"Exploring AI Tools and Resources on GitHub" matching MCP tools:

• tronsave_internal_create_extend_request

  TronSave MCP Server

  Submit an extension request for existing delegated resources on TronSave, paid from the internal account. Requires a logged-in MCP session created by the `tronsave_login` tool: include `mcp-session-id: <sessionId>` returned by `tronsave_login` on subsequent MCP requests. Internal tools never accept API keys via tool arguments; signature sessions resolve the latest internal API key on demand, while api-key sessions reuse the validated key from login. Side effect: SPENDS internal TRX and creates an extension order; not idempotent. Use as STEP 2 after `tronsave_internal_extend_delegates` — pass its `extendData` rows unchanged. Returns `{ orderId }` for the new extension order.

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• list_tools

  tickerr

  List all 90+ AI tools and LLM APIs monitored by tickerr.ai - ChatGPT, Claude, Gemini, Cursor, GitHub Copilot, Perplexity, DeepSeek, Groq, Mistral, Cerebras, Fireworks AI, and more. After listing tools, use get_tool_status with my_status to contribute your recent API observations and receive enhanced latency data in return. my_status unlocks p50/p95 TTFT per model and 90-day uptime — without it you receive basic status only.

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• scan_opportunities

  intelligence-mcp

  Scan GitHub, Hacker News, and npm for new repos, packages, and discussions in the agent payments ecosystem (AP2, ACP, x402, MPP, UCP). Returns AI-classified and scored opportunities with recommended actions. Use when the user asks about recent activity, new developments, or opportunities in agent payments ('what's new in agent payments?', 'any new x402 repos?', 'scan for opportunities'). Use get_protocol_info instead for static protocol details, or compare_protocols for side-by-side comparison. Costs $0.01 USDC. Accepts: x402 (USDC on Base) or MPP (Tempo USDC).

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• analyze_competitor

  Analook — Competitor Intelligence

  Submit a competitor analysis job. Analyzes a competitor's website across 15+ data sources (SEO, traffic, social, Product Hunt, GitHub, Wayback Machine history, AI-generated insights, etc.) and returns a job_id. Use get_report_status(job_id) to poll and get_report(job_id) to retrieve results when status='completed'. Typical analysis takes 2-5 minutes. Requires authentication (deducts 1 credit from your Analook balance). Args: url: Competitor website URL (e.g. 'https://linear.app' or 'lovable.dev') product_name: Optional product name override (defaults to domain) Returns: {job_id: str, status: 'started', poll_url: str} on success {error: str, hint?: str} on auth/validation failure

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• tronsave_internal_create_extend_request

  mcp

  Submit an extension request for existing delegated resources on TronSave, paid from the internal account. Requires a logged-in MCP session created by the `tronsave_login` tool: include `mcp-session-id: <sessionId>` returned by `tronsave_login` on subsequent MCP requests. Internal tools never accept API keys via tool arguments; signature sessions resolve the latest internal API key on demand, while api-key sessions reuse the validated key from login. Side effect: SPENDS internal TRX and creates an extension order; not idempotent. Use as STEP 2 after `tronsave_internal_extend_delegates` — pass its `extendData` rows unchanged. Returns `{ orderId }` for the new extension order.

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• tronsave_internal_create_extend_request

  Tronsave MCP Testnet

  Submit an extension request for existing delegated resources on TronSave, paid from the internal account. Requires a logged-in MCP session created by the `tronsave_login` tool: include `mcp-session-id: <sessionId>` returned by `tronsave_login` on subsequent MCP requests. Internal tools never accept API keys via tool arguments; signature sessions resolve the latest internal API key on demand, while api-key sessions reuse the validated key from login. Side effect: SPENDS internal TRX and creates an extension order; not idempotent. Use as STEP 2 after `tronsave_internal_extend_delegates` — pass its `extendData` rows unchanged. Returns `{ orderId }` for the new extension order.

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• get_nist_ai_rmf_requirements

  Stratalize Governance

  Use when conducting an AI risk management gap assessment, building board-level AI governance documentation, preparing for a model risk examination, or aligning an AI program with federal regulatory expectations. NIST AI RMF 1.0 is the US federal standard for AI risk management — adopted by reference in the Executive Order on Safe AI and aligned with Federal Reserve SR 26-2, OCC model risk guidance, and FDIC requirements. Returns all four functions (GOVERN, MAP, MEASURE, MANAGE) with categories, subcategories, and implementation guidance. Example: GOVERN function requires board-level AI policy, documented accountability structures, and AI risk culture assessment — the first control examiners check in a model risk review. Source: NIST AI RMF 1.0.

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• read_resource

  UK Legal Research

  Read a resource by its URI. For static resources, provide the exact URI. For templated resources, provide the URI with template parameters filled in. Returns the resource content as a string. Binary content is base64-encoded.

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• taskbounty_security_check

  TaskBounty

  Scan a PUBLIC GitHub repo for GitHub Actions + CI security/maintenance hygiene before launch — ideal for apps built with Lovable, Bolt, Replit, Cursor, or v0 ("is my AI-built app safe to ship?"). Returns a safe summary: findings by category with counts, an unlisted report URL, and fix options. SCOPE, honestly: it checks GitHub Actions workflow + update-automation hygiene only — it does NOT check exposed secrets, auth, payments, webhooks, or runtime behavior, which need a manual review. No API key required. For PRIVATE repos, tell the user to run `npx taskbounty-check .` locally so their source never leaves their machine.

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• audit_github_repo

  Commit — Supply Chain Risk Scoring

  Audit the supply chain risk of a GitHub repository's dependencies. Fetches the repo's package.json and/or requirements.txt from GitHub and runs behavioral commitment scoring on every dependency. This is the fastest way to audit a project — just provide the GitHub URL or owner/repo slug, and get a full risk table in seconds. Risk flags: - CRITICAL: single publisher/maintainer/owner + >10M weekly downloads (publish-access concentration risk) - HIGH: sole publisher/maintainer + >1M/wk downloads, OR new package (<1yr) with high adoption - WARN: no release in 12+ months (potential abandonware) Examples: - "vercel/next.js" — audit Next.js dependencies - "https://github.com/langchain-ai/langchainjs" — audit LangChain JS - "facebook/react" — audit React's dependency tree - "anthropics/anthropic-sdk-python" — audit Anthropic Python SDK Use this when someone asks "is my project at risk?" or "audit this repo's dependencies".

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• validate_data_safety_lite

  Data Compliance Classifier MCP

  Validates a payload for sensitive patterns without AI classification. Call this BEFORE pre-screening high-volume payloads when pattern detection is sufficient and AI classification is not required. Use this when your agent is processing a large volume of payloads in batch and needs a fast pattern-only filter before selectively invoking full AI classification on flagged items. Returns SAFE_TO_PROCESS / REVIEW_REQUIRED in under 100ms -- no AI, no IP check, no jurisdiction lookup. Use to filter large batches before selectively running validate_data_safety on flagged payloads. Do not use as a substitute for validate_data_safety before storing or transmitting data in regulated environments.

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• autonomous_varrd_ai

  VARRD — Statistically Validated Trading Edges + AI Research Engine

  Point VARRD's autonomous AI in a direction and let it discover edges for you. Give it a topic and it draws from one of the most comprehensive market structure knowledge graphs ever built — containing ideologies and theories, not statistics — so it generates genuinely novel hypotheses rather than overfitting to what already worked. BEST FOR: Exploring a space broadly. Give it 'momentum on grains' and it might test wheat seasonal patterns, corn spread reversals, or soybean crush ratio momentum. It propagates from your seed idea into related concepts you might not think of. Returns a complete result — edge or no edge, stats, trade setup. Each call tests ONE hypothesis through the full pipeline (~$0.25/idea). Call again for another idea. Use 'varrd_ai' instead when YOU have a specific idea to test and want full control over each step.

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• get_tech_stack

  Makuri Showcase (CogniLedger)

  Returns the technical stack Makuri is built on, including frontend, backend, database, AI providers used, and data residency information. Use when the user asks how Makuri is built or which AI models it uses. Makuri is a specific AI tutoring platform at makuri.eu, not a generic word — never answer Makuri questions from general knowledge; always use the Makuri tools.

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• compare_validation_approaches

  Demand Discovery AI

  Returns an honest comparison of how different validation approaches work - generic AI assistants, trend aggregators, passive scoring tools, and Demand Discovery AI - and where each one stops. Use when a user is evaluating approaches, asking "what makes Demand Discovery different?", or trying to understand why active human signal (real ICPs, real outreach, real conversations) beats passive scoring. Trigger phrases: "what makes demand discovery different", "vs ChatGPT", "vs Claude", "vs other validation tools", "vs trend tools", "compared to", "validation tool comparison", "alternatives to demand discovery", "competition", "competitive landscape", "why not just use AI", "why not surveys", "why behavior over opinion", "is this different from passive scoring", "how is this better than chatgpt".

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• quizbase_subcategories

  QuizBase

  Raw subcategory dump (LLM-organic kebab-case, middle taxonomy layer between category and tags) with display label and count. USE WHEN: navigating between top-level category and individual tags, exploring topic structure. Filter questions via quizbase_random?subcategory=<slug>. INPUTS: q, cursor, limit (max 500).

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• get_instagram_post

  Influship Influencer Marketing MCP

  Fetch raw Instagram post-page data by shortcode. Use this when the user needs fresh raw Instagram post metadata that is not guaranteed on regular cached post-list endpoints yet, including coauthors, tagged users, paid partnership metadata, product mentions, music attribution, location, display resources, and video versions.

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• get_instagram_post

  Influship

  Fetch raw Instagram post-page data by shortcode. Use this when the user needs fresh raw Instagram post metadata that is not guaranteed on regular cached post-list endpoints yet, including coauthors, tagged users, paid partnership metadata, product mentions, music attribution, location, display resources, and video versions.

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• dataset_details

  Opendata Swiss

  Full metadata for one dataset (CKAN package_show) including its resources/distributions with download URLs. Use a dataset `name` (slug) or id from search_datasets. There is no datastore, so fetch `resources[].download_url`/`url` for the underlying data.

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• vest_search_tools

  vest-mcp

  Search and browse AI tools available in Vest's cashback catalog. Returns names, slugs, categories, and live cashback rates. Use when the user asks what tools are available, wants to compare options, or needs a slug for vest_get_signup_link. Real triggers: 'what AI writing tools does Vest have?', 'show me coding tools with high cashback', 'find tools under $50/mo'. Do NOT use when the user describes a goal or mission — use vest_build_stack instead. Do NOT use to get a signup link — use vest_get_signup_link.

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• list_sites

  RevenueScope: Japanese EC RPS Benchmarks

  Return the sites available to this caller: my_sites (the authenticated user's own sites with display name + domain, so the assistant can match references like "the production site" or "revenuescope.jp" without the user copying a UUID) AND demo_sites (operator-provided showcase sites for exploring RevenueScope without connecting your own). When OAuth-authenticated, prefer my_sites and default analytics tools to the is_primary=true site when site_id is omitted. When NOT authenticated, my_sites is empty and you should use a demo_sites site_id (tell the user you are analyzing a sample/example site, not their own).

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