lessie

# Lessie — People Search & Enrichment ## Setup Lessie supports two modes: **CLI** (default, recommended) and **MCP Server**. ### Mode A: CLI (default) Install the Lessie CLI binary: ```bash npm install -g @lessie/cli ``` Or use without installing: ```bash npx @lessie/cli --version ``` First-time authorization: ```bash lessie auth ``` This opens a browser for login/registration. Token is cached at `~/.lessie/oauth.json`. Verify connection: ```bash lessie status ``` ### Mode B: MCP Server Add to your MCP config (Claude Code `~/.claude/mcp.json`, Cursor `~/.cursor/mcp.json`, etc.): ```json { "mcpServers": { "lessie": { "command": "npx", "args": ["-y", "@lessie/mcp-server"], "env": { "LESSIE_REMOTE_MCP_URL": "https://app.lessie.ai/mcp-server/mcp" } } } } ``` ### Uninstall - **CLI:** `npm uninstall -g @lessie/cli && rm -rf ~/.lessie/` - **MCP:** Remove the `"lessie"` entry from your `.mcp.json` and `rm -rf ~/.lessie/` ## Quick start After setup, try saying to Claude: - "Find Engineering Managers at Stripe in San Francisco" - "Look up Sam Altman's contact info" - "Research OpenAI — recent news and open job postings" ## Mode detection Determine which mode to use at the start of each session: 1. Check if `lessie` CLI is available: run `lessie status` 2. If the command succeeds → use **CLI mode** (call tools via Bash) 3. If the command fails (not found) → attempt auto-install: `npm install -g @lessie/cli` 4. After install, run `lessie status` again to verify 5. If install succeeds → use **CLI mode** 6. If install fails (no npm, permission denied, network error, etc.) → check if MCP tools are available (`authorize`, `use_lessie`) 7. If MCP tools are available → use **MCP mode** 8. If neither → inform the user that installation failed and suggest manual install or MCP setup ## Credits & Pricing Lessie is a credit-based service. New accounts receive free trial credits. View your balance and purchase more at https://lessie.ai/pricing. The agent will disambiguate company names before searching to avoid wasting credits on wrong results. ## Data & Privacy - **Data sources:** Contact and company information is aggregated from publicly available sources (business directories, social profiles, corporate websites). - **Query logging:** Search queries are logged for service improvement and abuse prevention. No query data is shared with third parties. - **Data compliance:** Lessie follows applicable data protection regulations. Users are responsible for using retrieved contact data in compliance with local laws (GDPR, CAN-SPAM, etc.). - **Privacy policy:** https://lessie.ai/privacy - **Terms of service:** https://lessie.ai/terms-of-service ## Authorization ### CLI mode 1. Run `lessie status` to check token validity. 2. If `authorized: false` → run `lessie auth` to open browser for login. 3. After the user completes login, run `lessie status` again to confirm. ### MCP mode 1. Call `authorize` to check connection status. 2. **If already authorized** → proceed to use tools directly. 3. **If not authorized** → `authorize` returns an authorization URL. Tell the user you need to open a browser for Lessie login/registration, and open it using the appropriate system command: - macOS: `open "<url>"` - Linux: `xdg-open "<url>"` - Windows: `start "<url>"` 4. Tell the user the browser has been opened and they need to complete login/registration. 5. After the user confirms, call `authorize` again to verify the connection. 6. If authorization fails (timeout, denied, port conflict), follow the diagnostic hints returned by `authorize` and retry. Always inform the user before opening the browser — never silently redirect. ## Agent behavior rules ### Entity disambiguation When a user mentions a company name that could refer to multiple entities (e.g., "Manus" could be Manus AI, Manus Bio, Manus Plus, etc.), disambiguate before searching: 1. **Ask the user** which company they mean, or present the top candidates and let them pick. 2. If context makes it unambiguous (e.g., user previously discussed AI agents), state your assumption and confirm: "你是指做 AI Agent 的 Manus AI (manus.im) 吗？" 3. **Never silently assume** one entity over another — wrong domain = wasted search credits and irrelevant results. ## Tools overview ### People | Tool | CLI command | When to use | |------|-------------|-------------| | `find_people` | `lessie find-people` | Discover people by title, company, location, seniority, audience. Default strategy is `hybrid`. **If a request times out or fails, retry with `--strategy saas_only`** — it's faster (~30s vs ~60s) and more stable, though recall may be lower | | `enrich_people` | `lessie enrich-people` | Fill missing profile data for known individuals (email, phone, LinkedIn, work history) | | `review_people` | `lessie review-people` | Deep-qualify **ambiguous** candidates via web research — skip for obvious matches/mismatches | ### Companies | Tool | CLI command | When to use | |------|-------------|-------------| | `find_organizations` | `lessie find-orgs` | Discover companies by name, keyword, location, size, funding | | `enrich_organization` | `lessie enrich-org` | Get full profile for known company domain(s) — industry, employees, funding, tech stack | | `get_company_job_postings` | `lessie job-postings` | View active job openings (needs `organization_id` from enrich) | | `search_company_news` | `lessie company-news` | Find recent news articles (needs `organization_id` from enrich) | ### Web research | Tool | CLI command | When to use | |------|-------------|-------------| | `web_search` | `lessie web-search` | General web search; cached results make follow-up `web_fetch` free | | `web_fetch` | `lessie web-fetch` | Extract specific info from a URL via AI summarization | ## Detailed references - **CLI command examples & MCP calling**: See [references/cli-reference.md](references/cli-reference.md) - **Workflow patterns** (domain resolution, company research, search+qualify): See [references/workflow-patterns.md](references/workflow-patterns.md) - **Domain resolution decision tree**: See [references/domain-resolution.md](references/domain-resolution.md) ## Key constraints - `enrich_people` / `enrich_organization`: max 10 per call; split larger lists into batches - `find_people` / `find_organizations`: paginated — use `--page` for more results - `web_search` caches page content; if a result has `has_content: true`, calling `web_fetch` on that URL is instant - Seniority levels: `owner`, `founder`, `c_suite`, `partner`, `vp`, `head`, `director`, `manager`, `senior`, `entry`, `intern` - For people enrichment, providing `domain` (company domain) alongside name greatly improves match accuracy - CLI output is JSON on stdout, status messages on stderr — parse stdout for data