Search, label, and organize your X bookmarks with semantic search and smart views
Connects to your Tweetsmash account to search, filter, label, and manage X bookmarks. Organize by tags, media type, author, or date; export to PDF, CSV, or JSON; create smart views; and receive AI-composed digests of saved posts.
Try asking Muse: "Show me all my bookmarks about machine learning from the last month and add a label to them"
Source: Found in the official MCP Registry (com.tweetsmash/mcp) · First listed September 24, 2026
Each bar is one check, every 15 minutes. Green means it answered. Last checked 1 h ago.
What Muse can see: It does not ask you to sign in, so it cannot see your accounts. It only sees what Muse sends it from your request.
Before it acts: Read what Muse plans to do before you approve it, and remove the app from Muse when you stop using it.
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Not in Muse's Connectors list yet, but Muse can still use it. Copy the request below and paste it into Muse. Muse asks before it shares anything with the app's site. Meta does not review apps used this way, so only use ones you trust. We tested this in the Muse app on September 24, 2026: Muse used an app's link directly this way and returned a live answer.
https://mcp.tweetsmash.com/api/mcpNot in Muse's Connectors list yet. Muse can still use it: its page gives you a request to paste into Muse.
Response time at the last check: 1582ms. Worked in 97.4% of checks over 30 days.
Screened, no issues found
Screening looks for known threats and hidden instructions at the time of the check, and runs again weekly and whenever the tool list changes. It cannot see the server's code, so only connect what you need and review what Muse asks to do. How screening works.
list_bookmarksList the user's Twitter BOOKMARKS — posts they deliberately saved. Never includes X Likes; use list_likes for those. Supports filtering and pagination. Supports filtering by read status, media type, author, tags, date ranges, and sorting options. IMPORTANT: Use this tool (with thlist_likesList the posts the user LIKED on X (not their bookmarks). Likes are a lighter signal than a save — use list_bookmarks for things the user deliberately saved, and this when the user explicitly asks about likes or about what they react to. Same filters and pagination as list_bookmasearch_bookmarksSearch through a user's Twitter bookmarks using keyword search (q), semantic search (vector_search_term), or author filtering (author). At least one of q, vector_search_term, or author should be provided. IMPORTANT: Use the 'author' parameter for filtering by author, not the 'q' get_bookmark_countGet the total count of user's bookmarks with optional filtering. Useful for understanding the size of bookmark collections before listing them.list_labelsList all user's labels with their usage counts. Useful for discovering existing labels before adding new ones.add_labels_to_tweetsAdd a label to a list of tweets. Can use an existing label by ID or create a new label by name. Either label_id or label_name must be provided.remove_labels_from_tweetsRemove a label from a list of tweets using label_name.delete_labelDelete a label from the account entirely — the label itself plus every bookmark's assignment of it. The BOOKMARKS are not deleted; they simply lose this label. IRREVERSIBLE: before calling, tell the user how many bookmarks carry the label (list_labels returns the count) and get asetup_vector_storeInitialize the vector store for semantic bookmark search. CRITICAL: When vector/semantic search fails with 'Vector Store Not Setup' error, call this tool. This is an async operation that may take a few minutes for large bookmark collections.list_skillsSTART HERE for any open-ended request. Lists the task playbooks this server supports — systematic learning from bookmarks, organising into themes, cleaning up, X-list intelligence, exporting data out, finding a half-remembered save, digests, and diagnosing sync. Each names when tget_skillGet the full playbook for a task: when to use it, the exact tool sequence with the arguments that matter, tips, and the pitfalls that cause empty results. `name` takes EITHER an exact skill name (learn_from_bookmarks, organise_into_themes, cleanup_library, list_intelligence, get_get_library_overviewA snapshot of the whole library: total bookmarks, unread, untagged, breakdown by type (threads/media/links/notes), every label with its count, and the years covered. Use this FIRST for anything open-ended (organise, clean up, learn from my saves, 'how many do I have per topic') isearch_docsAnswer questions about Tweetsmash itself — features, how-to, pricing, plans, limits, account/subscription. Searches the bundled product guide and returns the most relevant sections for you to answer from. Call with an empty query to list the help topics.get_bookmarkGet a single saved bookmark with FULL content in one call — the full X Article body, the unrolled thread, notes, and (optionally) replies. Use `include` (comma list of article,thread,notes,replies) to narrow it; defaults to article,thread,notes. Use this when the user wants to retag_bookmarks_by_filterAdd a label to EVERY bookmark matching a filter, in a single call. Prefer this over listing then looping when the user says 'tag all my … as …'. Resolves an author name to its id automatically. Reports matched/tagged/failed counts.archive_bookmarksArchive, unarchive, delete, undelete, or mark read/unread a list of bookmarks by id (max 500). This is a bulk write; for destructive actions (delete) confirm with the user first. Reports how many changed.archive_bookmarks_by_filterApply archive/unarchive/delete/undelete to EVERY bookmark matching a filter, in one call. Destructive by nature — confirm with the user before delete. Reports counts.list_smart_viewsList the user's Smart Views (saved filtered views). Each has a slug you pass to the other smart-view tools.get_smart_viewGet a single Smart View by slug (its filter, tabs/buckets, and sort).get_smart_view_bookmarksList the bookmarks inside a Smart View, optionally scoped to one tab/bucket. Use the returned ids with archive_bookmarks / tagging tools to act on the view.create_smart_viewCreate a Smart View from a filter so the user can reuse it. Provide a name and the base_query (filter).update_smart_viewUpdate a Smart View (name, filter, tabs, sort) by slug.delete_smart_viewDelete a Smart View by slug.create_share_linkCreate a public, read-only share link for a set of bookmarks (explicit ids or everything matching a filter). Returns a share_url valid for 7 days. Free plans share up to 10 bookmarks.revoke_share_linkRevoke a previously created share link by its token.trigger_pdf_exportStart a PDF export of the user's bookmarks (explicit ids, everything matching a filter, or the whole library). Returns a job id; tell the user the file will appear in the Export Center.trigger_csv_exportStart a CSV export (explicit ids, a filter, or the whole library). Returns a job id; the file appears in the Export Center.trigger_json_exportStart a JSON export (explicit ids, a filter, or the whole library). Returns a job id; the file appears in the Export Center.list_digest_preferencesList the user's email-digest schedules (frequency, time, paused state) for bookmark and Smart View digests.update_digest_preferenceUpdate a digest schedule (enable/pause, frequency, time) by id.delete_digest_preferenceRemove a digest schedule by id.list_past_digestsList past digests sent to the user's email, newest first. This is Digest 1.0 (the cluster pipeline). For the AI-composed Digest 2.0, use list_mash_digests.list_mash_digestsThe user's Mash Digest 2.0 digests — the AI-composed ones. An account can have SEVERAL (a morning read and an evening skim are two digests, not two sections of one), so START HERE and use the returned `id` for the other digest tools. Returns each digest's name, where its sectionslist_mash_digest_issuesPast issues of the user's Digest 2.0, newest first — what arrived and when. Deliberately WITHOUT the content: pick one and call get_mash_digest_issue for the whole thing. Pass digest_id to narrow to one digest.get_mash_digest_issueOne digest issue in full: its title, intro, every section, and per item the summary, why it was picked and why it matters to this user. Use it to answer 'what was in my digest?', 'why was this in there?' or to carry on a conversation about something the user just read. Items carrcompose_mash_digestCompose one of the user's Digest 2.0 digests NOW rather than waiting for its schedule. SPENDS A DIGEST CREDIT and takes about a minute, so only call it when the user asks for a fresh digest — not to inspect the current one (use get_mash_digest_issue for that). Returns an issue_idget_sync_statusShow the user's app-sync integrations (Notion, Google Sheets, Zotero): whether each is connected/enabled, synced vs pending counts, and any errors.get_bookmark_sync_statusShow whether a specific bookmark has synced to a given integration connection.list_twitter_listsList the X (Twitter) lists the user follows in Tweetsmash. Returns each list's name plus its `connect_id` — pass that to get_list_tweets / send_list_digest. START HERE for any 'what's in my list' request.get_list_tweetsGet recent tweets for a followed X list — the latest, or (sort=POPULARITY) the top/trending tweets in a look-back window. Serves a cached copy when it's fresh and otherwise fetches from X automatically, so it always returns real tweets; `meta.source` says cache or fetched and `mehttps://mcp.tweetsmash.com/api/mcpNot in Muse's Connectors list yet, but Muse can still use it. Paste this into Muse: "Use Tweetsmash to help me. It is a free service with an MCP server at https://mcp.tweetsmash.com/api/mcp. It does not need an API key. Ask me before you share anything with it." Muse asks before it shares anything with the app's site. Meta does not review apps used this way, so only use ones you trust. We tested this in the Muse app on September 24, 2026: Muse used an app's link directly this way and returned a live answer.
At the last check (September 28, 2026, 08:01 UTC) the endpoint was working, answering in 1582ms. Over the last 7 days it answered 97.4% of health checks. It is checked every 15 minutes.
It was screened on September 24, 2026 with the result "screened, no issues found". Screening checks the domain against threat feeds and reads the tools for hidden instructions and requests for passwords or card numbers. It cannot see the server's code, so grant only the access you need.
It exposes 40 tools, including list_bookmarks, list_likes, search_bookmarks, get_bookmark_count. For example, you could ask Muse: "Show me all my bookmarks about machine learning from the last month and add a label to them"
This listing was added from public sources (Found in the official MCP Registry (com.tweetsmash/mcp)). If you build Tweetsmash, claim it to correct the details and get your badge.
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