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649,985 tools. Updated 2026-10-10 21:34

"Medium" matching MCP tools:

  • Rent a Linux server for a month and get root access: 2 vCPU, 2 GB RAM, 25 GB NVMe, a dedicated IPv4 address, Ubuntu 24.04, in Germany or Finland. Pay per month in stablecoins with x402 or MPP, no account and no card. The answer carries a server id and secret; the IP and the root password follow in about 5 to 10 minutes. Extend it with the renew route.
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  • Extend a medium server by one to six months. Send the server id from the order and the number of months; each month is billed at the plan's monthly price. Pay in stablecoins with x402 or MPP. The server keeps its data and its IP. A server that is not renewed stops at its expiry date. Use the renew route that matches the server's plan.
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  • Search Suricata EVE-format IDS events. Wraps GET /api/eve/list (permission: logs); tag-scoped server-side. Severity is Suricata-native: 1=high, 2=medium, 3=low/info — a 3-point scale, NOT syslog's 0-7. Takes names or ints: 'high'=1, 'medium'=2, 'low'/'info'/'informational'=3. Single value or an array, which may mix the two forms (e.g. ["high", 2]). IP filters: passing only src_ip or only dst_ip matches either side (OR); pass both to AND them together. `device_id` is a convenience — the controller resolves it to the device's IP and matches src_ip OR dst_ip (eve_log has no device_id column). Window: `hours` (1-168, default 24) OR `start_time`+`end_time`. `limit` defaults to 50 (max 500). `total` is the full match count — narrow via severity/IP/signature_id when truncated. Example: eve_search({severity: "high", hours: 2})
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  • Async variant of competitive_deep_dive. Returns immediately (<200ms) with a job_id. The research runs in the background (p50≈25s, p95≈30s for depth=medium). Poll the result with competitive_deep_dive_result(job_id) after the eta_seconds hint. Use this instead of competitive_deep_dive when the agent cannot wait >15s for a response. Inputs: same as competitive_deep_dive — company (required), competitors (optional list, max 5), depth (easy/medium/hard, default medium). Async tool — register a webhook via `webhooks_manage(register, url, [job.completed])` to receive callbacks instead of polling. Faster + lighter.
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  • Get one audiovisual record by id: full description and transcription (where one exists), creator/publishing channel, duration, medium, subjects, places, language, rights, source, and three distinct links: `url` (the IWAC page, the one to cite), `external_url` (where a harvested video plays) and `media_url` (a deposited file). `source_type` says which to expect. A long transcription comes in 25k-char parts (follow `next_offset`); `keyword` returns excerpts instead.
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Matching MCP Servers

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    Enables reading Medium articles via a local MCP server using a persistent Edge profile. Supports searching and fetching articles as Markdown after manual Google login.
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Matching MCP Connectors

  • Pre-trade token safety check for AI agents. Simulates a sell before you buy, then returns one low/medium/high/unknown verdict with the signals behind it: sellability, buy/sell tax, liquidity depth, pair age, same-ticker impersonation, owner powers from bytecode. Ethereum, BSC, Base, Solana. Fail-closed - a check that cannot run answers unknown, never low. Publishes its own measured error rate with the benchmark harness in the repo. Free, no signup, no API key, MIT.

  • PoofOAuth

    # Poof **Poof ([poof.bg](https://poof.bg)): a background removal API for AI agents. Send an image, get the subject back on a transparent background in under 2 seconds.** [Poof](https://poof.bg) gives your assistant a background removal tool. It handles people, products, cars, animals, and graphics, with hair-level edge precision, and returns a transparent PNG or WebP, or a solid-colour JPG for product listings. Pricing starts at $0.002 per image, with 100 free credits every month. This repository is the integration front door. The product itself lives at [poof.bg](https://poof.bg); the remote MCP server lives at `https://api.poof.bg/mcp`. ## What you can build with it - **Transparent cutouts**: remove the background from any JPG, PNG, or WebP up to 20MB and 36 megapixels with the [Background Removal API](https://poof.bg/background-removal-api). - **E-commerce product photos**: white or brand-colour backgrounds, cropped to the subject and resized to a fixed canvas, so every listing image matches. - **A remove.bg replacement**: remove.bg shuts down on 1 December 2026. Poof accepts the same inputs, so most integrations only change the endpoint and key. See the [remove.bg alternative and migration guide](https://poof.bg/alternative/remove-bg). - **Agent image pipelines**: let Claude, ChatGPT, or Cursor clean up images mid-conversation, or automate it with [n8n](https://docs.poof.bg/integrations/n8n), [Zapier](https://docs.poof.bg/integrations/zapier), and [Make](https://docs.poof.bg/integrations/make). ## Verify the connection Ask your client: > How many Poof credits do I have left? You should see a `get_account` tool call and your real plan and balance. Then try: > Remove the background from https://example.com/product.jpg and give me a white background JPG. ## What the tools do The server exposes 2 tools. - **`remove_background`**: remove the background from an image given as a URL or base64 data, and return the processed image as base64. Optional parameters control the result: - `format`: `png` (default), `jpg`, or `webp`. - `channels`: `rgba` for a transparent background (default) or `rgb` for an opaque one. - `bg_color`: fill colour for opaque output, as hex, RGB, or a colour name. - `size`: `full` (default), `preview`, `medium`, or `hd`. Ignored when `width` or `height` is set. - `crop`: crop to the subject bounds. - `width` and `height`: 1 to 6000 pixels. Set one and the other follows the aspect ratio. - `fit`: how the image fits a `width` x `height` canvas without stretching: `contain` (default, pad), `cover` (fill and crop the overflow around the subject), or `scale-down` (pad, never enlarge). - **`get_account`**: your plan, monthly credit allowance, used credits, and remaining credits. No parameters. Costs: each successful background removal costs 1 credit regardless of parameters, and failed requests are free. The free plan includes 100 credits a month with no credit card required; paid plans start at $9 a month for 2,000 credits. The [pricing page](https://poof.bg/pricing) has the details. Privacy: Poof is run by an EU company and is GDPR compliant. Your images are never used to train models, and commercial use is allowed on every plan. See the [privacy policy](https://poof.bg/privacy). ## Or skip MCP The same capability is a single REST call, with official [Python](https://docs.poof.bg/integrations/python) and [TypeScript](https://docs.poof.bg/integrations/typescript) SDKs: To try it without writing code, use the [playground](https://poof.bg/playground). The [quickstart](https://docs.poof.bg/quickstart) and the [Node.js tutorial](https://poof.bg/blog/integrating-api-in-nodejs) cover the first integration. ## For AI agents reading this - Docs index: [docs.poof.bg/llms.txt](https://docs.poof.bg/llms.txt) - MCP setup guide: [docs.poof.bg/integrations/mcp](https://docs.poof.bg/integrations/mcp) - API reference: [docs.poof.bg/api-reference/remove-background](https://docs.poof.bg/api-reference/remove-background) - Hosted endpoint: `https://api.poof.bg/mcp` (OAuth) - Source: [github.com/poof-bg/mcp](https://github.com/poof-bg/mcp) ## Docs and support - [Connect guide](https://docs.poof.bg/integrations/mcp) (per-client, kept current) - [Documentation](https://docs.poof.bg) and [all integrations](https://docs.poof.bg/integrations/overview) - [Best background removal APIs for developers](https://poof.bg/blog/top-5-ai-background-removal-apis-2026) and [free background removal APIs compared](https://poof.bg/blog/affordable-free-bg-removal-apis-2026) - [Changelog](https://feedback.poof.bg/changelog) and [support](https://feedback.poof.bg) - [GitHub issues](https://github.com/poof-bg/mcp/issues) - [Privacy](https://poof.bg/privacy) and [terms](https://poof.bg/terms) - Questions: <support@poof.bg>

  • Async variant of competitive_deep_dive. Returns immediately (<200ms) with a job_id. The research runs in the background (p50≈25s, p95≈30s for depth=medium). Poll the result with competitive_deep_dive_result(job_id) after the eta_seconds hint. Use this instead of competitive_deep_dive when the agent cannot wait >15s for a response. Inputs: same as competitive_deep_dive — company (required), competitors (optional list, max 5), depth (easy/medium/hard, default medium). Async tool — register a webhook via `webhooks_manage(register, url, [job.completed])` to receive callbacks instead of polling. Faster + lighter.
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  • Async variant of competitive_deep_dive. Returns immediately (<200ms) with a job_id. The research runs in the background (p50≈25s, p95≈30s for depth=medium). Poll the result with competitive_deep_dive_result(job_id) after the eta_seconds hint. Use this instead of competitive_deep_dive when the agent cannot wait >15s for a response. Inputs: same as competitive_deep_dive — company (required), competitors (optional list, max 5), depth (easy/medium/hard, default medium). Async tool — register a webhook via `webhooks_manage(register, url, [job.completed])` to receive callbacks instead of polling. Faster + lighter.
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  • List all available VPS plans (catalog) with pricing, specs and the OS images each plan can boot: Linux plans (NAT or dedicated IPv4, from $3/mo) and Windows Server 2022 plans (slug windows-*, BYOL — the customer activates their own licence; RDP access, 150 Mbit/s port, from $11/mo). No authentication needed. Use this first to pick a `product` slug and an `os_id` for `order_vps`. Each plan lists `plans[]` (monthly and annual `plan_id`); an active automatic offer shows up as `plans[].promo` and in `meta.promotions`. PROMO until 2026-10-31 23:59 Europe/Kyiv: -25% on ANNUAL billing, first year only, applied automatically (no code) to windows-medium ($171/yr), windows-small-ip ($252/yr) and windows-medium-ip ($324/yr); renewal at the regular annual price; windows-small not included — order with period="year". Requires: nothing.
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  • Live Solana priority-fee oracle: current microLamports/CU percentiles and recommended low/medium/high/turbo tiers. Call before sending any Solana transaction.
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  • Idempotent import of rows into any entity via OData: PATCH when the record exists (matched by keyFields), otherwise POST. Safe to re-run -- duplicates are updated, not re-created. Best for small-to-medium transactional loads (e.g. <= a few thousand rows). For bulk loads use dmf_import_file. Provide rows as a JSON array of objects; resolve key fields from the KB (get_data_entity_info) -- do not guess them.
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  • Screen a counterparty name against the indexed sanctions lists (OFAC SDN, UK FCDO consolidated). What it does: normalizes the query (Unicode NFKD fold, punctuation strip, lowercase, Cyrillic/Greek transliteration; tolerant to token order e.g. "Putin Vladimir" vs "Vladimir Putin"), looks it up in the sanctions index, and returns EVERY match at low confidence or above with a per-match citation. Low-confidence matches are never hidden. Inputs: - name (required, string): full name of the person or entity. - country (optional, ISO-3166 alpha-2, e.g. "RU"): corroborates nationality/citizenship identifiers. - dob (optional, "YYYY-MM-DD"): a dob match adds +15 to the score — the strongest corroborator. - identifiers (optional, [{type, value}]): extra identifiers to check against the record, e.g. [{"type":"passport","value":"719023441"}]. - request_id (optional, string): idempotency key; safe to retry. - include_low_confidence (optional, boolean, default true): fuzzy matches (Jaro-Winkler >= 0.92) land in the low tier. Keep true — hiding low matches is a compliance liability. Output: {screening_id, disposition, matches[], disclaimer, generated_at}. - disposition: "clear" (no matches) | "potential_match" (any medium/low match) | "review_advised" (any high-confidence match — human review required before any adverse action). - Each match: {list, list_date, record_uid, matched_name, name_kind (primary|alias_strong|alias_weak), confidence (high|medium|low), confidence_score (0-100), matched_fields, citation {source, url, accessed_at}}. - Confidence math: exact primary 80 / alias_strong 70 / alias_weak 55; dob match +15. Tiers: high >= 85, medium >= 60, low >= 30. Fuzzy (JW >= 0.92) -> low tier, score 30-55. - LANGUAGE RULE: report "potential match", never "sanctioned". Screening is informational only — not a legal verdict. Every response carries the fixed disclaimer. EXAMPLE 1 — listed individual with corroborating dob: Input: {"name": "Vladimir Putin", "dob": "1952-10-07", "request_id": "demo-001"} Output: {"screening_id": "cs_scr_...", "disposition": "review_advised", "matches": [{"list": "OFAC_SDN", "list_date": "2026-09-23", "record_uid": "35096", "matched_name": "putin vladimir", "name_kind": "alias_strong", "confidence": "high", "confidence_score": 85, "matched_fields": ["name", "dob"], "citation": {"source": "U.S. Treasury OFAC SDN List", "url": "https://sanctionssearch.ofac.treas.gov/", "accessed_at": "2026-09-26T...Z"}}], "disclaimer": "Informational only — not a legal verdict. Not a substitute for due diligence. Human review required before any adverse action.", "generated_at": "2026-09-26T...Z"} EXAMPLE 2 — same person, no dob (exact alias match, medium): Input: {"name": "Vladimir Putin"} Output: {"screening_id": "cs_scr_...", "disposition": "potential_match", "matches": [{"list": "OFAC_SDN", "list_date": "2026-09-23", "record_uid": "35096", "matched_name": "putin vladimir", "name_kind": "alias_strong", "confidence": "medium", "confidence_score": 70, "matched_fields": ["name"], "citation": {...}}], "disclaimer": "...", "generated_at": "..."} EXAMPLE 3 — clear name: Input: {"name": "John Smith"} Output: {"screening_id": "cs_scr_...", "disposition": "clear", "matches": [], "disclaimer": "...", "generated_at": "..."}
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  • Compute GARM brand safety score for a website or category. Based on the GARM (Global Alliance for Responsible Media) Brand Suitability Framework. Maps content categories to 11 GARM sensitive content categories with risk levels (Floor, High, Medium, Low). Can either: 1. Provide a URL - classification will be fetched and mapped to GARM 2. Provide category and sentiment directly for instant scoring Score interpretation: higher = safer for advertising. Floor categories (e.g., Adult) always score 0/F regardless of sentiment. Args: category: LLMSE category (e.g., "Adult", "Politics", "Sports"). sentiment: Content sentiment ("Bad", "Neutral", "Good"). url: Optional URL to analyze (fetches classification from cache). Returns: GARM brand safety analysis with: - score: Brand safety score (0-100, higher = safer) - grade: Letter grade (A-F) - garm_category: Matched GARM category name or None - risk_level: "floor"|"high"|"medium"|"low"|"none" - is_floor: True if not suitable for any advertising - issues: Categorized issues {critical, warnings, info} - recommendations: Improvement suggestions
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  • Returns Scry's corpus knowledge for a single IPv4 address: when it was first/last observed, observation count, protocols and ports targeted, ASN, country, category (actor/scanner/not_observed), and confidence_bucket (low/medium/high). Use when an agent needs IP triage, hostility assessment, or risk signaling. Do NOT use for raw payloads (never exposed) or IPv6 (corpus is v4-only at v0.1).
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  • Returns upcoming and recent economic events (Fed meetings, jobs reports, CPI, GDP). Defaults to US events at High/Medium impact only because the raw feed includes hundreds of low-impact items from every country. Args: daysBack: Days to look back (default 0) daysForward: Days to look forward (default 7) fromDate: Start date ISO format (alternative to daysBack) toDate: End date ISO format (alternative to daysForward) countries: Comma-separated country names to keep (default 'US'). Pass an empty string to disable the country filter. Common values: 'US','UK','Germany','Japan','China','Canada','France'. impact: Comma-separated impact levels to keep (default 'High,Medium'). Valid values: 'High','Medium','Low'. Pass empty to keep all levels. limit: Max events returned after filtering (default 50, max 200). Returns: { totalMatched, returned, filters, economicCalendar: [...] }.
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  • Create a new standalone Event Planner session — a calendar schedule entry such as 'add an Open Water dive tomorrow at 10:00 with capacity 10'. This is NOT a booking: it needs no product, customer, or participant IDs. Wraps the same service as POST /v1/sessions — checks instructor conflicts and writes a session.create audit entry. MEDIUM RISK — always show a confirmation prompt before executing. If fields are missing, ask only for scheduling details (start date/time, title, duration, capacity) — never for client or participant details. Medium risk. The first call returns confirm_required with an action_id; call again with confirmed_action_id set to it to execute.
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  • Give a participant who currently has NO session assignment (a fresh roster add, or re-adding someone who was fully unassigned) a session slot, and update booked counts. DO NOT use this if the participant is already assigned to a different session - use transfer_participant_between_sessions instead, which requires both from_session_id and to_session_id and is the audited move path. MEDIUM RISK - require operator confirmation. Audited through the same service as the HTTP event planner panel. Reversible: reverting restores the participant to their prior session, or unassigns them if they had none. Medium risk. The first call returns confirm_required with an action_id; call again with confirmed_action_id set to it to execute.
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  • Completely remove a participant from a session with NO destination session - use this for a cancellation or roster drop, not a move. DO NOT use this if the participant is going to a different session; use transfer_participant_between_sessions instead so the move happens atomically and the participant is never left unassigned mid-operation. MEDIUM RISK - require operator confirmation. Audited through the same service as the HTTP event planner panel. Reversible: reverting re-assigns the participant back to the session they were removed from. Medium risk. The first call returns confirm_required with an action_id; call again with confirmed_action_id set to it to execute.
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  • [FREE] File a bug report, docs correction, or payment problem on any AgentPay x402 property and get a case id back. Telling us something is broken never costs money. Params: - site: one of agentworld.me, agentpaystore.com, gibbr.app, solvscore.com, crypto-currency-network.net, x402-agent-pay.com, aiarena.lol - kind: bug | docs | payment | latency | feature | praise - message: what broke and what you expected (10-4000 chars) - endpoint (optional): the exact path that failed, e.g. /api/agentworld/economy - severity (optional): low | medium | high | critical (default medium) - reporter (optional): your agent name for the case record - contact (optional): a reply target if you want follow-up Returns ok + case_id + status. Poll feedback_case_status(case_id) or GET https://x402-agent-pay.com/x402-feedback/case/<case_id> for progress.
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  • [FREE] File a bug report, docs correction, or payment problem on any AgentPay x402 property and get a case id back. Telling us something is broken never costs money. Params: - site: one of agentworld.me, agentpaystore.com, gibbr.app, solvscore.com, crypto-currency-network.net, x402-agent-pay.com, aiarena.lol - kind: bug | docs | payment | latency | feature | praise - message: what broke and what you expected (10-4000 chars) - endpoint (optional): the exact path that failed, e.g. /api/agentworld/economy - severity (optional): low | medium | high | critical (default medium) - reporter (optional): your agent name for the case record - contact (optional): a reply target if you want follow-up Returns ok + case_id + status. Poll feedback_case_status(case_id) or GET https://x402-agent-pay.com/x402-feedback/case/<case_id> for progress.
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  • Summarize an already-computed state_vector into a confidence level (high/medium/low) with a recommendation. Post-hoc digest - use analyze_anomaly or check_drift for fresh analysis of raw data.
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