name	configure-zymtrace-mcp
description	Use when connecting a coding agent — Claude Code, OpenAI Codex, or Cursor — to the zymtrace MCP server so the user can analyze CPU and GPU flamegraphs through natural-language queries. Walks through finding the gateway URL, generating an auth token (if service-token auth is on), adding the server with the right command for the user's client, and verifying the connection. This skill is plumbing only — the analytical workflow lives in `optimize-cpu-workloads` and `optimize-gpu-workloads`. Trigger phrases: "connect zymtrace MCP", "set up zymtrace MCP", "configure zymtrace MCP", "add zymtrace to /mcp", "connect Claude/Codex/Cursor to zymtrace", "/mcp doesn't show zymtrace", "zymtrace MCP token", "Cursor zymtrace integration", "set up the zymtrace AI assistant".

name

configure-zymtrace-mcp

description

Use when connecting a coding agent — Claude Code, OpenAI Codex, or Cursor — to the zymtrace MCP server so the user can analyze CPU and GPU flamegraphs through natural-language queries. Walks through finding the gateway URL, generating an auth token (if service-token auth is on), adding the server with the right command for the user's client, and verifying the connection. This skill is plumbing only — the analytical workflow lives in `optimize-cpu-workloads` and `optimize-gpu-workloads`. Trigger phrases: "connect zymtrace MCP", "set up zymtrace MCP", "configure zymtrace MCP", "add zymtrace to /mcp", "connect Claude/Codex/Cursor to zymtrace", "/mcp doesn't show zymtrace", "zymtrace MCP token", "Cursor zymtrace integration", "set up the zymtrace AI assistant".

Configure zymtrace MCP

Helps the user connect their coding agent — Claude Code, OpenAI Codex, or Cursor — to their zymtrace backend's MCP server. Once connected, the user can analyze their CPU and GPU flamegraphs with natural-language queries — see optimize-cpu-workloads (CPU-only) or optimize-gpu-workloads (GPU) for the analytical workflow.

The MCP server is part of the zymtrace backend itself — it lives at <gateway-host>/mcp. If the backend isn't installed and reachable yet, route to install-zymtrace-backend and expose-zymtrace-backend first.

Which client? The URL, token, and reachability steps are identical for every client; only the add-the-server command differs (Step 3–4). Detect the client from context — which agent is running this, or what the user says ("connect Codex", "Cursor") — and use that client's block. If unsure, ask: "Claude Code, Codex, or Cursor?"

Greet the user

👋 Let's connect your agent to the zymtrace MCP so you can analyze flamegraphs in natural language. I'll need your zymtrace URL and — if your install has service-token auth on — a token. Five minutes max.

Doc reference: https://docs.zymtrace.com/mcp/configure-mcp

Skip the greeting if the user has already volunteered the URL and token.

Sources of truth

MCP configuration: https://docs.zymtrace.com/mcp/configure-mcp
Service tokens (auth): https://docs.zymtrace.com/authentication/service-tokens
MCP overview: https://docs.zymtrace.com/mcp

Pre-flight

Check whether zymtrace is already connected in the user's client:

Client	Check
Claude Code	`claude mcp list 2>&1 \| head -20` (and `claude --version` — older than v2.x: MCP support varies, recommend updating)
Codex	`codex mcp list 2>&1 \| head -20`
Cursor	open `~/.cursor/mcp.json` (or project `.cursor/mcp.json`); or Settings → MCP/Tools

If zymtrace already appears, the connection exists — jump straight to verification (Step 5).

Pre-resolve what you can

Variable	Resolve by
Backend gateway URL	Ask the user. Typically `https://zymtrace.<their-domain>` or the ALB / Ingress hostname. If installed in-cluster only, see "Port-forward fallback" below.
MCP endpoint	`<gateway-url>/mcp` — append `/mcp` to whatever they give you.
Auth required?	If the backend has `auth.serviceToken.enabled: true` (check with `kubectl get cm -n <NS> -o yaml \| grep -i serviceToken`), the user needs a token. Otherwise skip.
Existing MCP servers	the client's MCP list (Pre-flight table) — to avoid name collision.

Things you must ask:

The zymtrace URL (don't guess).
Which client they're connecting (Claude Code / Codex / Cursor), if not already clear.
For Claude Code / Codex: user scope (global) or project scope (just this repo).

Decision: auth or no auth?

Backend setting	What's needed
`auth.serviceToken.enabled: false` (default)	No token. Connection is open within the network that can reach the gateway.
`auth.serviceToken.enabled: true`	Token required. Ask the user to generate a service token in the zymtrace UI: Settings → Service Tokens → New Token. Full doc: https://docs.zymtrace.com/authentication/service-tokens.

For production exposures behind ALB / NGINX / mTLS, service-token auth is recommended.

Standard flow

Step 1: Confirm reachability

Claude runs

curl -fsI <gateway-url>/health 2>&1 | head -3

Should return HTTP 200/204. If unreachable → the gateway isn't exposed externally; route to expose-zymtrace-backend or use the port-forward fallback below.

Step 2: Generate a token (only if service-token auth is enabled)

If the MCP (or the REST API) requires authentication, ask the user to generate a zymtrace service token — the skill never creates or sees it. Reference: https://docs.zymtrace.com/authentication/service-tokens.

What you need to do in a terminal (user-driven)

The token is generated through the zymtrace UI, not by this skill:

Open the zymtrace UI: <gateway-url> (e.g. https://zymtrace.acme.com).
Settings → Service Tokens → New Token.
Scope it to mcp (or whatever scope the org uses).
Copy the token immediately — it's shown once. Store it in your password manager or $ZYMTRACE_MCP_TOKEN env var.

If your install doesn't have service-token auth on, skip this step.

Step 3: Confirm with the user before running

Print the exact command/edit for their client (Step 4) and wait for explicit confirmation. In every case the token stays in an env var the user exports first ($ZYMTRACE_MCP_TOKEN) — never inline the literal token in the conversation or in files.

Step 4: Add the MCP server — pick the user's client

The user runs/edits this themselves (the token is in their env, not the skill's). Replace <gateway-url> with their URL; drop the auth header/line entirely if service-token auth is off.

Claude Code

export ZYMTRACE_MCP_TOKEN="<paste-token>"   # only if auth is on
claude mcp add zymtrace --transport http <gateway-url>/mcp \
  --header "Authorization: Bearer $ZYMTRACE_MCP_TOKEN"   # drop this line if auth is off

For project scope instead of user scope, add --scope project (config lands in .claude/settings.json).

OpenAI Codex

export ZYMTRACE_MCP_TOKEN="<paste-token>"   # only if auth is on
codex mcp add zymtrace --url <gateway-url>/mcp \
  --bearer-token-env-var ZYMTRACE_MCP_TOKEN   # drop this line if auth is off

Codex stores it as a streamable_http server in ~/.codex/config.toml.

Cursor — no CLI; add an entry to ~/.cursor/mcp.json (global) or .cursor/mcp.json (this project):

{
  "mcpServers": {
    "zymtrace": {
      "url": "https://<gateway-url>/mcp",
      "headers": { "Authorization": "Bearer ${env:ZYMTRACE_MCP_TOKEN}" }
    }
  }
}

Drop the "headers" field entirely if auth is off. Cursor resolves ${env:ZYMTRACE_MCP_TOKEN} from the environment, so the literal token still never lands in the file.

Step 5: Verify

Confirm the server is registered in the user's client:

Client	Verify
Claude Code	`claude mcp list \| grep -i zymtrace` → `Connected`; in a fresh session `/mcp` lists `zymtrace`.
Codex	`codex mcp list \| grep -i zymtrace`; restart Codex and confirm zymtrace appears in `/mcp`.
Cursor	Settings → MCP/Tools shows `zymtrace` with a green/active indicator.

Quick functional test (any client), in a new session:

"Using zymtrace MCP, list the top 5 hottest CPU functions from the last 1 hour."

If it returns data, the connection works. unauthorized → token wrong, regenerate. connection refused → URL wrong or unreachable.

Step 6: Hand off

Direct the user to the analytical workflow — optimize-cpu-workloads for CPU-only deployments, optimize-gpu-workloads for GPU workloads (it adds the GPU↔CPU cross-view and inference-server pattern catalogues), or optimize-memory-allocation for JVM memory-allocation / GC analysis (Java only). That's where the connected MCP actually gets used.

Optional: pair with the GitHub MCP for code-level fixes

If the user also connects the GitHub MCP, Claude can pair the flamegraph analysis with the actual codebase — locating the hot function in their repo and proposing a specific edit (PR-ready), not just a generic recommendation.

What you need to do in a terminal

Add the GitHub MCP (https://api.githubcopilot.com/mcp/, bearer $GITHUB_TOKEN) with the same Step 4 mechanism as your client — e.g. Claude Code:

claude mcp add github --transport http https://api.githubcopilot.com/mcp/ \
  --header "Authorization: Bearer $GITHUB_TOKEN"

(Codex: codex mcp add github --url https://api.githubcopilot.com/mcp/ --bearer-token-env-var GITHUB_TOKEN; Cursor: a second entry in mcp.json.)

Then in a session: "Analyze my GPU workload over the last hour, use the github MCP to find the code path in myorg/myrepo, and suggest a fix." The agent pulls the flamegraph from zymtrace, locates the hot frame in the repo via GitHub MCP, and proposes the edit. The two MCPs compose without any extra configuration on the skill side.

Optional: fewer approval prompts during analysis

Once connected, the analysis skills and the zymtrace-perf-engineer agent pull profiles, search your repo, and apply fixes — so the client prompts you to approve each tool call unless you've pre-approved it. That per-call prompting is the client's permission system, not the skill or agent (the agent is already written to run end to end without checkpointing). To let an investigation run without confirming every step:

Claude Code — allow-list the tools in ~/.claude/settings.json (all projects) or .claude/settings.json (one repo):

{
  "permissions": {
    "allow": ["mcp__zymtrace", "Read", "Grep", "Glob", "Edit", "Write"]
  }
}

This pre-approves the MCP data pulls, source search, and the fix edit. Keep Bash off the allow-list (or scope it, e.g. "Bash(git diff *)") so arbitrary shell — like a "run it to benchmark" step — still prompts. Alternatives without editing settings: press Shift+Tab to switch the session to accept-edits mode, or choose "Yes, and don't ask again" the first time each prompt appears (it writes the rule for you). For a fully unattended run in a sandbox only, claude --dangerously-skip-permissions bypasses every check — never on a machine with real credentials or prod access.

Codex / Cursor — approval is governed by the app's own trust settings (Codex approval mode, Cursor's tool-approval toggles), not a file edited here; raise the workspace trust level to reduce prompts.

Port-forward fallback (for in-cluster-only gateways)

If the gateway has no external exposure (still ClusterIP), the user can MCP through a port-forward.

What you need to do in a terminal

kubectl port-forward -n <backend-NS> svc/<PREFIX>-gateway 8080:80
# Leave this running, then add http://localhost:8080/mcp via your client's Step 4 command
# (Claude: claude mcp add … http://localhost:8080/mcp; Codex: codex mcp add … --url http://localhost:8080/mcp;
#  Cursor: "url": "http://localhost:8080/mcp" in mcp.json). Auth is usually off for a local port-forward.

This is fine for dev / one-off investigations. For team-wide use, run expose-zymtrace-backend to give the gateway a real hostname.

Done

The client's MCP list (Step 5) shows zymtrace connected.
A test query (e.g. "list top 5 hottest CPU functions in the last hour") returns data.

If both check, hand off to optimize-cpu-workloads (CPU-only), optimize-gpu-workloads (GPU), or optimize-memory-allocation (JVM memory/GC).

Common pitfalls

zymtrace doesn't appear after adding it → wrong scope or stale session. Claude Code: if you used --scope project, it only shows in that repo — re-add with --scope user (or no flag). Codex/Cursor: restart the app so it re-reads the config.
unauthorized on every query → token wrong, scoped wrong, or expired. Regenerate in Settings → Service Tokens.
connection refused → gateway URL typo, missing /mcp suffix, or backend not exposed externally. Test with curl -I <gateway-url>/health first.
Mixed Content in browser when testing UI on HTTP gateway → use HTTPS via expose-zymtrace-backend. MCP can stay on the same URL.
Token committed to a values file or pasted into the session → revoke it in the UI immediately and re-issue. Tokens belong only in env vars or password managers.

Security constraints

Never inline the MCP token in the conversation, values files, scripts, commits, mcp.json, or any MCP-add command arguments. Always reference an env var ($ZYMTRACE_MCP_TOKEN, or ${env:ZYMTRACE_MCP_TOKEN} in Cursor's mcp.json) the user exports.
Never generate, copy, or store the token on the user's behalf — the user pastes it once into their shell or password manager; the skill never sees it.
Never add the server for them (run the CLI command or edit mcp.json) without explicit confirmation of the exact command/edit + gateway URL.
Never suggest disabling auth as a "fix" for an auth error. The fix is a valid token, not less security.
Never declare the connection done without verifying via the client's MCP list (Step 5).

Navigation Menu

Uh oh!

Configure zymtrace MCP

Greet the user

Sources of truth

Pre-flight

Pre-resolve what you can

Decision: auth or no auth?

Standard flow

Step 1: Confirm reachability

Claude runs

Step 2: Generate a token (only if service-token auth is enabled)

What you need to do in a terminal (user-driven)

Step 3: Confirm with the user before running

Step 4: Add the MCP server — pick the user's client

Step 5: Verify

Step 6: Hand off

Optional: pair with the GitHub MCP for code-level fixes

What you need to do in a terminal

Optional: fewer approval prompts during analysis

Port-forward fallback (for in-cluster-only gateways)

What you need to do in a terminal

Done

Common pitfalls

Security constraints

Uh oh!

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SKILL.md

Latest commit

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SKILL.md

File metadata and controls

Configure zymtrace MCP

Greet the user

Sources of truth

Pre-flight

Pre-resolve what you can

Decision: auth or no auth?

Standard flow

Step 1: Confirm reachability

Claude runs

Step 2: Generate a token (only if service-token auth is enabled)

What you need to do in a terminal (user-driven)

Step 3: Confirm with the user before running

Step 4: Add the MCP server — pick the user's client

Step 5: Verify

Step 6: Hand off

Optional: pair with the GitHub MCP for code-level fixes

What you need to do in a terminal

Optional: fewer approval prompts during analysis

Port-forward fallback (for in-cluster-only gateways)

What you need to do in a terminal

Done

Common pitfalls

Security constraints