key>",
"OPIK_WORKSPACE": "<your-workspace>"
}
}
}
}
Restart Claude Code. Verify with /mcp — opik-mcp should appear as connected.
Then, in the chat, ask: "list my Opik projects" — Claude will call the list
tool and you'll see your workspace's projects.
Edit ~/.cursor/mcp.json (global) or .cursor/mcp.json (project), or open
Cmd+Shift+J → Features → Model Context Protocol:
{
"mcpServers": {
"opik-mcp": {
"type": "stdio",
"command": "uvx",
"args": ["opik-mcp"],
"env": {
"OPIK_API_KEY": "<your-key>",
"OPIK_WORKSPACE": "<your-workspace>"
}
}
}
}
Reload Cursor; the green dot next to opik-mcp in the MCP panel confirms the
connection. Ask in chat: "list my Opik projects".
Cursor 60s timeout. Cursor enforces a hard tool-call timeout that doesn't reset on progress notifications. Long
ask_ollieturns will fail on Cursor. See Known host limits.
.vscode/mcp.json in your workspace (or User Settings JSON):
{
"servers": {
"opik-mcp": {
"type": "stdio",
"command": "uvx",
"args": ["opik-mcp"],
"env": {
"OPIK_API_KEY": "<your-key>",
"OPIK_WORKSPACE": "<your-workspace>"
}
}
}
}
Reload the window; the Copilot Chat MCP indicator shows opik-mcp once
the server is reachable. Ask in chat: "list my Opik projects".
OPIK_API_KEY=<your-key> OPIK_WORKSPACE=<your-workspace> \
npx @modelcontextprotocol/inspector uvx opik-mcp
Add COMET_URL_OVERRIDE (and OPIK_URL if Opik lives at a non-default path) to
the same env block in your host config:
{
"mcpServers": {
"opik-mcp": {
"type": "stdio",
"command": "uvx",
"args": ["opik-mcp"],
"env": {
"OPIK_API_KEY": "<your-key>",
"OPIK_WORKSPACE": "<your-workspace>",
"COMET_URL_OVERRIDE": "https://opik.your-company.com",
"OPIK_MCP_ANALYTICS_SOURCE": ""
}
}
}
}
Omit OPIK_WORKSPACE on an open-source deployment, where default is the only
workspace; keep it on a self-hosted Comet, which has real named ones.
ask_ollie and run_experiment are available on Comet Cloud only — on
self-hosted those calls will fail at dispatch, so use read / list / write
directly. Setting OPIK_MCP_ANALYTICS_SOURCE="" opts your install out of the
cloud-Comet source label on telemetry events.
opik-mcp exposes a small, outcome-oriented surface — six tools that cover
the full lifecycle (read → annotate → curate → author → iterate).
| Tool | Purpose |
|---|---|
read |
Universal read by id / name / opik:// URI |
list |
Universal list with optional name filter + pagination |
ask_ollie |
Investigate / synthesize via the Opik in-product assistant |
write |
Universal write — log traces/spans, score, comment, save prompts, manage test suites & experiments |
schema |
Introspect write-operation schemas (used by the LLM to construct valid payloads) |
run_experiment |
Run an evaluation experiment end-to-end via Ollie |
readOne tool for any "show me X" question. Takes an entity_type plus an id
(UUID or, for nameable types, a name) or a full opik:// URI. Composite reads
(trace, prompt) inline their children so a single call returns the full
picture.
Supported entities: project, trace, span, test_suite, experiment,
prompt. Name-based lookup is available for project, experiment, prompt,
test_suite (slower — two API calls — and may return multiple matches).
read(entity_type="trace", id="7f2e3c8a-…")
read(entity_type="project", id="demo") # name lookup
read(entity_type="trace", id="opik://traces/7f2e3c8a-…")
listBrowse a collection with optional name filter and pagination. Project-scoped
types (trace, test_suite_item, prompt_version) require their parent UUID.
list(entity_type="experiment", page=1, size=25)
list(entity_type="experiment", name="rerank") # name substring filter
list(entity_type="trace", project_id="<project-uuid>") # traces of one project
ask_ollieFor investigative questions, cross-entity synthesis, or anything that needs Opik domain expertise. Ollie has direct read access to your workspace and can execute writes (scores, comments, test-suite items, prompt versions) mid-stream when asked.
ask_ollie(query="Why are spans in project 'demo' slower this week than last?")
ask_ollie(query="Compare experiments A and B on factuality. Score the bottom 5 traces of A 0.2 with reason.")
Returns the assistant's final text plus a thread_id. Pass it back on
follow-ups to preserve context — Ollie has no memory across threads.
YOLO mode (default). Writes Ollie performs mid-stream execute without a
per-action confirmation. Each auto-approval is logged as a JSON audit row on
the opik_mcp.audit Python logger. To require confirmation instead, set
OPIK_MCP_AUTO_APPROVE=disabled — Ollie's confirm requests then surface as
typed errors you can manually re-issue.
Available on Comet Cloud only.
writeUniversal write dispatcher. Pass operation + data and the dispatcher
validates the payload, applies the right REST verb, and returns the
backend response.
Operations:
| Operation | What it does |
|---|---|
trace.create |
Log a single trace (or a batch). Parent for spans / scores / comments. |
trace.update |
Finalize or amend an existing trace. |
span.create |
Log a span on an existing trace (or a batch). |
score.create |
Attach a numeric feedback score to a trace, span, or thread. |
comment.create |
Attach a free-text comment to a trace, span, or thread. |
prompt_version.save |
Save a new prompt version (creates the prompt by name if missing). |
test_suite.create |
Create an evaluation test suite. |
test_suite_item.upsert |
Upsert items into a test suite (always the envelope shape). |
experiment.create |
Create an experiment scoped to a test suite. |
experiment_item.create |
Attach trace + dataset_item rows to an experiment. |
write(operation="score.create", data={
"target": "trace",
"target_id": "7f2e3c8a-…",
"name": "helpfulness",
"value": 0.9,
"reason": "great recovery"
})