# 𧲠OpenLeads
### Find people and their work emails from free public data β then work them like you would in Apollo. No API keys. $0.
**Type who you want (_"dentists in Austin"_, _"fintech founders"_, _"law firms in London"_) and OpenLeads searches OpenStreetMap, Y Combinator, GitHub, OpenAlex, SEC EDGAR, Wikidata and company websites, finds the real people, and tells you honestly which emails are confirmed and which are guesses. Then it scores them against your ideal customer, organizes them into lists, and runs multi-step email, call and LinkedIn sequences, tasks and a deal pipeline. It runs on your machine.**
[](./COMMERCIAL-LICENSE.md)
[](https://pypi.org/project/openleads/)
[](https://www.npmjs.com/package/openleads)
[](https://www.python.org/)
[](#how-it-works)
[](https://github.com/Samyrrrrrr990/openleads/actions/workflows/ci.yml)
[](./BENCHMARK.md)
[](https://github.com/Samyrrrrrr990/openleads/stargazers)
```bash
pipx install openleads # or: pip install openleads Β· npx openleads
openleads find "dentists in Austin"
openleads web # the dashboard Β· or `openleads demo` to look around first
```
[**Website**](https://samyrrrrrr990.github.io/openleads/) Β· [**Docs**](https://samyrrrrrr990.github.io/openleads/docs/) Β· [**Live benchmark**](./BENCHMARK.md) Β· [**Changelog**](./CHANGELOG.md)
The local dashboard (openleads demo, invented data). Light and dark, keyboard-first, nothing leaves your machine.
 |
 |
| People & companies. Facets with live counts, saved searches, bulk actions on every matching row, full records with timeline, notes, tasks and deals. |
Sequences. Email, call, LinkedIn and task steps; A/B variants; same-thread follow-ups; AI-written steps; people leave when they reply. |
 |
 |
| Deals. A drag-and-drop pipeline with weighted forecast; winning a deal makes the contact a customer. |
Everything else. Task queue, templates, ICP scoring, CSV import, data health and duplicate merge, a βK palette. |
```bash
openleads people --fit A --never-contacted # best untouched leads
openleads lists add "Q4 dentists" --where dental
openleads seq enroll "Q4 outbound" --list "Q4 dentists"
openleads tasks --bucket today
openleads import apollo-export.csv --list "Imported"
```
[Workspace guide β](./docs/workspace.md) Β· [Sequences guide β](./docs/sequences.md)
## Use it from Claude, Cursor or Claude Code
OpenLeads is an [MCP server](./docs/mcp.md). Your AI assistant can find and verify
leads mid-conversation:
```bash
claude mcp add openleads -- openleads mcp
```
```json
{ "mcpServers": { "openleads": { "command": "openleads", "args": ["mcp"] } } }
```
> *"Find 10 law firms in London with emails we can actually send to, and draft a two-line intro for each."*
> *"Save them to a list called London law, add the A-grade ones to my Q4 sequence, and give me a call task for each partner."*
The workspace tools let an assistant search your contacts and companies, read a
full record, and save leads, set stages, tag, take notes, create tasks and deals
and enroll people in sequences β never sending anything itself.
## Build it as a workflow
The dashboard's **Workflows** page draws each saved search as a node canvas, like n8n.
Click a node to edit it (who to find, what to offer, when to run, where to export), then hit
**Test run** and watch every node fill in from the live engine. Test runs never
send. [Workflows guide β](./docs/workflows.md)
Export nodes push leads to CSV, Google Sheets, Notion, Airtable, or any webhook, so
the rest of your stack (n8n, Zapier, Make) can take it from there.
## Put it on a schedule
```bash
openleads recipe add miami "marketing agencies in Miami" --every "weekdays 9am" --send
openleads schedule on # one agent: launchd Β· cron Β· Windows Task Scheduler
openleads runs # what ran, what it found, what failed
```
Schedules can be plain English (`every 2h`, `mon,thu 14:00`) or cron. Sends stay
inside your daily cap, warmup ramp and business-hour windows, and stop for anyone
who replies. Failed runs send a desktop alert, plus a webhook if you set one.
[Timed runs β](./docs/timed-runs.md)
Rather run it in CI? There's a GitHub Action:
```yaml
- uses: Samyrrrrrr990/openleads@v5.0.0
with: { query: "marketing agencies in Miami", count: 50 }
```
## Install
```bash
pipx install "openleads[all]" # recommended
pip install openleads # minimal: stdlib-only engine + CLI
npx openleads find "β¦" # Node: sets up a private Python env on first run
```
```bash
openleads doctor # checks your setup (DNS, port 25, mailbox)
openleads # chat: type what you want
openleads web # local dashboard at http://127.0.0.1:8787
```
Full walkthrough: [docs/quickstart.md](./docs/quickstart.md).
## Commands
```bash
openleads find "50 fintech founders, verified only" -o leads.csv
openleads find "emails at stripe.com"
openleads enrich my-list.csv # your names/companies β verified emails
openleads verify ada@acme.io # check one address
openleads run "rust developers in Berlin" # find β write β send (dry-run unless --live)
openleads recipe add NAME "query" --every "β¦" # save it, schedule it
openleads watch add NAME "query" # alert me only on new matches
openleads schedule on | off | status
openleads runs
openleads people Β· companies Β· lists Β· seq # your workspace (see above)
openleads tasks Β· deals Β· import Β· dedupe Β· stats Β· backup
openleads demo # the dashboard on invented data
openleads bench # live quality benchmark
openleads mcp # MCP server for AI tools
openleads sources Β· crm Β· config Β· doctor Β· inbox
```
Sending is a **dry run by default** everywhere. Add `--live` to send.
## How it works
```mermaid
flowchart LR
Q["'dentists in Austin'"] --> P[Intent parser]
P --> F[Federation