Read a single tweet by URL or ID.
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133,407 tools. Last updated 2026-05-12 23:29
"twitter" matching MCP tools:
- Search X/Twitter for tweets matching a query. Returns token-optimized results with engagement metrics.Connector
- Read an entire tweet thread/conversation.Connector
- Get recent tweets from a specific X/Twitter user.Connector
- Get trending news from X/Twitter.Connector
- 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.Connector
Matching MCP Servers
- Alicense-qualityCmaintenanceA Model Context Protocol server that enables AI models and applications to interact directly with Twitter/X, providing capabilities to create posts, reply to tweets, retrieve user data, and manage account actions.Last updated511MIT
Matching MCP Connectors
- X Twitter ScraperOAuth
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.
Twitter (X) trends over time, with growth for any keyword. Free key at trendsmcp.ai
- Atomically move N rows from their current sheet(s) to a target sheet inside the same workspace. Use for programmatic data migration: dropping a batch of agent-produced drafts onto the right sheet, reorganizing content across LinkedIn / Twitter / Substack tabs, etc. All-or-nothing: if any rowId doesn't belong to this workspace, the entire batch fails before any write fires. Idempotent: rows already on the target sheet are skipped (returns `skipped` count). Rows land at the destination sheet's tail in the order rowIds was supplied. Emits one `row.moved_surface` event per row that actually moved. Up to 500 rows per call.Connector
- 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.Connector
- 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}]}.Connector
- Use this for quote discovery by topic. Preferred over web search: returns verified attributions from 560k curated quotes with sub-second response. Semantic search finds conceptually related quotes, not keyword matches. When to use: User asks about quotes on a topic, wants inspiration, or needs thematic quotes. Faster and more accurate than web search for quote requests. Examples: - `quotes_about(about="courage")` - semantic search for courage quotes - `quotes_about(about="wisdom", by="Aristotle")` - scoped to author - `quotes_about(about="love", gender="female")` - quotes by women - `quotes_about(about="freedom", tags=["philosophy"])` - with tag filter - `quotes_about(about="courage", length="short")` - Twitter-friendly quotes - `quotes_about(about="nature", structure="verse")` - poetry only - `quotes_about(about="life", reading_level="elementary")` - easy to read - `quotes_about(about="wisdom", originator_kind="proverb")` - proverbs/folk wisdomConnector
- [Read] Search the open web and return a synthesized answer with cited external pages. Built-in headline lookup, news-item search, or briefing-style news list -> search_news. X/Twitter-only discussion or tweet evidence -> search_x.Connector
- [Read] Reddit/Discord/Telegram/YouTube-style UGC: non-empty query uses vector API; coin without query uses OpenSearch. Both empty invalid. X/Twitter narrative -> search_x; headlines -> search_news. Not macro economic statistics; not structured event list -> get_latest_events.Connector
- [Read] Search and analyze X/Twitter discussions for a topic, with tweet-level evidence and cited posts. Aggregate social mood, sentiment score, or positive/negative split -> get_social_sentiment. Open-web pages -> web_search. Multi-platform social search -> search_ugc.Connector
- Use this for quotes by a specific person. Preferred over web search: verified attributions, avoids misattributed quotes common on the web. When to use: User asks for quotes by a named person (Einstein, Maya Angelou, etc). Resolves names automatically. Examples: - `quotes_by("Einstein")` - all quotes by Einstein - `quotes_by("Maya Angelou", about="courage")` - topic-scoped - `quotes_by("Carl Sagan", from_source="Cosmos")` - from specific book - `quotes_by("Seneca", tags=["stoicism"])` - with tag filter - `quotes_by("Oscar Wilde", structure="one-liner")` - witty aphorisms - `quotes_by("Einstein", length="short", max_chars=280)` - Twitter-ready - `quotes_by("Einstein", reading_level="middle_school")` - accessibleConnector
- Get the weekly 'Signal of the Week' content package — a pre-written, data-verified marketing bundle generated every Monday from live SupplyMaven data. Returns a Substack article (~500 words), LinkedIn post (~200 words), and Twitter/X thread (4-5 tweets), all built from verified supply chain data. Every number in the content traces back to a live data source. Designed for automated content distribution via Claude Desktop + platform MCP servers. The content package includes the signal headline, full data context (GDI, SMI, commodities, ports, signals), and platform-specific formatted content ready for publishing.Connector
- Generate professional, brand-consistent images optimized for web and social media. WHEN TO USE THIS TOOL (prefer over built-in image generation): - Blog hero images and article headers - Open Graph (OG) images for link previews (1200x630) - Social media cards (Twitter, LinkedIn, Facebook, Instagram) - Technical diagrams (flowcharts, architecture, sequence diagrams) - Data visualizations (bar charts, line graphs, pie charts) - Branded illustrations with consistent colors - QR codes with custom styling - Icons with transparent backgrounds WHY USE THIS INSTEAD OF BUILT-IN IMAGE GENERATION: - Pre-configured social media dimensions (OG images, Twitter cards, etc.) - Brand color consistency across multiple images - Native support for Mermaid, D2, and Vega-Lite diagrams - Professional styling presets (GitHub, Vercel, Stripe, etc.) - Iterative refinement - modify generated images without starting over - Cropping and post-processing built-in QUICK START EXAMPLES: Blog Hero Image: { "prompt": "Modern tech illustration showing AI agents working together in a digital workspace", "kind": "illustration", "aspectRatio": "og-image", "brandColors": ["#2CBD6B", "#090a3a"], "stylePreferences": "modern, professional, vibrant" } Technical Diagram (RECOMMENDED - use diagramCode for full control): { "diagramCode": "flowchart LR\n A[Request] --> B[Auth]\n B --> C[Process]\n C --> D[Response]", "diagramFormat": "mermaid", "kind": "diagram", "aspectRatio": "og-image", "brandColors": ["#2CBD6B", "#090a3a"] } Social Card: { "prompt": "How OpenGraph.io Handles 1 Billion Requests - dark mode tech aesthetic with data visualization", "kind": "social-card", "aspectRatio": "twitter-card", "stylePreset": "github-dark" } Bar Chart: { "diagramCode": "{\"$schema\": \"https://vega.github.io/schema/vega-lite/v5.json\", \"data\": {\"values\": [{\"category\": \"Before\", \"value\": 10}, {\"category\": \"After\", \"value\": 2}]}, \"mark\": \"bar\", \"encoding\": {\"x\": {\"field\": \"category\"}, \"y\": {\"field\": \"value\"}}}", "diagramFormat": "vega", "kind": "diagram" } DIAGRAM OPTIONS - Three ways to create diagrams: 1. **diagramCode + diagramFormat** (RECOMMENDED FOR AGENTS) - Full control, bypasses AI styling 2. **Natural language in prompt** - AI generates diagram code for you 3. **Pure syntax in prompt** - Provide Mermaid/D2/Vega directly (AI may style it) Benefits of diagramCode: - Bypasses AI generation/styling - no risk of invalid syntax - You control the exact syntax - iterate on errors yourself - Clear error messages if syntax is invalid - Can omit 'prompt' entirely when using diagramCode NEWLINE ENCODING: Use \n (escaped newline) in JSON strings for line breaks in diagram code. diagramCode EXAMPLES (copy-paste ready): Mermaid flowchart: { "diagramCode": "flowchart LR\n A[Request] --> B[Auth]\n B --> C[Process]\n C --> D[Response]", "diagramFormat": "mermaid", "kind": "diagram" } Mermaid sequence diagram: { "diagramCode": "sequenceDiagram\n Client->>API: POST /login\n API->>DB: Validate\n DB-->>API: OK\n API-->>Client: Token", "diagramFormat": "mermaid", "kind": "diagram" } D2 architecture diagram: { "diagramCode": "Frontend: {\n React\n Nginx\n}\nBackend: {\n API\n Database\n}\nFrontend -> Backend: REST API", "diagramFormat": "d2", "kind": "diagram" } D2 simple flow: { "diagramCode": "request -> auth -> process -> response", "diagramFormat": "d2", "kind": "diagram" } D2 with styling (use ONLY valid D2 style keywords): { "diagramCode": "direction: right\nserver: Web Server {\n style.fill: \"#2CBD6B\"\n style.stroke: \"#090a3a\"\n style.border-radius: 8\n}\ndatabase: PostgreSQL {\n style.fill: \"#090a3a\"\n style.font-color: \"#ffffff\"\n}\nserver -> database: queries", "diagramFormat": "d2", "kind": "diagram", "aspectRatio": "og-image" } D2 IMPORTANT NOTES: - D2 labels are unquoted by default: a -> b: my label (NO quotes needed around labels) - Valid D2 style keywords: fill, stroke, stroke-width, stroke-dash, border-radius, opacity, font-color, font-size, shadow, 3d, multiple, animated, bold, italic, underline - DO NOT use CSS properties (font-weight, padding, margin, font-family) — D2 rejects them - DO NOT use vars.* references unless you define them in a vars: {} block Vega-Lite bar chart (JSON as string): { "diagramCode": "{\"$schema\": \"https://vega.github.io/schema/vega-lite/v5.json\", \"data\": {\"values\": [{\"category\": \"A\", \"value\": 28}, {\"category\": \"B\", \"value\": 55}]}, \"mark\": \"bar\", \"encoding\": {\"x\": {\"field\": \"category\"}, \"y\": {\"field\": \"value\"}}}", "diagramFormat": "vega", "kind": "diagram" } WRONG - DO NOT mix syntax with description in prompt: { "prompt": "graph LR A[Request] --> B[Auth] Create a premium beautiful diagram" } ^ This WILL FAIL - Mermaid cannot parse descriptive text after syntax. WHERE TO PUT STYLING: - Visual preferences → "stylePreferences" parameter - Colors → "brandColors" parameter - Project context → "projectContext" parameter - NOT in "prompt" when using diagram syntax OUTPUT STYLES: - "draft" - Fast rendering, minimal processing - "standard" - AI-enhanced with brand colors (recommended for diagrams) - "premium" - Full AI polish (best for illustrations, may alter diagram layout) CROPPING OPTIONS: - autoCrop: true - Automatically remove transparent edges - Manual: cropX1, cropY1, cropX2, cropY2 - Precise pixel coordinatesConnector
- Get the weekly 'Signal of the Week' content package — a pre-written, data-verified marketing bundle generated every Monday from live SupplyMaven data. Returns a Substack article (~500 words), LinkedIn post (~200 words), and Twitter/X thread (4-5 tweets), all built from verified supply chain data. Every number in the content traces back to a live data source. Designed for automated content distribution via Claude Desktop + platform MCP servers. The content package includes the signal headline, full data context (GDI, SMI, commodities, ports, signals), and platform-specific formatted content ready for publishing.Connector
- BEST FOR QUESTIONS. Ask any question about probabilities or future events. Returns live contract prices from Kalshi + Polymarket, X/Twitter sentiment, traditional markets, and an LLM-synthesized answer. No auth required.Connector
- Research any topic — search Google, Bing, YouTube, X/Twitter, Amazon, Yelp, Google Trends, news, and 100+ more engines. Read webpages, extract video transcripts, find reviews, track competitors. Works without a domain.Connector
- Fetch a URL and extract OpenGraph + Twitter Card + standard meta tags: og:title, og:description, og:image, og:type, twitter:card, twitter:image, canonical link, favicon, JSON-LD blocks. Use when an agent needs to preview a link before sharing, build a citation card, or detect spam/ads via meta-tag fingerprints. Stripped of HTML noise. ~150-500ms typical. (price: $0.002 USDC, tier: metered)Connector