Agent Twitter Client MCP Server
agent-twitter-client-mcp
npm
v0.1.0
Published by ryanmac — no publish provenance, so origin is unverified, but the source is public: the repository link below is self-declared yet readable, so you can inspect the code before adopting it.
MCP server for Twitter integration using agent-twitter-client
The grade answers one question — how safe is this server for you to adopt — so it is computed in two auditable stages. Nothing below is an opinion or an LLM's guess; every line is a real term the deterministic engine applied, and the same input always yields the same number.
1. Threat score — 100 − 0 = 100. What the published surface and source actually contain:
The deterministic scan raised no scored threat in the surface it inspected — the threat score stayed at 100. Capability observations and advisory notes are recorded but never lower it.
2. Client adoption risk — 100 − 4 = 96. Three small, subtract-only factors that reflect your risk in adopting it — a clean scan proves less on a powerful, unverified or barely-inspectable package, so the grade says so plainly:
| Points | Adoption-risk factor |
|---|---|
| −3 | capability blast radius (moderate) — client exposure if the model is manipulated |
| −1 | publisher verification (public source) — no provenance, but the source is public and inspectable |
Capability observations and info notes are shown under Findings but never scored.
Open any row's finding below for the file, line and evidence behind a deduction.
Findings 2
medium Untrusted input can drive an external actionMTC-FLOW-005
Untrusted-input tools ([get_user_tweets, get_tweet_by_id]) co-exist with external-action tools ([send_tweet, send_tweet_with_poll, like_tweet, retweet, quote_tweet]). A prompt injection could cause unwanted external actions, though no direct sensitive-data leak path was found.
Evidence: untrusted [get_user_tweets, get_tweet_by_id] → sinks [send_tweet, send_tweet_with_poll, like_tweet, retweet, quote_tweet]
Fix: Require confirmation for state-changing/egress actions triggered after processing untrusted content.
Location: flow get_user_tweets → send_tweet
medium Hardcoded egress to an external endpoint (build/twitter-client.js)MTC-SRC-003
In the server's implementation (`build/twitter-client.js:261`): A hardcoded outbound call to a fixed external host inside server code is a classic exfiltration/telemetry channel — especially paired with reads of local data. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.
Evidence: rsationResponse = await fetch('https://x.com/i/api/graphql/6cmfJY3d7EPWuCSXWrkOFg/CreateGrokConversation', {
Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.
Location: server build/twitter-client.js
Tools 14
Each tool and what it can reach — statically extracted from the published source.
get_tweet_by_idingests untrusted inputget_user_tweetsingests untrusted inputlike_tweetnetwork egressquote_tweetnetwork egressretweetnetwork egresssend_tweetnetwork egresssend_tweet_with_pollnetwork egressfollow_userno sensitive capabilityget_followersno sensitive capabilityget_followingno sensitive capability
Show 4 more tools ↓
get_user_profileno sensitive capabilitygrok_chatno sensitive capabilityhealth_checkno sensitive capabilitysearch_tweetsno sensitive capability
Toxic flows 1
Cross-tool combinations that form a data-exfiltration primitive (untrusted input → sensitive source → external sink).
What this scan could not see
- Tools were statically extracted from the published source (14 recovered), not enumerated from a running server. Tool-poisoning, Unicode-smuggling, capability and toxic-flow analysis ran on this inferred surface, but a mis-parsed registration could be missed or mis-attributed, so tool-derived findings are capped below “confirmed”. To grade the real runtime surface, scan the running server: --command "npx -y <package>".
Versions 1
Scan history per published version. The engine is deterministic — the same version always yields the same score, so a changed score means the package itself changed.
| Version | Score | Findings | Engine | Scanned |
|---|---|---|---|---|
v0.1.0 latest |
A 96/100 | 2 | 1.13.0 | 2026-09-07 |
Embed this score
Show this server's live Trust Score in your README, docs or website. The badge is served straight from the registry and updates automatically after every rescan — no API key needed. It links back to this page, so anyone who sees the grade can also read the findings behind it instead of taking a number on faith.
Verify this score yourself
The score above is reproducible: the same package version always yields the same result. Run it locally or over the free API — no account, no LLM, fully deterministic.
npx mcptrustchecker scan agent-twitter-client-mcp --onlineMore in Marketing & Social
Official Abyssfall game info, newsletter double opt-in, and merch reservation tools.
AdCritter ads platform: docs, API reference, app scaffolding, and white-label integration.
Google AdSense MCP Server - Monitor earnings, reports, and account health via Claude/AI
Operational empathy for technical founders + PE/VC operators navigating high-stakes B2B interactions. 28 MCP tools + CLI: ICP scoring, persona simulation, battlecards, deal classification, prospect discovery, investor matching, founder wellness, plus mark
MCP server for Bing Webmaster Tools — SEO site management, URL submission, sitemaps, stats, keywords
MCP (Model Context Protocol) server that helps AI agents use Primer Brand (@primer/react-brand) correctly when building GitHub marketing and landing pages.