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@arizeai/phoenix-mcp

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by Arize-ai

phoenix-support

Receive expert assistance with tracing AI applications, managing datasets and prompts, and using evals and annotations for Arize Phoenix and OpenInference.

Instructions

Get help with Phoenix and OpenInference.

  • Tracing AI applications via OpenInference and OpenTelemetry

  • Phoenix datasets, experiments, and prompt management

  • Phoenix evals and annotations

Use this tool when you need assistance with Phoenix features, troubleshooting, or best practices.

Expected return: Expert guidance about how to use and integrate Phoenix

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesYour question about Arize Phoenix, OpenInference, or related topics
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided. The description indicates it is a read-only support tool returning expert guidance, which is transparent about its behavior. No misleading statements.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, front-loaded with the main purpose, uses bullet points for topics, and every sentence adds value without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple single-parameter tool with no output schema, the description provides sufficient context: purpose, topics, when to use, and expected return. No gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%. The description repeats the schema's description for the 'query' parameter without adding new meaning, so baseline score of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Get help with Phoenix and OpenInference' and lists specific topics (tracing, datasets, evals). It effectively distinguishes this support tool from sibling tools that perform concrete operations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says 'Use this tool when you need assistance with Phoenix features, troubleshooting, or best practices.' Does not mention when not to use, but the context of sibling tools makes it clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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