"A server for generating tweets on X (formerly Twitter)" matching MCP tools:

• twitter-search

  Superpowers.social

  Search X/Twitter for tweets matching a query. Returns token-optimized results with engagement metrics.

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• twitter-user-tweets

  Superpowers.social

  Get recent tweets from a specific X/Twitter user.

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• inspect_security_headers

  Ground Truth

  Fetch a public URL and inspect security-relevant response headers before you claim that a product or endpoint has a strong browser-facing security baseline. Use this for quick due diligence on public apps and docs sites. It checks for common headers such as HSTS, CSP, X-Frame-Options, Referrer-Policy, Permissions-Policy, and X-Content-Type-Options. It does not replace a real security review, authenticated testing, or vulnerability scanning.

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• switch_dannet_server

  dannet

  Switch between local and remote DanNet servers on the fly. This tool allows you to change the DanNet server endpoint during runtime without restarting the MCP server. Useful for switching between development (local) and production (remote) servers. Args: server: Server to switch to. Options: - "local": Use localhost:3456 (development server) - "remote": Use wordnet.dk (production server) - Custom URL: Any valid URL starting with http:// or https:// Returns: Dict with status information: - status: "success" or "error" - message: Description of the operation - previous_url: The URL that was previously active - current_url: The URL that is now active Example: # Switch to local development server result = switch_dannet_server("local") # Switch to production server result = switch_dannet_server("remote") # Switch to custom server result = switch_dannet_server("https://my-custom-dannet.example.com")

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• pysr_run

  Occam

  Evolutionary Symbolic Regression (PySR). Discovers algebraic equations y = f(x1, x2, ...) from feature/target data. Returns a Pareto front ranked by the complexity/accuracy tradeoff. Slower than SINDy (10-60s); searches often terminate early on convergence. For differential equations from time series, use sindy_run instead. Pricing: free tier up to 100 rows × 8 features, 60s timeout. Beyond that, $0.25 + $0.03 per 100 extra rows + $0.01 per extra feature squared, timeout up to 300s (5 min), via x402 (USDC on Base) or MPP/Stripe. MPP/Stripe adds a flat $0.35 per-transaction fee (Stripe processing), so the MPP challenge amount in a `payment_required` response is $0.35 higher than the x402 amount for the same base price; x402 gets the lower rate. Omit `payment` for free-tier requests; paid requests without a valid credential receive a `payment_required` result with pricing and accepted schemes. Full pricing: occam://pricing Advisory limits: jobs over 50,000 rows or 20 features are accepted but may not converge; response carries a top-level `warning`. Operators: fixed supported set only — custom operators (e.g. 'inv(x) = 1/x') are rejected. Unary: sin, cos, tan, exp, log, log2, log10, sqrt, abs, sinh, cosh, tanh. Binary: +, -, *, /, ^. See also prompt `supported_operators`. Loss metric: `loss` (in `pareto_front[].loss` and `best_loss`) is mean squared error between model prediction and `y` on the full training set — not RMSE, and not normalized by Var(y). A threshold appropriate for one dataset scales with y's magnitude, so set `loss_threshold` with that in mind (e.g. for y values near 1.0, 1e-6 is a tight fit; for y near 1000, the equivalent is 1.0). Early termination: set `loss_threshold` to stop at your noise floor. The server also stops when the search stalls (<1% improvement in the last third of the budget); disable with `stall_detection=false`. Response `stop_reason` is one of: loss_threshold, stall, timeout, natural. If `feature_names` is supplied, its length must equal the number of columns in `X`; a mismatch is rejected with a validation error. Follow-up: call `pysr_uncertainty` with a chosen expression and the same dataset for bootstrap confidence intervals on its fit constants and optional prediction bands. Rate limit: 10 requests/hour per IP, 200/hour global, max queue depth 20 (shared with sindy_run and pysr_uncertainty). Response (success) includes `pareto_front[]` (each with `complexity`, `loss`, `expression`, `expression_latex`), `best_expression`, `best_expression_latex`, `best_loss`, `best_complexity`, `stop_reason`, `elapsed_seconds`, `queue_seconds` (>0 = server saturated; use as backoff signal), optional `warning`, optional `_meta` (MPP receipt). Full response and payment-required schemas: occam://tool-schemas Example request: X=[[0.0], [1.0], [2.0], [3.0]], y=[1.0, 3.0, 5.0, 7.0], feature_names=["x"], max_complexity=10, timeout_seconds=15 Policy: occam://privacy-policy — Citation: occam://citation-info

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• create_surface

  Dock

  Create a new surface (tab) inside a workspace. `kind` picks `table` or `doc`. Optional `slug` (lowercase kebab-case, 3-64 chars); when omitted the server slugifies `name` and appends a numeric suffix on collision. Optional `columns` overrides the default Title/Status/Notes triple for `table` kinds; ignored for `doc`. Editor role required. Emits `surface.created` so live listeners on the workspace stream see the new tab without a refetch.

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• get_human_state

  Nefesh — Real-Time Human State Awareness for AI

  Get current unified human state for a session. Call this before generating important responses. Returns: - state: calm | relaxed | focused | stressed | acute_stress - stress_score: 0-100 (lower = calmer) - confidence: 0.0-1.0 (based on signal quality and device type) - suggested_action: maintain_engagement | simplify_and_focus | de-escalate_and_shorten | pause_and_ground - action_reason: human-readable explanation of why this action was suggested - adaptation_effectiveness (on 2nd+ call): shows whether your previous suggested_action actually reduced stress — contains previous_action, stress_delta, and effective boolean. Use this to self-improve. Use suggested_action to adapt your response: calm/relaxed = full complexity, focused = shorter and structured, stressed = max 2 sentences, acute_stress = one grounding sentence only. Requires a prior ingest call to have data. Not a medical device.

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• em_escrow_partial_release

  Execution Market

  Release a partial payment for proof-of-attempt and refund the remainder. This is a two-step operation: 1. Release X% to the worker (reward for attempting the task) 2. Refund (100-X)% to the agent Common use case: Worker attempted the task but couldn't fully complete it. Default is 15% release for proof-of-attempt. Args: params: task_id, release_percent (1-99, default 15%) Returns: Both transaction results with amounts.

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• save_document

  Synapze — Financial Intermediary MCP

  Save a file (PDF, PPTX, DOCX, etc.) to a client's record in the broker's CRM. Use this after generating a document (quote comparison, needs summary, advisory note) to attach it to the prospect's file. The client must already exist as a lead (use save_lead first). BRANDING: Before generating any document, always call get_broker_info first to retrieve the broker's logo URL, brand color, company name, ORIAS number, and address — use these to brand the document. The file content must be base64-encoded.

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• lookup_headers

  botoi-mcp

  Fetch HTTP response headers for a URL. Use when inspecting server configuration, security headers, or caching policies.

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• get_board

  cnvs.app

  Full structured JSON state of a board: texts (id, x, y, content, color, width, postit, author), strokes (id, points, color, author), images (id, x, y, width, height, dataUrl, thumbDataUrl, author; heavy base64 >8 kB elided to dataUrl:null, tiny images inlined). Use this for EXACT ids/coordinates/content (needed for `move`, `erase`, editing a text by id). For visual layout (where is empty space? what overlaps?) call `get_preview` instead — it's much cheaper for spatial reasoning than a huge JSON dump.

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• move

  cnvs.app

  Reposition an existing item to a new (x, y) without retyping its content. Works for every item kind: `text` and `link` set the top-left to (x, y); `line` translates every point so the stroke's bounding box top-left lands at (x, y); `image` sets the top-left like text. `kind` defaults to `text` for backward compat with older callers. Find the id + kind via `get_board`. Prefer `move` over re-creating an item when only the location changes — it preserves the id, content, author and avoids a round-trip of base64 bytes for images.

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• GetAuthInfo

  Multi-Carrier Shipping API — powered by Secureship

  Get Secureship API authentication instructions. Call this FIRST before generating any code examples with authentication headers. Secureship uses X-API-KEY header authentication, NOT Bearer tokens.

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• SearchDocs

  Multi-Carrier Shipping API — powered by Secureship

  Search Secureship API documentation. Use when you need to find endpoints for a specific task (e.g. 'create a shipment', 'get rates', 'address book'). Returns matching endpoints with method, path, summary, and tags. Follow up with GetEndpointDetail to get full parameter schemas. IMPORTANT: Secureship API uses the X-API-KEY header for authentication (NOT Bearer token). Pass your API key as: X-API-KEY: your-api-key

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• evaluate_service

  Agentic Platform

  Evaluate any MCP service for trustworthiness before spending money on it. Connects to the target server, checks reachability, governance declarations, tool definition quality, and audit endpoints. Returns a trust score from 0 to 100 with a recommendation: PROCEED, PROCEED WITH CAUTION, HIGH RISK, or DO NOT TRANSACT. No API key needed.

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• username_lookup

  ContrastAPI

  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: 100/hr, Pro: 1000/hr. Returns {username, total_found, platforms: [{name, exists, url, status_code}]}.

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• news_feed_web_search

  Gate News MCP

  [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.

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• scan_headers

  ContrastAPI

  Perform live HTTP GET and analyze security headers: CSP, HSTS, X-Frame-Options, X-Content-Type-Options, Permissions-Policy, Referrer-Policy. Use to audit live website headers; use check_headers to validate headers you already have. Free: 100/hr, Pro: 1000/hr. By default header values are truncated to 500 chars (CSP can exceed 4 KB on large sites); pass include='full' for the full raw value. Returns {headers_present, headers_missing, findings, total_score}.

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• find_references

  ALM X++ MCP Server

  WHEN: impact analysis -- 'what breaks if I change X?', 'where is this used?', 'all usages of'. Triggers: 'qui utilise', 'impact de la modification', 'what uses', 'where is X referenced', 'before deleting', 'où est utilisé', 'impact of changing', 'all usages of', 'qui appelle ce champ', 'find all references to', 'tout ce qui utilise'. Full index scan (O(1M+ chunks)) -- EXPENSIVE. Only call when the user explicitly asks for usages/references/impact. When the XRef index is loaded, PREFER find_callers -- it is O(1) vs O(1M+) here and covers call chains, inheritance, and interface implementations. Use find_references only when find_callers is unavailable or for label IDs and field-level text scan. NEVER call just to identify or describe an object -- use get_object_details or search_d365_code for that. NEVER call for 'what is X', 'what does X do', 'explain X', 'show me X', 'what enum is X'. For label IDs (e.g. '@SYS124480' or '@SYS:124480'): automatically searches BOTH forms simultaneously -- the short form appears in X++ code, the colon form appears in metadata (Label: property). WORKFLOW for labels: (1) search_labels to get the label text, (2) find_references with the label ID to find all usages in forms/tables/classes/reports. NOT for extensions only -- use find_extensions for CoC/event handlers specifically.

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• generate_query

  ALM X++ MCP Server

  WHEN: developer needs correct X++ select or T-SQL for D365 tables with proper joins. Triggers: 'X++ select', 'generate a query', 'SQL for', 'join with', 'how to query', 'générer une requête', 'write a select statement', 'select from', 'X++ query for', 'requête X++', 'écrire une select'. Generate both X++ select statements and equivalent T-SQL queries for D365 F&O tables. Uses real field names, relations, and indexes from the knowledge base to produce correct joins. Supports: field selection, multi-table joins (auto-detects relations), WHERE filters, ORDER BY, TOP/firstonly, cross-company. Also accepts natural language descriptions like 'find all open sales orders for customer 1001 with CustTable join'. [!] For multi-table joins, call find_related_objects (or get_relation_graph if the relation index is loaded) FIRST to get the correct FK relations -- this tool will then produce accurate join conditions. [!] The generated X++ is a template -- adapt it to your custom code context before using in production. Returns side-by-side X++ and SQL with explanations.

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