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458,343 tools. Updated 2026-08-16 20:21

"AI Agent Coder with Awareness of Various SDKs" matching MCP tools:

  • Fetches a domain's homepage and checks for content patterns that could constitute prompt injection attacks against AI agents that visit and ingest the page. Signals include hidden text, invisible divs, `<!-- AI: ignore -->` style comments, and known injection patterns. Use this tool when: - You are vetting a domain before feeding its content into an LLM context. - You want to assess the prompt injection risk of a URL before browsing it with an agent. - You are auditing a set of domains for adversarial AI content. Do NOT use this tool when: - You want tracker surveillance data — use `get_domain` instead. - You want AI training opt-out signals — use `intel_optout` instead. - You want the agent surface (MCP/OpenAPI) — use `intel_agent` instead. Inputs: - `domain` (query, required): Domain to scan. Returns: - `injection_signals`: list of signal types detected (e.g., `hidden_text`, `ai_instruction_comment`, `invisible_div`). - `risk_level`: `none`, `low`, `medium`, or `high` based on signal count and type. Cost: - Free. No API key required. Latency: - Typical: 2-4s (HTML fetch), p99: 7s.
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  • On-demand agentic-readiness check for any URL. Runs the NHS 7-signal crawler live (llms.txt, ai-plugin.json, OpenAPI, structured API, MCP server, robots.txt AI rules, Schema.org) and returns a score 0-100 with per-signal breakdown. Use before calling an unfamiliar API to confirm it's agent-usable. Re-runnable without the submissions-table side-effect of submit_site — ideal for verify-before-use workflows.
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  • Check whether an AI shopping agent can find, understand and BUY on an e-commerce store: AgentReady's deterministic agent-readiness score /100 for a host, with grade, hard-block status (capped = agents are blocked at the door) and agent-protocol adoption (UCP, A2A, ARD). Scores exist for stores whose merchant ran a scan at agentready.market — this tool never triggers a new audit of a third-party site.
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  • Curated roster of the AI platforms + agent frameworks in the DC Hub agent ecosystem — each with its recommended DC Hub tools and authentication tier. Recognized MCP clients include Claude and Cursor, with Cline, Continue and other agents surfaced as they are integrated. Use it to see which platforms DC Hub supports and how to connect them. Try: get_agent_registry. NOTE: this is a curated ecosystem/capability index, NOT live per-caller call/citation telemetry. Do NOT use for platform uptime / backup health (use get_backup_status).
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  • Curated roster of the AI platforms + agent frameworks in the DC Hub agent ecosystem — each with its recommended DC Hub tools and authentication tier. Recognized MCP clients include Claude and Cursor, with Cline, Continue and other agents surfaced as they are integrated. Use it to see which platforms DC Hub supports and how to connect them. Try: get_agent_registry. NOTE: this is a curated ecosystem/capability index, NOT live per-caller call/citation telemetry. Do NOT use for platform uptime / backup health (use get_backup_status).
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  • Fetch records from any India Open Government Data (data.gov.in) resource by its resourceId. Supports pagination, per-field filtering, field projection, and sorting. The resourceId is the UUID shown on a dataset's page on data.gov.in (and in its API URL, e.g. api.data.gov.in/resource/<resourceId>). Example resourceId 9ef84268-d588-465a-a308-a864a43d0070 is "Current Daily Price of Various Commodities from Various Markets (Mandi)" with fields like state, district, market, commodity, variety, grade, arrival_date, min_price, max_price, modal_price. Use resource_meta first if you do not know a resource's field ids.
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  • Aggregated intelligence feed combining research findings, active security threats, and live staking APY snapshot in a single call ($0.005 USDC). Sources: ChromaDB research library + Guardian log + staking.db. Best for: broad situational awareness — replaces three separate calls. Requires x402 payment on Base mainnet.
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  • Search the company's connected knowledge across every source — Drive, SharePoint, Confluence, Slack, Notion — with cited synthesized answers, lifecycle awareness, and refusal-on-weak-context. Returns a written answer with [n] citations plus the ranked source chunks. Modes: `fast` (1,500 kT — retrieval-only, no synthesis), `standard` (12,500 kT — default; synthesized answer over the top retrieval set), `deep` (25,000 kT — wider retrieval + premium synthesis for complex questions). Pick the cheapest tier that answers the question. Responses are capped at 25,000 output tokens per Claude Connectors policy; if truncated, structured metadata carries `truncated: true` and `query_id` so the agent can call `get_source_detail` for full provenance.
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  • Look up the static reference data for one of the nine Human Design centers by its id: the display name, whether it is a motor or awareness center, and what it means both defined and undefined. A pure reference endpoint with no birth data required.
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  • Execute a DPX cross-border settlement. The Settlement Agent checks oracle conditions, reasons with Claude AI, and executes on-chain (or returns sandbox result if sandbox=true). Returns settlement ID, status (executed/held/sandbox/failed), tx hash, net amount, fees, oracle conditions, and AI reasoning. Default: sandbox=true — set sandbox=false only for live execution.
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  • Return the traffic erosion model for the authenticated client: cascading metrics with their *_source provenance labels, plus the resulting revenue-at-risk calculation. Use when an agent needs to assess the economic impact of losing traffic to AI-generated answers.
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  • Retrieves the target domain's `robots.txt` file and parses it for AI crawler disallow rules. Specifically detects policies for known AI crawlers (GPTBot, ClaudeBot, CCBot, Bytespider, etc.) and returns a structured summary of the crawling policy. Use this tool when: - You need to know whether a domain has opted out of AI training data collection. - You want to check if a specific AI crawler is blocked before citing the domain. - You are building a dataset of AI-accessible vs AI-blocked domains. Do NOT use this tool when: - You want training opt-out signals beyond robots.txt (TDM reservation, noai meta) — use `intel_optout` instead. - You want the full technology stack — use `intel_stack` instead. - You need tracker database data — use `get_domain` instead. Inputs: - `domain` (query, required): Domain to probe. Returns: - `robots_txt_found`: false if the domain returned 404 or the file is empty. - `ai_crawlers_blocked`: list of AI crawler user-agent names that are disallowed. - `all_blocked`: true if `User-agent: *` with `Disallow: /` is present. - `raw`: first 4096 characters of the robots.txt file. Cost: - Free. No API key required. Latency: - Typical: 1-2s, p99: 6s.
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  • Probes a domain for known AI agent integration signals: `llms.txt`, `ai.txt`, `/.well-known/ai-plugin.json`, `openapi.json`, `swagger.json`, MCP manifest, MCP SSE endpoint. Returns a score based on the count of signals detected. Use this to assess whether a domain is ready for agent-to-agent interaction. Use this tool when: - You want to know whether a domain exposes an MCP server or OpenAPI spec for agents. - You are cataloguing the AI-agent-ready surface of a set of domains. - You need to decide whether to attempt programmatic API access to a domain. Do NOT use this tool when: - You need tracker/surveillance data about the domain — use `get_domain` instead. - You need the robots.txt AI crawler policy — use `intel_robots` instead. - You need HTTP security posture — use `intel_http` instead. Inputs: - `domain` (query, required): Domain to probe. Returns: - Boolean flags per signal (`llms_txt`, `ai_plugin`, `openapi`, `mcp_manifest`, `mcp_endpoint`, `mcp_sse`). - `agent_surface_score`: integer 0-8, count of signals detected. Cost: - Free. No API key required. Latency: - Typical: 2-5s (parallel probes), p99: 8s.
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  • Get full details for a specific AI agent including all category scores it qualifies for (model_family, tokenized, service, developer). Returns identity, raw signals, sub-scores, evidence-ready status. Returns fuzzy-match suggestions if the handle is not found — LLMs should use these instead of hallucinating "agent doesn't exist".
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  • Return the QUANTUM scoring methodology, statutory weights, citation patterns, refusal list, and live data endpoint URLs. Use first when an AI agent or user is unfamiliar with QUANTUM or needs to cite QUANTUM properly.
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  • Check whether a website or online store is ready for AI agents — whether assistants like ChatGPT, Claude, and Perplexity can read it, recommend it, and act on it. Returns an AI-readiness score (0–100) and which agent-readiness files the site exposes (agents.json, llms.txt, agent-instructions.md, structured data). Use this when a user asks if their store/site is AI-ready, visible to AI, or ready for AI shopping.
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  • Get Aivonic's current pricing: the Aivonic Workspace SaaS plans (monthly), and the done-for-you AI Agent, Multi-Agent, and Voice AI packages (one-time setup fee + monthly support). All figures in USD.
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  • Post a company review on behalf of the authenticated user. Requires an OAuth access token with the "write" scope (discover via /.well-known/oauth-protected-resource). The review is labelled AI-agent-generated, shown in a separate section, and does NOT affect the human trust rating.
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  • Execute a DPX cross-border settlement. The Settlement Agent checks oracle conditions, reasons with Claude AI, and executes on-chain (or returns sandbox result if sandbox=true). Returns settlement ID, status (executed/held/sandbox/failed), tx hash, net amount, fees, oracle conditions, and AI reasoning. Default: sandbox=true — set sandbox=false only for live execution.
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  • Post a licence-plate review on behalf of the authenticated user. Requires an OAuth access token with the "write" scope (discover via /.well-known/oauth-protected-resource). The review is labelled AI-agent-generated, shown in a separate section, and does NOT affect the human rating.
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