phoenix vs opik-mcp
LLM observability and evaluation tools compared
phoenix is a self-hosted platform for tracing, evaluating, and troubleshooting LLM applications. opik-mcp connects MCP-compatible assistants to an Opik workspace, focusing on selected workspace actions from a coding workflow rather than providing a standalone application observability platform.
phoenix: Observe and Evaluate AI Applications
Arize Phoenix is a self-hosted platform for tracing, evaluating, and troubleshooting LLM applications. It helps AI engineers inspect runtime behavior and test changes to prompts, models, and retrieval.
opik-mcp: Connect AI Assistants to Opik
opik-mcp is a Python MCP server that lets AI coding assistants work with an Opik workspace. Use it to inspect traces, record scores, manage prompts, and explore evaluation data through natural-language workflows.
| phoenix | opik-mcp | |
|---|---|---|
| Language | Python | Python |
| License | NOASSERTION | Apache-2.0 |
| Stars | 11.7k | 220 |
| Forks | 1.2k | 37 |
| Last analyzed | Oct 3, 2026 | Oct 3, 2026 |
Key differences
- phoenix collects OpenTelemetry-based application traces and supports evaluations and experiments; opik-mcp provides assistant access to Opik data and actions such as searching traces, recording scores, and managing prompts.
- phoenix supports work across different frameworks, providers, and programming languages through OpenInference instrumentation; opik-mcp is a Python MCP server for Opik workspaces.
- phoenix can be run locally or deployed in containers or the cloud; opik-mcp offers a local server and can also connect to Opik Cloud's hosted MCP endpoint.
- phoenix metadata reports license `NOASSERTION`, while its README describes Elastic License 2.0; opik-mcp is licensed under Apache-2.0.
- phoenix has 11.7k stars and 1.2k forks; opik-mcp has 220 stars and 37 forks.
- opik-mcp's recommended local setup requires Python 3.13 or newer and uses `uvx`; phoenix's deployment considerations focus on choosing and operating a self-hosted environment.
Choose phoenix if you…
- need application-level tracing and troubleshooting across LLM calls, retrieval, or agent workflows.
- want to create datasets and compare prompt, model, or retrieval changes with evaluations and experiments.
- need a self-hosted platform that can be run locally or deployed in containers or the cloud.
Choose opik-mcp if you…
- already use Opik and want an MCP-compatible assistant to inspect workspace data or perform selected actions.
- want to search traces, record scores or comments, and manage prompts from a coding workflow.
- need a local Python MCP server or want to use Opik Cloud's hosted MCP endpoint.
Compare the numbers side by side, or add more projects
This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.