The full upstream README, mirrored here for reference. Install config, tool schemas, adoption signals, and an original overview live on the Lusha MCP Plugin listing page.
Find and enrich B2B contacts and companies with verified emails, direct dials, mobile numbers, and real-time buying signals from Lusha — straight from inside your AI assistant.
Supports Codex (plugins), Claude Code (Claude Code CLI / Cowork), Cursor (plugins), VS Code Copilot (GitHub Copilot Chat with MCP), and Gemini CLI (extensions).
Find and enrich
| Skill | What it does |
|---|---|
enrich-contact | Look up any person and get their verified direct and mobile phone numbers, email, and company context |
prospect | Describe your ICP in plain English — get a filtered, enriched lead list with phone numbers revealed |
signal-prospect | Start from a buying signal (funding, hiring surge, job change) and get the right decision makers' phones |
lookalike-prospect | Give Lusha 5+ reference companies or contacts — get a matched list enriched with phone numbers |
Write outreach — a two-stage pair, run in order
| Skill | What it does |
|---|---|
outreach-research | Stage 1. Capture what you sell, to whom, and how you differentiate as a portable positioning brief (lusha-outreach-brief.md). Text only — makes no Lusha API calls |
outreach-sequence | Stage 2. Turn that brief plus a contact list into personalized, signal-grounded Email 1 (optionally E2/E3 and LinkedIn), handoff-ready as flat CSV |
The find-and-enrich skills each chain multiple Lusha API calls into a complete workflow, and surface verified phone numbers prominently — direct lines and mobile numbers are first-class outputs, not an afterthought.
The outreach pair sits on top of them. outreach-research is pure conversation, producing a brief you save and reuse. outreach-sequence consumes that brief and never calls Lusha directly: it delegates signal discovery and harvest to signal-prospect, and contact enrichment to enrich-contact, so credit handling stays in one place. Every call it triggers is tagged with a reason_for_invocation starting outreach-sequence: , which is how skill-driven usage is attributed.
All clients load the same skills/*/SKILL.md files and the same Lusha MCP server — only the per-client manifest and store endpoint differ:
| Client | Manifest | MCP endpoint | How to invoke |
|---|---|---|---|
| Codex | .codex-plugin/plugin.json + mcp.json | mcp.lusha.com/mcp/codex | Skills activate from natural language requests |
| Claude Code | .claude-plugin/plugin.json | mcp.lusha.com/mcp/claude | /enrich-contact, /prospect, etc. |
| Cursor | .cursor-plugin/plugin.json | mcp.lusha.com/mcp/cursor | Skills activate from natural language requests |
| VS Code Copilot | .github/plugin/plugin.json | mcp.lusha.com/mcp/copilot | /enrich-contact, /prospect, etc. |
| Gemini CLI | gemini-extension.json | mcp.lusha.com/mcp/gemini | Gemini activates the matching skill on demand |
Skills reference Lusha tools by their bare logical name (e.g. contacts_search), so a single skill source works identically across all clients. Gemini CLI auto-discovers the bundled skills/ directory as extension skills.
The Codex plugin lives at the repo root — .codex-plugin/plugin.json (manifest) and mcp.json (MCP server), with skills: "./skills/" pointing at the shared root skills/. Codex discovers it through the repo marketplace catalog at .agents/plugins/marketplace.json, which uses a url source pinned to a branch/tag. That catalog is read only by Codex/OpenAI tooling — Claude, Copilot, and Gemini keep using their own provider-specific manifests.
A
urlsource is used instead of alocalpath because Codex rejects a local plugin path that resolves to the repo root (codex#17066) and silently drops symlinks during install (codex#18863). Cloning the repo overurlkeepsskills/as real files at the plugin root, so no copy or symlink is needed.
Add the marketplace and install:
Select Lusha Plugins, install the Lusha plugin, then start a new Codex thread so the skills and MCP tools are loaded. The url source installs from the ref pinned in .agents/plugins/marketplace.json, so changes take effect once they land on that ref.
Cursor reads the plugin manifest at .cursor-plugin/plugin.json and discovers the bundled skills/ automatically. Add the repo as a plugin marketplace, then install the Lusha plugin from .cursor-plugin/marketplace.json (catalog lusha-plugins, plugin lusha). All six skills activate from natural-language requests once the MCP server connects.
Requires a VS Code version with agent-plugin support and the GitHub Copilot extension. The plugin bundles the MCP server and all skills together via .github/plugin/plugin.json.
Cmd+Shift+P / Ctrl+Shift+P).lusha-oss/lusha-mcp-plugin.The Lusha MCP server and all six skills load automatically. Invoke a skill from Copilot Chat with /enrich-contact, /prospect, /signal-prospect, /lookalike-prospect, /outreach-research, or /outreach-sequence.
The repo ships a gemini-extension.json manifest at its root, so Gemini CLI wires up the Lusha MCP server and discovers the bundled skills automatically.
All six skills are registered as extension skills — Gemini activates the matching one on demand (e.g. when you ask it to find a contact's phone number, build a prospect list, or draft outreach). Run gemini skills list to confirm they loaded.
The Lusha MCP server uses OAuth. The first time you invoke a Lusha skill or tool, you'll be prompted to sign in with your Lusha account. Subsequent calls reuse the authenticated session.
Skills are designed to feed into each other:
prospect → signal-prospect: build a list, then filter it to companies showing buying signalslookalike-prospect → signal-prospect: find lookalikes, then prioritize by signalenrich-contact → lookalike-prospect: enrich a single contact, then find similar peopleoutreach-research → outreach-sequence: capture positioning once, then draft against itprospect → outreach-sequence: hand a lead list straight into drafting (optional — any CSV with full_name, company, and title works)outreach-sequence requires a brief from outreach-research; without one it refuses to draft rather than inventing positioning. An audience is required too, but it can come from anywhere: a pasted CSV, an attached file, a single named contact, or a prospect handoff.
outreach-sequence runs in two modes, set out in its Execution Mode section:
"non-interactive", "headless", "automated run", or "no user is available to answer"), as an automation runner or scheduled job would. Every question resolves from a supplied value or a documented default and execution continues, because an emitted question would become the final output and the run would produce nothing.Automated mode never relaxes the data rules: the brief and audience stay hard-required, signal and enrichment work still delegates to the other skills, and nothing may be fabricated to fill a gap.
Root skills/ is the single source of truth — every client (Codex, Claude, Copilot, Gemini) reads these same files, so edit skills only under skills/.
When releasing, update the ref in .agents/plugins/marketplace.json to the branch or tag Codex users should install from (e.g. master for production, or a feature branch while testing).