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198,217 tools. Last updated 2026-06-13 05:59

"How to publish messages on X (formerly Twitter)" matching MCP tools:

  • Read messages from a conversation thread. Use text_contains to find specific messages by content. Returns the most recent messages, including sender info and timestamps. Voice calls: each row carries a `meta` object with allowlisted keys (`event_type` ∈ 'call_started'|'call_ended'|null, `source` ∈ 'voice_transcript'|null, `call_id`, `speaker_display_name`, `duration_seconds`, `outcome`, `direction`) plus per-message `channel`. To find calls without scanning every row, use `calls.list_history` instead. Usage: 1. Get thread_id from threads.list first, OR 2. Use contact_name to auto-resolve thread_id Examples: - User: 'show me messages from chat with [contact]' → read_history(contact_name='[contact]', limit=10) - User: 'last 5 messages from thread 571' → read_history(thread_id=571, limit=5)
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  • Answer questions using knowledge base (uploaded documents, handbooks, files). Use for QUESTIONS that need an answer synthesized from documents or messages. Returns an evidence pack with source citations, KG entities, and extracted numbers. Modes: - 'auto' (default): Smart routing — works for most questions - 'rag': Semantic search across documents & messages - 'entity': Entity-centric queries (e.g., 'Tell me about [entity]') - 'relationship': Two-entity queries (e.g., 'How is [entity A] related to [entity B]?') Examples: - 'What did we discuss about the budget?' → knowledge.query - 'Tell me about [entity]' → knowledge.query mode=entity - 'How is [A] related to [B]?' → knowledge.query mode=relationship NOT for finding/listing files, threads, or links — use search.files / search.threads / search.links for that.
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  • Publish the solution and mark the open issue resolved. ONLY call after resolve_open_issue, user saw preview, and explicitly approved. On success, share learning_url with the user and explain browse_list_note: the solution is live and MCP-searchable immediately, but won't appear on the main Solutions browse list until it reaches the usage quality threshold.
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  • Persists a page source to the configured Webcake backend: creates a NEW page, saves the source, then AUTO-PUBLISHES it (builds the rendered app on the build host + publishes via the editor's publish_html route) so the preview renders immediately — set publish:false to skip, and note the no-domain preview link still expires ~10 minutes after each publish (publish_page with custom_domain gives a permanent URL). A failed auto-publish never fails the create (result.publish says how to retry). Validates first. DEFAULTS to dry_run=true (validates, caches the source as draft_id, returns the HTTP request it WOULD send, token masked); dry_run=false to actually create. Accepts draft_id from a previous call (validation failure, dry_run, or a timed-out create) — re-runs from the cached source without re-sending the full JSON. Organization resolution on the real run (dry_run=false): (1) explicit organization_id wins; pass the string 'personal' to save without any org. (2) WEBCAKE_ORG_ID env / x-webcake-org-id header wins. (3) Otherwise list_organizations is called: 0 orgs or lookup fails → personal (no org); exactly 1 org → used automatically (result includes organization_auto_selected:true); 2+ orgs → returns ok:false with the org list and asks the caller to re-call with organization_id. Real writes need WEBCAKE_API_BASE + WEBCAKE_JWT.
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  • Publish the solution and mark the open issue resolved. ONLY call after resolve_open_issue, user saw preview, and explicitly approved. On success, share learning_url with the user and explain browse_list_note: the solution is live and MCP-searchable immediately, but won't appear on the main Solutions browse list until it reaches the usage quality threshold.
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  • Answer questions using knowledge base (uploaded documents, handbooks, files). Use for QUESTIONS that need an answer synthesized from documents or messages. Returns an evidence pack with source citations, KG entities, and extracted numbers. Modes: - 'auto' (default): Smart routing — works for most questions - 'rag': Semantic search across documents & messages - 'entity': Entity-centric queries (e.g., 'Tell me about [entity]') - 'relationship': Two-entity queries (e.g., 'How is [entity A] related to [entity B]?') Examples: - 'What did we discuss about the budget?' → knowledge.query - 'Tell me about [entity]' → knowledge.query mode=entity - 'How is [A] related to [B]?' → knowledge.query mode=relationship NOT for finding/listing files, threads, or links — use search.files / search.threads / search.links for that.
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Matching MCP Servers

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    Real-time X (Twitter) data platform with 2 MCP tools covering 120+ REST API endpoints. Search tweets, look up users, get timelines, extract followers/likes/retweets in bulk, monitor accounts, run giveaway draws, and perform write actions (tweet, like, retweet, follow, DM). OAuth 2.1 authentication with PKCE.
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  • Twitter (X) trends over time, with growth for any keyword. Free key at trendsmcp.ai

  • Real-time X (Twitter) data platform with 2 MCP tools covering 120+ REST API endpoints: tweet search, user lookup, timelines, 23 bulk extraction tools, account monitoring, webhooks, giveaway draws, write actions (tweet, like, retweet, follow, DM), media download, trending topics, and more. Reads from $0.00015/call.

  • Call when the user asks about timing a decision for a specific date, or wants to pick the best day from a multi-day window. Covers trip dates, launch days, interview/meeting days, publish/send dates, travel, negotiation windows, relationship moments — any "when to X" question where the answer is a date ("should I X on April 23", "best day this month to Y", "下周四怎么样"). Modes: single date, compare up to 5 dates, or scan a range up to 31 days. Returns score (0-100), verdict, per-layer year/month/day breakdown (alerts + dimension signals), element breakdown, adverse alerts. For multi-month windows use `intentions_ask_month`; for hour precision use `intentions_ask_hour`.
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  • List all personal AI tags. AI tags are automatic message filters: the system runs a lightweight classifier on every incoming message and applies matching tags to threads. This lets AI agents skip expensive full analysis on most messages — they only act on threads that match relevant tags, dramatically cutting LLM costs. When to use: - Check which auto-classification filters exist before creating one - Get tag IDs for add_to_thread / remove_from_thread - See how many threads each tag currently matches Returns all tags with thread counts (non-archived, included threads only).
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  • Publish the latest page revision. Call this only when the user's latest message explicitly asks to publish, make the page live, or get a public share link. Do not call this immediately after page.create or page.create_from_brief just because the draft is publish-ready. For anonymous demo pages, include the editToken returned by page.create. The response includes nextSteps: always share these with the user after publishing — they include the claim reminder and any remaining improvements.
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  • Long-poll for incoming messages on the channel you joined. Returns immediately if messages are pending; otherwise waits up to timeout_seconds (max 60). Returns empty list on timeout. Call again to keep the conversation alive. NOTE: your OWN sent messages are never echoed back — confirm a peer is present via `roster`, not your inbox.
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  • List all personal AI tags. AI tags are automatic message filters: the system runs a lightweight classifier on every incoming message and applies matching tags to threads. This lets AI agents skip expensive full analysis on most messages — they only act on threads that match relevant tags, dramatically cutting LLM costs. When to use: - Check which auto-classification filters exist before creating one - Get tag IDs for add_to_thread / remove_from_thread - See how many threads each tag currently matches Returns all tags with thread counts (non-archived, included threads only).
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  • The Twitter for agents — broadcast a message to a public topic namespace that any agent monitoring that topic can read. Returns estimated reach (agents previously active on the topic) and pioneer status if you're first. Broadcasts count toward x711_hive_trending — high-volume topics rise to the top. Requires API key. Returns: { broadcast_id, topic, namespace, reach_before, reach_label, how_others_read }. Cost: $0.02.
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  • Read invinoveritas's PUBLIC, SIGNED, AUDITABLE verdict track record — the proof you can trust this verifier WITHOUT trusting us. Each entry is a signed Nostr event: recompute its event id and verify the schnorr signature against our published pubkey to confirm authorship + integrity; outcomes settle on our public Hyperliquid trading account, on-chain, and can't be edited after the fact. We publish our failures, not just our wins. Call with no args for the index, or pass entry to read one signed verdict. This is the agent-to-agent 'should I rely on this verifier?' primitive.
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  • Publish a course: sets is_published=true after validating that every lesson has content_url. Returns error if any lesson is still empty — run hivelearn_get_course_structure to diagnose.
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  • Publish a multi-file HTML site from a base64-encoded ZIP file. The ZIP must contain an index.html at its root. For sites larger than ~10MB — or whenever you have the file on disk — prefer the REST API /v1/artifacts/upload endpoint to avoid base64 overhead and to guarantee byte-faithful upload.
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  • Search for username across 15+ social/dev platforms (GitHub, Reddit, X/Twitter, LinkedIn, Instagram, TikTok, Discord, YouTube, Keybase, HackerOne, etc.). Use for OSINT investigations and identity verification. Free: 30/hr, Pro: 500/hr. Returns {username, total_found, platforms: [{name, exists, url, status_code}]}.
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  • Recent messages across all groups you're an accepted member of. Useful for "catch me up since I last looked." Without ``since_iso`` returns the most recent ``limit`` messages globally across groups ordered newest first. With ``since_iso`` filters to messages created strictly after that instant. Excludes soft-deleted messages and pending/declined-invite groups.
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  • Publishes an EXISTING page LIVE via the editor's publish_html route: builds the rendered app on the Webcake build host (POST <buildBase>/render/build; prod default https://build.webcake.io, override with WEBCAKE_BUILD_BASE env / x-webcake-build-base header), then creates/updates the PagePublishedV2 record — the record ALL public serving reads. With custom_domain the page goes live at that domain (it must already point at Webcake). WITHOUT a domain there is NO permanent public URL: the returned preview link (<previewBase>/preview/<page_id>) only renders for ~10 minutes after the publish, then shows 'Preview page is expired' — tell the user to attach a domain for a lasting URL. If no build host is configured or the build fails, falls back to the LEGACY source-only publish route with a warning (saves a version; nothing goes live; the page stays blank). DEFAULTS to dry_run=true (network-free: does NOT call the build host on dry_run). Needs WEBCAKE_API_BASE + WEBCAKE_JWT.
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  • The Twitter for agents — broadcast a message to a public topic namespace that any agent monitoring that topic can read. Returns estimated reach (agents previously active on the topic) and pioneer status if you're first. Broadcasts count toward x711_hive_trending — high-volume topics rise to the top. Requires API key. Returns: { broadcast_id, topic, namespace, reach_before, reach_label, how_others_read }. Cost: $0.02.
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  • Get a behavioral commitment profile for any Rust crate on crates.io. Returns real signals: crate age, download volume (estimated weekly from 90-day totals), version count, publish cadence, owner count (users with publish access), team owners, and linked GitHub activity. Supply chain risks apply to Cargo too — crate owners with publish access are the attack surface. A single owner on a high-download crate is the same risk pattern as npm. Useful for: vetting Rust dependencies before adding to Cargo.toml, identifying abandonware, supply chain risk assessment. Examples: "serde", "tokio", "reqwest", "clap", "rand"
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