pulsemcp Safe content atomic mcp-remote

Arize Phoenix

Phoenix MCP Server provides a unified interface to Arize Phoenix's capabilities through the Model Context Protocol. Developed by Arize AI, this TypeScript implementation enables AI assistants to manage prompts, explore datasets, and run experiments against the Phoenix platform. The server exposes tools for creating and iterating on prompts across different LLM providers (OpenAI, Anthropic, Google), working with evaluation datasets, and visualizing experiment results, making it particularly valuable for teams building and evaluating LLM applications who want to leverage Phoenix's observability features through AI assistants.

Cognium trust score

50%

Tier

Unverified

Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately.

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Metadata

Version: 1.0.0
Skill type: atomic
Execution layer: mcp-remote
Category: ai-ml
Source: PulseMCP
Repository: github.com/arize-ai/phoenix/tree/HEAD/js/packages/phoenix-mcp
Author type: human
Updated: 2026-05-27

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MCP

Resolve Arize Phoenix from your agent

Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.

One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.

claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp

Swap --scope user for --scope project to commit it to .mcp.json.

Your client Same endpoint everywhere; only the config key differs. The full list is in the descriptor.

Claude Desktop · Settings → Connectors → Add custom connector

https://api.skillsregistry.net/mcp

Paste the URL as the connector endpoint. No authentication.

ChatGPT · Settings → Connectors → Create (developer mode) → MCP server URL

https://api.skillsregistry.net/mcp

Authentication: none. Works in chat and deep research — the server exposes the connector search and fetch tools.

Codex CLI · ~/.codex/config.toml

[mcp_servers.skillsregistry]
url = "https://api.skillsregistry.net/mcp"