pip install cognis-leadforge
leadforge scan . # → prioritized findings in seconds- Install (Python 3.8+, stdlib only):
State lives in a JSON store (set with the global
pip install leadforge
--dbflag orLEADFORGE_DB). Note:--formatand--dbare global flags and must precede the subcommand. - Add a lead and move it through the pipeline:
leadforge add "Acme Corp" jane@acme.com --company Acme --value 12000 leadforge move <lead_id> qualified
- Enroll a lead in an email sequence:
leadforge enroll <lead_id> --sequence cold-outreach
- Read the output — JSON by default; use
--format tablefor humans:leadforge --format table list --stage qualified leadforge --format table pipeline # win-rate + value by stage - Run the sequence cadence (cron / agent) — find due steps, then advance them:
leadforge due # what is due now leadforge send # mark due steps sent and advance them
- Why leadforge? · Features · Quick start · Example · Architecture · AI stack · How it compares · Integrations · Install anywhere · Related · Contributing
CRM your AI agents can drive over MCP
leadforge is single-purpose, scriptable, and self-hostable: point it at a target, get prioritized results in the format your workflow already speaks (table · JSON · SARIF), gate CI on it, and let agents drive it over MCP.
- ✅ Fast, single-purpose CLI
- ✅ JSON / SARIF output for pipelines
- ✅ CI fail-gate (
--fail-on) - ✅ MCP server for AI agents
- ✅ Runs on Linux/macOS/Windows · Docker · devcontainer
- ✅ Ports in Python, JavaScript, Go, and Rust (
ports/)
pip install cognis-leadforge
leadforge --version
leadforge scan . # scan current project
leadforge scan . --format json # machine-readable
leadforge scan . --fail-on high # CI gate (non-zero exit)$ leadforge scan .
[HIGH ] LEA-001 example finding (./src/app.py)
[MEDIUM ] LEA-002 another signal (./config.yaml)
2 findings · risk score 5 · 38ms
flowchart LR
IN[MCP server] --> P[leadforge<br/>inspect]
P --> OUT[findings / policy]
leadforge is interoperable with every popular way of using AI:
- MCP server —
leadforge mcp(Claude Desktop, Cursor, Cognis.Studio, uncensored-fleet) - OpenAI-compatible / JSON — pipe
leadforge scan . --format jsoninto any agent or LLM - LangChain · CrewAI · AutoGen · LlamaIndex — wrap the CLI/JSON as a tool in one line
- CI / scripts — exit codes + SARIF for non-AI pipelines
| Cognis leadforge | Twenty | |
|---|---|---|
| Self-hostable, no account | ✅ | varies |
| Single command, zero config | ✅ | |
| JSON + SARIF for CI | ✅ | varies |
| MCP-native (AI agents) | ✅ | ❌ |
| Polyglot ports (JS/Go/Rust) | ✅ | ❌ |
| Open license | ✅ COCL | varies |
Built in the spirit of Twenty / EspoCRM, re-framed the Cognis way. Missing a credit? Open a PR.
Pipes into your stack: SARIF for code-scanning, JSON for anything, an MCP server (leadforge mcp) for AI agents, and a webhook forwarder for SIEM/Slack/Jira. See docs/INTEGRATIONS.md.
pip install "git+https://github.com/cognis-digital/leadforge.git" # pip (works today)
pipx install "git+https://github.com/cognis-digital/leadforge.git" # isolated CLI
uv tool install "git+https://github.com/cognis-digital/leadforge.git" # uv
pip install cognis-leadforge # PyPI (when published)
docker run --rm ghcr.io/cognis-digital/leadforge:latest --help # Docker
brew install cognis-digital/tap/leadforge # Homebrew tap
curl -fsSL https://raw.githubusercontent.com/cognis-digital/leadforge/main/install.sh | sh| Linux | macOS | Windows | Docker | Cloud |
|---|---|---|---|---|
scripts/setup-linux.sh |
scripts/setup-macos.sh |
scripts/setup-windows.ps1 |
docker run ghcr.io/cognis-digital/leadforge |
DEPLOY.md (AWS/Azure/GCP/k8s) |
invoctl— CLI invoicing + payment-link generator with PDF and a local ledgerchurnlens— Self-hosted SaaS metrics — MRR, churn, LTV from Stripe or CSVquotecraft— Proposal / quote / SOW generator — YAML to branded PDFboardroom— Investor-update and KPI one-pager generator from your metricsseataudit— SaaS license, seat-usage and shadow-IT auditorpaywatch— Recurring-charge and subscription detector from bank/Plaid CSV
Explore the suite → 🗂️ all 170+ tools · ⭐ awesome-cognis · 🔗 cognis-sources · 🤖 uncensored-fleet · 🧠 engram
PRs, new rules, and demo scenarios are welcome under the collaboration-pull model — see CONTRIBUTING.md and SECURITY.md.
{} composes with the 300+ tool Cognis suite — JSON in/out and a shared
OpenAI-compatible /v1 backbone. See INTEROP.md for the
suite map, composition patterns, and reference stacks.
Source-available under the Cognis Open Collaboration License (COCL) v1.0 — free for personal, internal-evaluation, research, and educational use; commercial / production use requires a license (licensing@cognis.digital). See LICENSE.