adauto 1.0.5

Developer marketing automation — pulse scanning, ethics filter, multi-platform posting

adauto

Developer marketing automation — ethics-filtered, human-approved.

adauto runs on your machine, drafts authentic posts for developer communities (Reddit, Hacker News, dev.to, X/Twitter), hunts for people who actually have the problem you solve, and learns from engagement over time. Every post passes an ethics filter and waits for your explicit approval — nothing is ever published automatically.

• Local-first. Runs as a CLI, an HTTP server, or an MCP server on your own machine.
• Bring your own brain. Works with deepstrain, OpenAI, Ollama, Anthropic, or any OpenAI-compatible API. No LLM backend is mandatory for the deterministic features.
• Human-in-the-loop. Generate and queue → review → approve → post. You hold the gate.
• Honest by design. Marketing claims are checked against a verified-claims source; the ethics filter blocks hype and unverifiable numbers.

Site: adauto.massiron.com

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Install

pip install adauto

Requires Python 3.11+.

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Start in 30 seconds

# 1. Register adauto (and any sibling tools) into every MCP client you have,
#    and start the local servers.
adauto setup

# 2. Open the web control center — run campaigns, review drafts, approve, connect.
adauto gui

adauto gui opens http://127.0.0.1:8766/ui in your browser. Nothing posts without your approval.

Prefer the terminal? The classic loop is:

adauto init-from-repo .      # build a campaign from YOUR repo's README + manifest
adauto generate myproject    # draft posts (queued, NOT posted)
adauto review                # read each draft, approve or skip
adauto post myproject        # publish only what you approved

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LLM backend options

adauto needs a language model only to write posts. The deterministic features (signal hunting, pulse scanning, analytics) use no LLM at all. When generation is needed, adauto picks the first available backend in this order:

Priority	Backend	How to enable	Notes
1	deepstrain	Run deepstrain serve (auto-detected on localhost:8765)	Richest context; uses your own deepstrain key. Optional.
2	OpenAI-compatible	ADAUTO_LLM_KEY (+ optional ADAUTO_LLM_URL, ADAUTO_LLM_MODEL)	Works with OpenAI, Together, Groq, Ollama (ADAUTO_LLM_URL=http://localhost:11434/v1), etc.
3	OpenAI	OPENAI_API_KEY (+ optional OPENAI_BASE_URL)	Defaults to gpt-4o-mini.
4	Anthropic Claude	ANTHROPIC_API_KEY	Requires pip install anthropic. Model via ADAUTO_CLAUDE_MODEL.

deepstrain is optional — adauto is fully standalone. To skip deepstrain even when it is running, set ADAUTO_NO_DEEPSTRAIN=1.

See .env.example for a copy-paste starting point.

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Command reference

Setup & serving

Command	What it does
adauto setup	Detect all MCP clients (Claude Code, Kilo Code, Cursor, Windsurf, Claude Desktop, Cline), register every installed product, and start the HTTP servers.
adauto setup --list-clients	List supported MCP clients and their config-file paths (no changes made).
adauto setup --no-start	Register clients but do not launch any HTTP server.
adauto gui	Open the 5-tab web control center (--port, --no-browser).
adauto chat	Terminal REPL against a running MCP HTTP server (--product, --url).
adauto serve	Start the REST/automation HTTP server (GET /, /exec, /eval, /approve).
adauto mcp	Start the MCP server (stdio by default; --http for HTTP).
adauto service install	Register adauto as an OS service that auto-starts on boot.

Campaign lifecycle

Command	What it does
adauto init	Create config directories and the local database.
adauto init-from-repo <path>	Auto-generate a campaign from a repo's README + manifest (--no-llm for offline).
adauto campaigns	List configured campaigns.
adauto generate <campaign>	Draft posts and queue them for approval (does not post).
adauto run	Full loop across due platforms: generate → queue (never auto-posts).
adauto review	Interactively read each pending post and approve / skip / edit.
adauto post <campaign>	Publish only the posts you approved (--dry-run to preview).

Signals & learning

Command	What it does
adauto hunt <campaign>	Zero-cost, no-LLM scan of Reddit/HN/GitHub/dev.to/Stack Overflow for matching pain signals.
adauto signals [campaign]	Review found signals (--stats for a platform breakdown).
adauto respond <campaign>	Draft genuinely-helpful replies to found signals → queued for approval.
adauto check-engagement	Poll platforms for upvotes/comments and update the learning data.
adauto report [campaign]	ROI report: cost, cost-per-score, best-performing strategy.
adauto status	Pending / approved / posted counts and engagement scores.

Configuration

Command	What it does
adauto configure	Set platform API credentials (Reddit, Twitter, dev.to) into ~/.adauto/credentials.env.
adauto configure --show	Show which credentials are set (masked).
adauto license activate <key>	Activate a Pro license.
adauto license status	Show current license tier.

Run adauto <command> --help for the full option list on any command.

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adauto setup — one command, every client

adauto setup looks for installed MCP clients and registers every massiron product you have on PATH as an HTTP MCP server (a single running server is visible to every client and to you directly — no invisible stdio subprocesses).

Supported clients and the config files they use:

Client	Config path
Claude Code	~/.claude.json
Claude Desktop	%APPDATA%/Claude/claude_desktop_config.json
Cursor	~/.cursor/mcp.json
Windsurf	~/.codeium/windsurf/mcp_config.json
Kilo Code	%APPDATA%/Code/User/globalStorage/kilocode.kilo-code/.../cline_mcp_settings.json
Cline	%APPDATA%/Code/User/globalStorage/saoudrizwan.claude-dev/.../cline_mcp_settings.json

Default HTTP MCP ports: adauto → 8767, deepstrain → 8765, atlas → 8768.

adauto setup                 # detect, register, start servers
adauto setup --list-clients  # just show clients + paths
adauto setup --no-start      # register only; start servers yourself later

After registering, restart your MCP client once to pick up the new servers.

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adauto chat — talk to a running server

A minimal REPL that speaks MCP to a running HTTP server. Useful for poking at tools without an LLM client.

adauto chat                       # connect to adauto      (port 8767)
adauto chat --product deepstrain  # connect to deepstrain  (port 8765)
adauto chat --url http://HOST:PORT

Example session:

$ adauto chat
[chat] Connected to adauto v0.5.5  (http://localhost:8767)
[chat] 5 tools: run, status, approve, post, report
[chat] Type 'tools' to list, '<tool> [k=v ...]' to call, 'q' to quit.

adauto> status
{
  "pending": 3,
  "approved": 1,
  "posted": 12
}
adauto> run campaign=myproject
{
  "queued": 4,
  "next": "Review with `adauto review`"
}
adauto> q

Inside the REPL: tools lists available tools, <tool> key=value … calls one (values are coerced to int/bool when they look like it), and q / quit exits.

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adauto sessions — resume an unfinished thread

adauto can find where your AI coding tools store their chat history on disk — Claude Code, Cursor, Windsurf, Cline, Kilo and Claude Desktop — so a half-finished thread can be picked up and handed to deepstrain to keep building. Read-only, deterministic, no LLM, no network.

adauto sessions                      # list detected sources, newest first
adauto sessions --json               # machine-readable (pipe into automation)
adauto sessions --handoff deepstrain # 'continue from' brief for deepstrain
adauto sessions --handoff deepstrain --product claude-code

Example:

$ adauto sessions
[adauto] 2 chat-history source(s) — newest first:

  Claude Code       122 sessions   last: 2026-06-01 22:56:06
                   one .jsonl per session, grouped by project path
                   → ~/.claude/projects/<project>/<session>.jsonl

  deepstrain         16 sessions   last: 2026-06-01 10:48:14
                   deepstrain's own session logs (see `deepstrain logs`)

The --handoff brief restates the recent exchange and the goal so another agent can continue exactly where you left off — the "continue from Claude / from your IDE" workflow.

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adauto gui — the web control center

adauto gui                 # opens http://127.0.0.1:8766/ui
adauto gui --port 9000     # custom port
adauto gui --no-browser    # start the server without opening a browser

Five tabs:

Tab	What it does
Campaigns	Overview stats, pick a campaign, Run it (generate + queue), and pull a ROI Report.
Review	Every pending draft shown in full with its ethics status. Approve all, or approve/skip one at a time. A badge shows how many are waiting.
Signals	Pain signals found by adauto hunt, grouped by campaign — the people who need what you built.
Analytics	Engagement scores and cost/score by platform and post type, plus a live readout of which LLM backend is active.
Connect	One-click "register in all MCP clients" (same as adauto setup), live server status, and an MCP tool tester.

Nothing posts from the GUI without your approval.

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Ecosystem (optional)

adauto stands alone. It is also one of three independent tools that share a local-first, bring-your-own-LLM design:

• adauto — developer marketing automation (this tool).
• deepstrain — terminal-native AI engineering agent. If running, adauto uses it as its richest content backend; otherwise adauto falls back to any OpenAI-compatible API. Entirely optional.
• atlas — deterministic code intelligence (offline, zero LLM tokens).

adauto setup will register whichever of these are installed into your MCP clients. Install only what you need.

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Configuration & data locations

• Campaign configs: ~/.adauto/campaigns/<name>.toml (copy from the repo's campaigns/).
• Platform credentials: ~/.adauto/credentials.env (user-only permissions, auto-loaded).
• Local database (queue, engagement, signals): under ~/.adauto/.

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Licensing

• Free — 1 campaign, 3 posts/day, all deterministic features (hunt, signals, pulse).
• Pro ($29/mo) — unlimited campaigns, all platforms, engagement learning.

adauto license activate ADTO-XXXXX-XXXXX-XXXXX-XXXXX
adauto license status

Get a license at adauto.massiron.com.