@Prompthub/

MCP server for PromptHub. Publish, fetch, list, update and search prompt repositories from Claude Code or Codex.

1. Get a token

Sign in at https://www.awesome-prompt.com → Settings → API tokens → create a token. Copy the ph_… value (shown once).

2. Configure

Either set an environment variable:

export PROMPTHUB_TOKEN=ph_xxx
# optional, defaults to https://www.awesome-prompt.com
export PROMPTHUB_BASE_URL=https://www.awesome-prompt.com
# optional — force which model search/recommend/publishing prefer (a registry slug,
# e.g. claude-sonnet-4-6). Overrides host auto-detection; handy for multi-model hosts.
export PROMPTHUB_MODEL=claude-sonnet-4-6

…or create ~/.prompthub/config.json:

{ "token": "ph_xxx", "baseUrl": "https://www.awesome-prompt.com", "model": "claude-sonnet-4-6" }

Environment variables take precedence over the file.

3. Register the server

The server installs straight from this public GitHub repo — no npm registry, no token to pull it.

Recommended — install once, then point at the prompthub-mcp binary (fast startup; builds on install):

npm i -g github:LionelHao/prompthub-mcp
claude mcp add prompthub --env PROMPTHUB_TOKEN=ph_xxx -- prompthub-mcp

Zero-install alternative — let npx fetch + build the repo on demand (slower cold start, always tracks main):

claude mcp add prompthub --env PROMPTHUB_TOKEN=ph_xxx -- npx -y github:LionelHao/prompthub-mcp

Codex — add to ~/.codex/config.toml. After npm i -g github:LionelHao/prompthub-mcp:

[mcp_servers.prompthub]
command = "prompthub-mcp"
env = { PROMPTHUB_TOKEN = "ph_xxx" }

Or zero-install (npx fetches + builds on demand):

[mcp_servers.prompthub]
command = "npx"
args = ["-y", "github:LionelHao/prompthub-mcp"]
env = { PROMPTHUB_TOKEN = "ph_xxx" }

4. Tools

Tool	What it does
prompthub_whoami	Verify the token; show your handle/name
prompthub_search	Search public repos by keyword (model-aware — see below)
prompthub_recommend	Recommend high-usage repos for a task (model-aware)
prompthub_get_repo	Fetch one repo (owner/name) with its file tree
prompthub_list_repos	List your repos, or a user's public repos
prompthub_create_repo	Create a repo from explicit fields
prompthub_update_repo	Full-replace one of your repos
prompthub_publish_session	Distill the current session into a reusable repo and publish
prompthub_describe_file_format	Show the exact files[] JSON shapes (text/conversation/workflow)
prompthub_describe_runner_protocol	Read the complete bundled Workflow Runner Contract (no token or network)

Authoring workflows and runtime runs

PromptHub uses “workflow” at two distinct layers:

• An authoring workflow is the reusable static DAG stored in a repository as a workflow file. The repo create/get/update/publish tools work with this authoring format.
• The Workflow Runner Contract governs an agent executing a local run package generated by PromptHub Desktop: frozen blueprint.json, append-only events.jsonl, and artifacts/.

The canonical public Runner Contract lives in the prompt-hub repository. This package ships a byte-identical, hash-pinned read-only mirror under docs/contracts/workflow-runner/. Any MCP host can call prompthub_describe_runner_protocol without a PromptHub token or network access to read the full human-readable contract, including compatibility, preflight, lifecycle, resume, rerun, and safety rules.

The MCP server only describes this runtime contract. It does not create or execute run packages, write events, monitor Desktop sessions, or make chat-only hosts compatible with local filesystem execution.

Model-aware search & publishing

The server detects which AI model you're working with and tailors results to it — no setup needed:

• Detection — inferred from the MCP host (clientInfo): Claude Code → claude-sonnet-4-6, Codex → gpt-5-5. Priority: per-call model arg > PROMPTHUB_MODEL env > host. Unknown / multi-model hosts (e.g. Cursor) fall back to PROMPTHUB_MODEL.
• Search & recommend — prompthub_search / prompthub_recommend rank prompts tagged for your model first — a preference, not a filter (model-agnostic prompts still appear). Results carry an appliedModel field + a short note to relay to the user.
• Publishing — prompthub_create_repo / prompthub_publish_session / prompthub_update_repo auto-tag your prompt's text nodes with the current model (only nodes without an explicit model; image/video nodes are left untouched). The reply notes how many nodes were tagged.
• Override anytime — tell the assistant "find Gemini prompts" (per-call model), or set PROMPTHUB_MODEL. Run prompthub_whoami to see the detected host + resolved model.

Model slugs/labels come from the live registry at GET /api/v1/models.

5. First run

Confirm it's wired up — ask your assistant:

"Use prompthub_whoami to check my PromptHub login."

You should see your handle. Then publish:

"Publish the prompt we just wrote to PromptHub as a private repo called my-first-prompt."

The assistant will call prompthub_publish_session and reply with the new repo URL (e.g. https://www.awesome-prompt.com/@you/my-first-prompt). If it's unsure of the format, it can call prompthub_describe_file_format first.

Organize a prompt before publishing

prompthub_organize_prompt（无参，无需令牌）取回「整理提示词」方法论：把原始 prompt 重写得更清晰， 并按 PromptHub 的 {{变量}} 规范模板化，便于他人编辑替换。发布前先调它，再用 create_repo / publish_session 发布。

作为 Claude Code plugin 安装

本仓同时是 Claude Code plugin（声明了 MCP server + 原生 prompt-organize skill）：

claude --plugin-dir /path/to/prompthub-mcp   # 本地
# 或 /plugin install <git-url>

更新方法论文本后，重新生成 SKILL.md：

PROMPTHUB_BASE_URL=https://www.awesome-prompt.com npm run sync-skill

License

MIT