Browser-native AI agents for X (Twitter): multi-account, MCP-ready, no X API key required.
# Add to your Claude Code skills
git clone https://github.com/ihuzaifashoukat/x-useGuides for using ai agents skills like x-use.
Last scanned: 7/25/2026
{
"issues": [
{
"file": "README.md",
"line": 149,
"type": "secret-exfiltration",
"message": "Instruction appears to send credentials/secrets to an external endpoint",
"severity": "medium"
},
{
"file": "README.md",
"line": 41,
"type": "remote-install",
"message": "Install command (remote install script piped to a shell — review the source before running): \"curl -fsSL https://raw.githubusercontent.com/ihuzaifashoukat/x-use/main/install.\"",
"severity": "low"
}
],
"status": "PASSED",
"scannedAt": "2026-07-25T06:18:19.076Z",
"npmAuditRan": true,
"pipAuditRan": false,
"promptInjectionRan": true
}Browser-native AI agents for X (Twitter). Multi-account, MCP-ready, no X API key required.
x-use drives a real, stealth-hardened browser instead of the paid X API. It posts, replies, searches, and engages across as many accounts as you configure, writes content with your own LLM, and exposes everything as MCP tools, so Claude Desktop, Claude Code, Cursor, and other MCP clients can run your X presence directly.
The X API's pricing tiers put write access out of reach for exactly the people who want to automate a couple of accounts. x-use sidesteps the API entirely: if a logged-in browser can do it, an MCP client can ask for it. And because write actions go through a draft-approval step by default, an agent can prepare work all day while nothing reaches X until a human says yes.
x-use is the v2 relaunch of twitter-automation-ai. The repository was renamed; old URLs keep redirecting, and stars, forks, and issues came along intact.
From PyPI (CLI and MCP server):
pip install x-use-mcp
For the full repo setup (presets, example configs, docs), the one-line installer clones the repo, installs x-use into its own virtual environment, and finishes with x-use doctor so you can see what is left to configure.
Windows (PowerShell):
iex "& { $(irm https://raw.githubusercontent.com/ihuzaifashoukat/x-use/main/install.ps1) }"
macOS / Linux / Git Bash:
curl -fsSL https://raw.githubusercontent.com/ihuzaifashoukat/x-use/main/install.sh | bash
Or the manual way:
git clone https://github.com/ihuzaifashoukat/x-use.git
cd x-use
pip install -e .
Requires Python 3.10+ and Chrome. Any of these gives you the x-use command.
x-use init # interactive wizard: presets, account + cookie import, LLM keys
x-use doctor # verify browser/driver, cookies, LLM keys, proxies
Then connect your AI client. Paste this into claude_desktop_config.json (Claude Desktop > Settings > Developer > Edit Config); the same command/args pair works for any MCP client that runs stdio servers:
{
"mcpServers": {
"x-use": {
"command": "x-use",
"args": ["mcp"]
}
}
}
If x-use is not on your client's PATH, use the full path the installer printed (for example venv/bin/x-use or venv\Scripts\x-use.exe). Restart the client, then ask it to list_accounts.
Draft mode is on by default. Write tools return a reviewable draft and change nothing until you call approve_draft with the returned draft_id. Opt out with "mcp": { "draft_mode": false } in config/settings.json.
25 tools in four groups. Two safety gates: the immediate write tools run in draft mode by default (review, then approve_draft), and the queue only stores work until an explicit process_queue call (or the opt-in auto_drain worker) executes it with jittered pacing and daily caps.
Interactive use needs no LLM key at all: your MCP client (Claude, Codex, ...) does the thinking and passes explicit text to the write tools. The optional server-side LLM (llm block in settings) only powers "auto" generation and background automation.
Read-only and status:
| Tool | What it does |
|---|---|
list_accounts() |
List configured accounts with secrets stripped. |
get_account(account) |
One account's masked config plus cookie-file status. |
get_metrics(account) |
Counters and recent events for an account. |
search_tweets(keywords, limit=10, account?) |
Search recent posts for a query. |
prepare_reply(account, tweet_url) |
Fetch a tweet's content plus the account context so your agent can write the reply itself. No LLM, nothing posted. |
list_queue(account?, status?) |
Queued actions with full payloads (exactly what will fire) plus per-status counts. |
list_drafts(status?, account?, limit=20) |
Drafts, newest first, with filters. |
get_draft(draft_id) |
One draft by id. |
reject_draft(draft_id) |
Reject a pending draft (local status flip; nothing touches X). |
get_run_status(run_id?) |
Poll run_cycle handles. |
get_account_health(account) |
Config, cookie validity, metrics, session, queue, and draft state in one call. |
Write tools (draft-gated):
| Tool | What it does |
|---|---|
post_tweet(account, text, media?, community?) |
Post text/media, optionally into a community. |
generate_and_post(account, topic) |
Generate a post with the server-side LLM (needs the llm block), then post it. Prefer post_tweet with your own text when driving from an MCP client. |
reply_to_tweet(account, tweet_url, text="auto") |
Reply with explicit text, or "auto" to generate from the tweet's content via the server-side LLM. |
engage(account, keywords, actions=["like"], max_actions=5) |
Relevance-gated likes/retweets on keyword results. |
run_cycle(account?, pipelines?) |
Full orchestrator cycle in the background; returns a run handle. |
approve_draft(draft_id) |
Execute a pending draft exactly once. |
Scheduled queue (the second gate):
| Tool | What it does |
|---|---|
queue_post(account, text? topic?, media?, community?, not_before?) |
Queue a post for paced execution. topic generates the text now, so list_queue shows the final payload. not_before schedules (ISO 8601). |
queue_engagement(account, action, tweet_url, text?) |
Queue a like, retweet, or reply. Replies accept "auto" to generate the text now. |
cancel_queued_action(queue_id) |
Cancel a pending or failed item. |
process_queue(account?, max_actions=5) |
The approval gate: drains due items through the shared pacing/dedup/metrics path with daily caps. |
Account management (validated, backed up, atomic):
| Tool | What it does |
|---|---|
add_account(account_id, cookie_file?, proxy?, target_keywords?, is_active=true) |
Add an account. Cookies import from a file path on the server, never inline. |
update_account(account, ...) |
Partial update; closes the warm session so changes take effect. |
set_account_active(account, active) |
Pause or resume an account without deleting it. |
remove_account(account, confirm) |
Remove an account (requires confirm=true; backups in config/backups/). |
Drafts persist in data/drafts.jsonl; the queue persists in data/engagement_queue.jsonl. Both survive restarts.
x-use init # interactive setup wizard
x-use run # all active accounts, concurrent
x-use run --account my_account # one account only
x-use run --pipeline keyword_replies # one pipeline only (in-memory; config files untouched)
x-use doctor # environment checks; exits non-zero on failure
x-use mcp # start the MCP stdio server
Pipelines for --pipeline: community_engagement, competitor_reposts, content_curation, keyword_replies, keyword_retweets, likes. The MCP run_cycle tool accepts the same names.
The legacy python src/main.py entry point still works via a deprecation shim (removal no earlier than v2.1).
| Area | What you get |
|---|---|
| MCP server | 25 tools over stdio on the official MCP Python SDK (FastMCP, pinned mcp>=1.6,<2): draft-gated writes, a persistent scheduled-action queue with daily caps, account management, and a lazy per-account browser session pool. |
| Draft mode | On by default. Write tools build the full payload (including LLM-generated text), store a draft, and touch nothing until approve_draft runs. |
| Multi-account engine | Post (including communities and media), reply, repost/quote, like, keyword search, and relevance-gated engagement. Per-account overrides for keywords, LLM settings, and action behavior. |
| LLM generation | One OpenAI-compatible client (llm: api_key, base_url, model) covers OpenAI, OpenRouter, Azure, Gemini, and local servers. Only needed for "auto" text and background automation; interactive MCP use runs keyless. Keys resolve from env/.env first, then config/settings.json. |
| Stealth | undetected-chromedriver, selenium-stealth, randomized user agents, headless support. |
| Proxies | Per-account proxy, named pools, hash or round-robin rotation, ${VAR} env interpolation in proxy strings. |
| Metrics | Per-account counters in data/metrics/<account_id>.json plus JSONL event logs in logs/accounts/<account_id>.jsonl. |
| x-use | API-based X/Twitter MCP servers | |
|---|---|---|
| X API cost | $0: cookie auth, no X API key needed | Paid X API tier required |
| Multi-account | Built-in: per-account config, cookies, proxies | Typically one account |
| Proxies | Per-account proxies, named pools, hash/round-robin rotation | N/A |
| Stealth | undetected-chromedriver + selenium-stealth, randomized user agents | N/A (official API) |
| Write safety | Draft mode on by default, explicit approve_draft gate |
Usually posts directly |
| Metrics | Per-account counters + JSONL event logs, readable via MCP | Varies |
An LLM key is optional: interactive
x-use is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by ihuzaifashoukat. Browser-native AI agents for X (Twitter): multi-account, MCP-ready, no X API key required. It has 148 GitHub stars.
Yes. x-use passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/ihuzaifashoukat/x-use" and add it to your Claude Code skills directory (see the Installation section above).
x-use is primarily written in Python. It is open-source under ihuzaifashoukat on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh x-use against similar tools.
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