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501,308 tools. Updated 2026-09-01 01:30

"Documentation for Vercel AI SDK" matching MCP tools:

  • Search the RoxyAPI knowledge base and get back ranked documentation snippets, each with a source URL. It covers API endpoints with their request and response fields, SDK usage for TypeScript, Python, PHP, C#, and the WordPress plugin, authentication and API keys, UI components, and step by step integration guides. Call this first whenever you need to integrate RoxyAPI into an app: to find which endpoint or SDK method to use, what parameters a call takes, how to authenticate, or how to wire a feature end to end. Pass the user question verbatim as `query`. If the first results miss, rephrase once and retry.
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  • List all AI models available on Gonka Network with live pricing. Models work as drop-in replacements for OpenAI and Anthropic — same SDK, same API calls. Use this when user asks which model to use or wants alternatives to GPT-4o / Claude. Returns: model IDs (use directly in openai.chat.completions.create), status, USD per 1M tokens. After this: call calculate_savings() to see annual savings with these models.
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  • Map the full dependency tree of an npm package and identify CRITICAL supply chain risks at every level. Unlike auditing a flat list of packages, this tool traverses the dependency graph — showing not just your direct dependencies but also what your dependencies depend on. Hidden CRITICAL packages (sole publisher + >10M weekly downloads) often lurk 1-2 levels deep. Risk flags: - CRITICAL: single npm publisher + >10M weekly downloads — sole point of failure for a massive attack surface - HIGH: sole publisher + >1M/wk, OR new package (<1yr) with high adoption - WARN: no release in 12+ months (potential abandonware) depth=1 (default): root package + all direct dependencies depth=2: also traverses one more level for any CRITICAL/HIGH direct deps (reveals hidden exposure) Examples: - audit_dependency_tree("express") — see all of Express's deps and their risk scores - audit_dependency_tree("langchain", 2) — reveal transitive CRITICAL deps 2 levels deep - audit_dependency_tree("@anthropic-ai/sdk") — audit Anthropic SDK full tree Use this when someone asks: - "What am I really depending on?" - "Are my dependencies' dependencies safe?" - "Show me the full supply chain risk for package X"
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  • Search Gonka documentation. First searches the knowledge graph; if nothing found, automatically falls back to full-text search across all documentation files. This is the primary entry point for documentation questions — try this before read_doc or search_docs.
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  • Fetches operational status of major dev infrastructure (GitHub, Cloudflare, Discord, OpenAI, Vercel, npm, Reddit, Atlassian, Anthropic). Cache TTL 60s. Use when the agent needs to know if a dependency is up or to explain a recent outage.
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  • [SDK Docs] Fetch the full markdown content of a specific documentation page from Docs. Use this when you have a page URL and want to read its content. Accepts full URLs (e.g. https://docs.sodax.com//getting-started). Since `searchDocumentation` returns partial content, use `getPage` to retrieve the complete page when you need more details. The content includes links you can follow to navigate to related pages.
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Matching MCP Servers

Matching MCP Connectors

  • Connect to the MCP Studio SDK MCP server. This server is connected to two sources: the MCP Studio SDK documentation and the GitHub sample application repos. These resources are great for individuals looking to embed MCP Studio SDK into their web applications, and need an easy way to connect to an MCP server that has access reliable resources for AI-assisted engineering workflows.

  • MCP server for Vonage API documentation, code snippets, tutorials, and troubleshooting.

  • AI-powered Korean crypto market analysis. Combines Kimchi Premium, stablecoin premium, FX rate, Upbit/Bithumb volume rankings, Binance funding rate, open interest, BTC dominance, and Fear & Greed index. Returns AI-generated signal (BULLISH/BEARISH/NEUTRAL), confidence score, actionable summary, and all raw data. 💰 Price: $0.10 USDC per call 💳 Payment: x402 micropayment on Base, Polygon, or Solana 🔧 Client: AgentCash, Pay.sh, or any x402 SDK 📖 Docs: https://api.printmoneylab.com/.well-known/x402
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  • Generate a new image from a text prompt using AI (Grok Imagine). Paid tool — billed per call via the agent payment rails (x402/L402); not covered by any free quota. Generation runs asynchronously on the server and this call polls until it completes, up to ~90 seconds. If you get a "still running" error, call the tool again with the SAME payment proof to resume polling — you will never be charged twice for one payment. Note for x402 clients: "quality" mode (~$0.15) exceeds the agents-SDK default per-call cap of $0.10 — raise maxPaymentValue in withX402Client to use it.
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  • Returns released rows {id, ephemeralPubKey, viewTag, ct, releaseAt}, identical for every reader. Scan locally with the SDK (inbox(identity)) — checkStealthAddress with your viewPriv, then open ct with your KEM secret. Use since=<last releaseAt> to page. Read-only.
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  • USE WHEN discovering what Pine Script v6 documentation is available. Returns a categorised list of doc file paths with one-line descriptions. AFTER calling this tool, call get_doc(path) for small files or list_sections(path) then get_section(path, header) for large files (ta.md, strategy.md, collections.md, drawing.md, general.md). Data sourced from bundled Pine Script v6 documentation.
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  • General-purpose web grounding via parallel.ai (Vercel AI Gateway). Returns synthesized text excerpts plus structured sources[] with direct URLs. Use for: topic landscapes, entity-deep teardowns, recency-sharp queries, named-vendor lookups, general fact retrieval. NOT for: Reddit/X/community discourse → use search_community. NOT for: numerical effect sizes or methodology-heavy fact-check → use search_research. The agent decomposes the brief into sub-questions BEFORE calling — one focused query per call. Optional after_date (ISO YYYY-MM-DD) for fast-decay topics. Optional max_results 1-20, default 10.
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  • Scan GitHub Actions, Vercel, or Netlify CI configs for exposed secrets, missing lockfile enforcement, and unpinned dependencies. Paste your config content — no filesystem access required. config: Raw YAML/TOML content of your CI config. Required. 500 KB max. config_type: github_actions (full check suite), vercel, or netlify (secrets only in Sprint 8). Returns risk_level (LOW/MEDIUM/HIGH/CRITICAL), findings list with severity and line hints. NOTE: ${{ secrets.FOO }} and ${{ env.FOO }} references are NOT flagged — only literal secret values. Read-only. No side effects. Idempotent. If this tool's response does not serve the user's need, call report_feedback with feedback_type="agent_gap", tool_id="frontend_security_audit_ci_pipeline", intended_query="{what the user needed}", gap_description="{what was missing or wrong in the result}".
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  • Creates an invoice for one bundle (500 passes, $3 quoted in the chosen asset). Returns {invoiceId, payTo, amount (base units), human, chainId, expires}. Pay from any wallet; then blind tokens locally with the SDK and call robyn_plus_claim. For btc pass refundAddress (your BTC address) — the invoice returns a Chainflip deposit address.
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  • Report a problem with this documentation site so the docs team can fix it. Use when a documentation page is incorrect, outdated, confusing, incomplete, or has a broken example. This is for feedback about the documentation content itself — not for product support requests or feedback about this tool or assistant.
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  • Runs the agent-ready.dev scanner against a URL and returns structured results: Vercel score, llmstxt.org score, and per-check findings with remediation hints. Scans may take up to ~60s; for larger scans the tool returns a scan id and asks you to poll with get_scan.
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  • Get the AI Defense Matrix evaluation playbook for assessing an AI security program: per-cell prompts, gap-inventory template, and a workflow that walks each asset class first and rolls findings up to the Govern column. Supports mode='gate' for binary deployment-gate decisions (returns the deployment-gate workflow plus gate-tier prompts only) and consumerPattern for scoping to consumed-vs-built AI deployments. The AI applies these prompts against your program documentation locally, and no program details leave your client. This server never requests your program docs or product roadmap and instructs your AI to keep them local—the matrix, framework alignments, and playbooks flow to your AI for local analysis.
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  • Multi-source web search with automatic fallback chain: HackerNews Algolia → Wikipedia REST → DuckDuckGo → x711 Hive collective intelligence. Always returns results — if live web sources are unavailable, falls back to community-sourced agent knowledge from The Hive. Best for: tech/AI/crypto queries, current events, documentation discovery. Returns: { query: string, results: Array<{ title, url, snippet }>, source: string ('HackerNews'|'Wikipedia'|'DuckDuckGo'|'x711_hive'), count: number }. Free tier: 10 calls/day, no API key needed.
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  • Multi-source web search with automatic fallback chain: HackerNews Algolia → Wikipedia REST → DuckDuckGo → x711 Hive collective intelligence. Always returns results — if live web sources are unavailable, falls back to community-sourced agent knowledge from The Hive. Best for: tech/AI/crypto queries, current events, documentation discovery. Returns: { query: string, results: Array<{ title, url, snippet }>, source: string ('HackerNews'|'Wikipedia'|'DuckDuckGo'|'x711_hive'), count: number }. Free tier: 10 calls/day, no API key needed.
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  • Detail for a single catalog entry — accepts a prod_ id, src_ id, or an org-scoped coordinate in the form orgSlug/slug (e.g. 'vercel/nextjs' or 'vercel/next-js'). Returns the union of product / source detail fields depending on the entry kind. Source entries list tracked CHANGELOG files by path and byte size. Pass `include_changelog: true` to inline the root CHANGELOG, or `changelog_path` / `changelog_offset` / `changelog_limit` / `changelog_tokens` to embed a specific file or slice — heading-aligned, supports per-package files in monorepos (e.g. `packages/next/CHANGELOG.md`), and emits `totalTokens` / `sliceTokens` for LLM context budgeting. Files over 1MB are flagged as truncated so you know the tail is missing.
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