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Observability for coding agents

Teams adopting AI coding agents need three things: to see what the agent did, to spend less doing it, or to use the agent to add observability to their own app.

You want to… Use What you get
See what the agent did. Read the conversation, check which tools ran, debug a bad run, share a session with a teammate. Opik tracing, set up per agent Every prompt, response and tool call, grouped into threads you can score, annotate and share.
Spend less doing it. Find where the tokens actually go, per user and per repo, then cut the waste. Cost Intelligence Token counts broken out across system prompt, tools, MCP servers, skills and memory, plus policy controls. Metadata only — never your code or conversations.
Add observability to your own app. Instrument your code, score outputs and run experiments from your coding agent. Opik MCP server uvx opik mcp configure registers the server and the Opik skills with your agent.

Each agent has its own way of getting sessions out. The Quick start column is the single step that does most of the work; the linked page has the full setup, endpoint modes and validation.

Agent Path into Opik Quick start Content captured Cost Intelligence
Claude Code Opik plugin (recommended), or native OTel export (beta) /plugin install opik inside Claude Code Plugin: yes. OTel: redacted unless enabled Supported
GitHub Copilot (VS Code, CLI) Native OTel export github.copilot.chat.otel.enabled: true plus the Opik endpoint Off unless captureContent is enabled Ask your account team
Cursor Opik Cursor extension Install the Opik extension and paste your API key Yes Supported
OpenAI Codex Native OTel export (internal spans and codex.* events only) An [otel.trace_exporter.otlp-http] table in ~/.codex/config.toml No. Prompt text and tokens go to the logs signal, which Opik does not ingest Supported
Other agents (opencode, Gemini CLI, ...) Native OTel export if the agent emits gen_ai.* spans Point the agent's OTLP exporter at the Opik OTel endpoint Depends on the agent Not yet
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