HoneyHive Docs

If you’re using an AI coding agent, give it four kinds of HoneyHive context:

Agent Skills

Reusable HoneyHive workflows your agent can follow.

HoneyHive CLI

Terminal access to HoneyHive resources and API workflows.

Docs MCP Server

Live search across the HoneyHive docs from your agent.

llms.txt

Paste a single URL for full doc context.

Agent Skills

Agent Skills are portable SKILL.md packages that teach coding agents domain-specific workflows. HoneyHive publishes official skills at github.com/honeyhiveai/skills. Use HoneyHive skills when you want an agent to perform a repeatable HoneyHive workflow, such as adding tracing to an LLM app, rather than just answering doc questions.

Install HoneyHive skills

Install GitHub CLI v2.91.0 or later, which includes gh skill, then install all recommended HoneyHive skills:

gh skill install honeyhiveai/skills honeyhive-instrument
gh skill install honeyhiveai/skills honeyhive-evaluate
gh skill install honeyhiveai/skills honeyhive-improve

Set up runtime prerequisites

These skills may ask your agent to run the HoneyHive CLI to validate credentials or inspect traces. Before using them, install the CLI from the HoneyHive CLI docs, then set your API key:

export HH_API_KEY="<your-project-api-key>"

For self-hosted, federated, or non-default deployments, set HH_API_URL to your deployment’s API base URL. Most cloud users can omit it. Validate access with a read-only CLI command:

honeyhive datasets list

HoneyHive recommends installing all three skills together:

honeyhive-instrument helps compatible agents add HoneyHive tracing to LLM, agent, and RAG applications.
honeyhive-evaluate helps agents set up HoneyHive evaluations and experiments.
honeyhive-improve helps agents use HoneyHive traces and evaluation results to improve application behavior.

HoneyHive Skills

Browse available HoneyHive skills and installation notes.

Agent Skills Specification

Learn how SKILL.md packages work across coding agents.

Install all three skills so your agent can instrument, evaluate, and improve HoneyHive-backed applications without switching setup flows.

HoneyHive CLI

The HoneyHive CLI gives coding agents a terminal-native way to inspect and manage HoneyHive resources. Use it when your agent needs to script datasets, runs, projects, or other REST API workflows from your development environment.

HoneyHive CLI

Install the CLI and run your first commands.

CLI Docs Home

Browse the generated command reference.

For example, after setting HH_API_KEY, an agent can inspect recent trace events from the terminal:

honeyhive events search --limit 10

Use the CLI with skills when the agent needs to validate credentials, inspect traces, or automate HoneyHive workflows as part of a code change.

Docs MCP Server

HoneyHive documentation includes a built-in Model Context Protocol (MCP) server. When connected, your AI assistant can search and retrieve HoneyHive docs in real time while generating responses, instead of relying on potentially outdated training data. The HoneyHive docs MCP server is available at:

https://docs.honeyhive.ai/mcp

The server exposes a search_honey_hive_ai_docs tool that performs semantic search across all HoneyHive documentation, returning relevant content with direct links to the source pages. Once connected, you can ask your AI assistant questions about HoneyHive tracing, evaluations, integrations, and more. It searches the documentation directly to provide accurate, current answers.

The docs MCP server indexes both the current (v2) and legacy (v1) documentation. When prompting, tell your agent to use the v2 docs so it pulls from the current SDK and UI references (see Example Prompts).

Cursor

Open Cursor Settings with Cmd + Shift + J (Mac) or Ctrl + Shift + J (Windows/Linux), click Tools & MCP in the sidebar, then click New MCP Server. This opens ~/.cursor/mcp.json. Add:

{
  "mcpServers": {
    "honeyhive-docs": {
      "url": "https://docs.honeyhive.ai/mcp"
    }
  }
}

Use .cursor/mcp.json in your project root instead if you want to commit the config and share it with your team.

Claude Code

Run this command in your terminal to add the server to your current project:

claude mcp add --transport http honeyhive-docs https://docs.honeyhive.ai/mcp

To make it available across all projects, add the --scope user flag:

claude mcp add --transport http honeyhive-docs --scope user https://docs.honeyhive.ai/mcp

VS Code / GitHub Copilot

Add the following to your VS Code MCP settings configuration file (.vscode/mcp.json):

{
  "servers": {
    "honeyhive-docs": {
      "type": "http",
      "url": "https://docs.honeyhive.ai/mcp"
    }
  }
}

Run MCP: Open User Configuration from the Command Palette to register the server across all workspaces instead of a single project.

Windsurf

Add the following to your Windsurf MCP configuration:

{
  "mcpServers": {
    "honeyhive-docs": {
      "url": "https://docs.honeyhive.ai/mcp"
    }
  }
}

Codex CLI

Run this command to register the server in ~/.codex/config.toml:

codex mcp add honeyhive-docs --url https://docs.honeyhive.ai/mcp

The --url flag requires Codex CLI with streamable HTTP support. Upgrade with npm install -g @openai/codex if codex mcp add --url is not recognized.

Claude Desktop

Claude Desktop connects to remote MCP servers through custom connectors in the app, not through claude_desktop_config.json (which only supports local stdio servers).

Open Claude Desktop and go to Settings > Connectors.
Click Add custom connector.
Set the name to honeyhive-docs and the remote MCP server URL to https://docs.honeyhive.ai/mcp, then click Add.

On Team and Enterprise plans, an Owner must first add the connector under Organization settings > Connectors before members can enable it. See Anthropic’s custom connectors guide for details.

ChatGPT

ChatGPT connects to MCP servers through custom connectors:

Go to Settings > Apps & Connectors > Advanced settings and turn on Developer mode.
Return to Settings > Apps & Connectors and click Create.
Fill in a name (e.g. HoneyHive docs) and set the connector URL to https://docs.honeyhive.ai/mcp, then click Create.

Custom connectors with full MCP support are available on ChatGPT Business, Enterprise, and Education plans, and only workspace admins or owners can enable developer mode. See OpenAI’s connector setup guide for details.

llms.txt

The llms.txt file provides a structured overview of HoneyHive documentation optimized for LLM consumption. Include the URL in a prompt to give any AI assistant broad context about HoneyHive’s capabilities.

https://docs.honeyhive.ai/llms.txt

For the full documentation content in a single file:

https://docs.honeyhive.ai/llms-full.txt

For example, you might prompt: “Using the docs at https://docs.honeyhive.ai/llms-full.txt, help me add OpenAI tracing to my Python project.”

When to use Skills, CLI, MCP, or llms.txt

	Agent Skills	HoneyHive CLI	MCP Server	llms.txt
Best for	Repeatable HoneyHive workflows	Terminal actions and automation	Ongoing development and IDE integration	One-off questions and quick context
How it works	Loads reusable `SKILL.md` instructions	Runs `honeyhive` commands	Searches live docs from the agent	Provides a static docs index and links
Setup	Install with `gh skill`	Install CLI and set `HH_API_KEY`	Add server URL to your agent config	Paste a URL
Freshness	Versioned in GitHub	Uses installed CLI version	Always live	Updated on each docs deployment

Page Quick Actions

Every page in the HoneyHive docs has a contextual menu in the top-right corner with shortcuts for AI tools:

Copy as Markdown - paste the full page content directly into any AI assistant
View as Markdown - view the raw markdown source of the page
Open in ChatGPT - open the page in ChatGPT with full context
Open in Claude - open the page in Claude with full context
Connect MCP - connect the docs MCP server to your tool
Add to Cursor - add the docs MCP server directly to Cursor
Add to VS Code - add the docs MCP server directly to VS Code

These actions are useful for quickly sharing context with your AI tool without a full MCP server setup.

Example Prompts

Once you’ve connected HoneyHive to your agent, try these prompts. Scope docs searches to the current (v2) docs so the agent doesn’t pick up pages from the legacy v1 tree.

Install HoneyHive tracing

Install the honeyhive-instrument skill from https://github.com/honeyhiveai/skills,
then use it to instrument this project. Use the HoneyHive v2 docs for
current SDK guidance.

Add OpenAI tracing to a Python project

Search the HoneyHive v2 docs (pages under /v2/) and add OpenAI
tracing to my Python project using OpenInference. Install the
required packages and initialize the HoneyHiveTracer with my
API key.

Inspect HoneyHive from the terminal

Use the HoneyHive CLI docs and my HH_API_KEY environment variable to
inspect recent events for this project.

Set up an experiment with evaluators

Using the HoneyHive v2 docs (pages under /v2/), help me set up
an experiment that runs my RAG pipeline against a dataset and
scores results with a custom Python evaluator.

Build a monitoring dashboard

Search the HoneyHive v2 docs (pages under /v2/) for how to
create a monitoring dashboard that tracks latency, cost, and
error rates for my production LLM application.

Getting Started

Observability

Evaluation

Prompt Management

Administration

Learn More

Use with Coding Agents

Agent Skills

HoneyHive CLI

Docs MCP Server

llms.txt

Agent Skills

Install HoneyHive skills

Set up runtime prerequisites

HoneyHive Skills

Agent Skills Specification

HoneyHive CLI

HoneyHive CLI

CLI Docs Home

Docs MCP Server

Cursor

Claude Code

VS Code / GitHub Copilot

Windsurf

Codex CLI

Claude Desktop

ChatGPT

llms.txt

When to use Skills, CLI, MCP, or llms.txt

Page Quick Actions

Example Prompts

Getting Started

Observability

Evaluation

Prompt Management

Administration

Learn More

Documentation Index

Agent Skills

HoneyHive CLI

Docs MCP Server

llms.txt

​Agent Skills

​Install HoneyHive skills

​Set up runtime prerequisites

HoneyHive Skills

Agent Skills Specification

​HoneyHive CLI

HoneyHive CLI

CLI Docs Home

​Docs MCP Server

​Cursor

​Claude Code

​VS Code / GitHub Copilot

​Windsurf

​Codex CLI

​Claude Desktop

​ChatGPT

​llms.txt

​When to use Skills, CLI, MCP, or llms.txt

​Page Quick Actions

​Example Prompts

Agent Skills

Install HoneyHive skills

Set up runtime prerequisites

HoneyHive CLI

Docs MCP Server

Cursor

Claude Code

VS Code / GitHub Copilot

Windsurf

Codex CLI

Claude Desktop

ChatGPT

llms.txt

When to use Skills, CLI, MCP, or llms.txt

Page Quick Actions

Example Prompts