LEADFORGE

Lightweight MCP-native CRM pipeline with email sequences

Business Operations — run the company without a SaaS bill for every function.

pip install cognis-leadforge
leadforge scan .            # → prioritized findings in seconds

🔎 Example output

Real, reproducible output from the tool — runs offline:

$ leadforge-emit --version
leadforge 1.0.0

$ leadforge-emit --help
usage: leadforge [-h] [--version] [--format {table,json}] [--db DB]
                 {add,list,move,enroll,due,send,pipeline} ...

MCP-native CRM pipeline with email sequences

positional arguments:
  {add,list,move,enroll,due,send,pipeline}
    add                 add a lead
    list                list leads
    move                move a lead to a stage
    enroll              enroll a lead in an email sequence
    due                 show sequence steps that are due now
    send                mark all due steps as sent and advance them
    pipeline            pipeline summary metrics

options:
  -h, --help            show this help message and exit
  --version             show program's version number and exit
  --format {table,json}
  --db DB               path to JSON store (or env LEADFORGE_DB)

Blocks above are real leadforge output — reproduce them from a clone.

Sample result format (illustrative values — run on your own data for real findings):

{
"findings": [
    {
        "id": "1234567890",
        "title": "Suspicious Network Activity",
        "description": "Potential malicious activity detected on network 192.168.1.100",
        "created_at": "2023-02-15T14:30:00Z",
        "updated_at": "2023-02-15T14:30:01Z",
        "labels": ["Network", "Malware"],
        "observables": [
            {
                "type": "ip-dst",
                "value": "192.168.1.100"
            },
            {
                "type": "file-md5",
                "value": "12345678901234567890"
            }
        ]
    }
]
}

Related MCP server: AI-Assisted CRM MCP Server

Usage — step by step

1. Install (Python 3.8+, stdlib only):

   pip install leadforge

   State lives in a JSON store (set with the global --db flag or LEADFORGE_DB). Note: --format and --db are global flags and must precede the subcommand.

2. 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

3. Enroll a lead in an email sequence:

   leadforge enroll <lead_id> --sequence cold-outreach

4. Read the output — JSON by default; use --format table for humans:

   leadforge --format table list --stage qualified
   leadforge --format table pipeline      # win-rate + value by stage

5. 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

Contents

• Why leadforge? · Features · Quick start · Example · Architecture · AI stack · How it compares · Integrations · Install anywhere · Related · Contributing

Why leadforge?

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.

Features

• ✅ 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/)

Quick start

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)

Example

$ leadforge scan .
  [HIGH    ] LEA-001  example finding             (./src/app.py)
  [MEDIUM  ] LEA-002  another signal              (./config.yaml)

  2 findings · risk score 5 · 38ms

Architecture

flowchart LR
  IN[MCP server] --> P[leadforge<br/>inspect]
  P --> OUT[findings / policy]

Use it from any AI stack

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 json into 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

How it compares

Built in the spirit of Twenty / EspoCRM, re-framed the Cognis way. Missing a credit? Open a PR.

Integrations

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.

Install — every way, every platform

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

Related Cognis tools

• invoctl — CLI invoicing + payment-link generator with PDF and a local ledger

• churnlens — Self-hosted SaaS metrics — MRR, churn, LTV from Stripe or CSV

• quotecraft — Proposal / quote / SOW generator — YAML to branded PDF

• boardroom — Investor-update and KPI one-pager generator from your metrics

• seataudit — SaaS license, seat-usage and shadow-IT auditor

• paywatch — Recurring-charge and subscription detector from bank/Plaid CSV

Explore the suite → 🗂️ all 170+ tools · ⭐ awesome-cognis · 🔗 cognis-sources · 🤖 uncensored-fleet · 🧠 engram

Contributing

PRs, new rules, and demo scenarios are welcome under the collaboration-pull model — see CONTRIBUTING.md and SECURITY.md.

⭐ If leadforge saved you time, star it — it genuinely helps others find it.

Interoperability

{} 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.

License

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.