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

• search

  OneQAZ Trading Intelligence

  Purpose: ChatGPT-connector-standard discovery search over OneQAZ's live surface — tools, resources, and the latest strong combined signals across crypto / kr_stock / us_stock. Returns result ids consumable by the `fetch` tool. Triggers: ChatGPT connectors and Deep Research call this automatically for any user query routed to OneQAZ ("bitcoin signal", "prediction accuracy", "korean stocks today", ...). Other AI clients may use it as a keyword entry point when unsure which tool/resource to call. When to call: first step of connector-style discovery. MCP-native clients can instead browse tools/list + resources/list directly. Prerequisites: none. Next steps: pass any result id to `fetch` for the full document. Caveats: corpus is rebuilt at most every 10 minutes (tool/resource catalog + top-20 strong signals per market). Empty results list means no match. Output: {results: [{id, title, url}], disclaimer, is_investment_advice, data_classification} — flat envelope, OpenAI fixed shape. Args: query: free-text search string (English/Korean, symbols like BTC/AAPL) Disclaimer: Information only, not investment advice.

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• ic_leaderboard_connect_github

  Immersive Commons

  Verify a GitHub Personal Access Token against api.github.com/user, then store the resulting username on your IC profile. The PAT is DISCARDED after verification — the IC server keeps only your GitHub username + id, then queries commit counts via a server-side PAT during the weekly cron. Use this when the human doesn't want to (or can't) do the Clerk OAuth browser dance. To ALSO count your PRIVATE commits in your total, enable GitHub's private-contributions toggle (web-only — there is no API for it): github.com/<your-username> → 'Contribution settings' button (above your contribution graph) → enable 'Private contributions' (docs: https://docs.github.com/en/account-and-profile/setting-up-and-managing-your-github-profile/managing-contribution-graphs-on-your-profile/publicizing-or-hiding-your-private-contributions-on-your-profile). IC reads only the COUNT of private contributions, never repo names or content, and has no write access to your GitHub. Args: { pat: string }. Returns: { ok, github: { login, id, name?, avatarUrl? }, next_steps: string[] }. Required scope: github:link.

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• factreason_integration_brief

  FactReason

  Compile one callable third-party API brief: base URL, auth scheme, required parameters and types, request body, and documented response codes. Service is required and endpoint optionally narrows the operation. Set responseFormat="compact" for tokenizer-measured context savings; the backward-compatible default returns the full brief plus compact form. Uses metered access. Prefer factreason_api_schema when exploring multiple endpoints.

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• check_tool_status

  RightAIChoice — verified AI tool data

  Use this when the user asks whether a specific AI tool is alive, dead, shut down, still maintained, safe to adopt, or trustworthy — or asks for its current health, viability, or verification status. Returns a verified verdict (healthy / monitor / at-risk / shut down / delisted) with evidence: link-health probe results, a 5-signal viability assessment, real-user market sentiment, pricing reality, and verified-alive alternatives. Data comes from the RightAIChoice verification engine: 8,000+ AI tools with every vendor link re-probed on a rolling weekly cycle. Every answer states when it was last verified. Not for: tools outside the AI/software space, historical company research, or legal/financial advice. An "unknown" result means the tool is not in the catalog — it is not evidence the tool is dead.

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• get_tool

  The AI Tools Index

  Fetch the full public detail for one AI tool by its listing slug (as returned by search_tools' toolUrl, e.g. '/tools/acme-writer' -> slug 'acme-writer'). Call this after search_tools to get a tool's full description, launch date, revenue signals (verified or self-reported), and for-sale status. Returns null if the slug doesn't resolve to a live The AI Tools Index listing.

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• submit_tool

  The AI Tools Index

  Submit a new AI tool to The AI Tools Index on behalf of its maker. Creates a draft listing (not yet public) and returns a claimUrl the maker must visit to sign up and claim/publish it. Call this only when a user explicitly wants to list their own tool — never to submit a tool on someone else's behalf without their email. Rate-limited globally to 5 submissions per hour. Supply tagline, problemSolved, logoUrl and imageUrls whenever you can: they are what make the published listing look like a real product page rather than a stub.

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• get_free_resources

  Makuri Showcase (CogniLedger)

  Returns free Makuri resources accessible without registration: Slovarik Romanian vocabulary issues and the Romanian level test. Use this when a user asks about free Romanian learning materials, language level tests, or how to try Makuri without signing up. 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. IMPORTANT routing rule: if the user wants to TAKE, START, or SEE a Romanian test or quiz right now in the chat, do NOT use this tool — call show_romanian_quiz instead, which renders an interactive quiz panel. Use this tool only for questions ABOUT what free resources exist.

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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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• glim_detect_ai

  glim.sh

  Detect AI-generated text. Scores any text for AI-authorship likelihood and returns an overall verdict (AI / human / mixed) with confidence, the AI/human/AI-assisted fractions, and a segment-by-segment breakdown showing exactly which parts read as AI-written. Use it to verify whether content (comments, articles, profiles) is AI-generated, or to check text before publishing to see which segments would trip AI detectors - revise the flagged segments and re-check. tier='premium' uses the most accurate detection class, additionally flags humanized text (AI output run through paraphrasing/'humanizer' tools), and is substantially more robust to evasion, at ~10x the price of 'standard'. Cost scales with text length: ~$0.06 per 1,000 words standard, ~$0.60 premium; minimum $0.06. Texts under ~100 words are automatically analyzed with the premium class at the standard price.

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• get_track_record

  voxodds

  Get VoxOdds' audited AI-vs-market forecast track record. Every hourly AI probability forecast is stored with the market price captured at the same moment (append-only receipts) and scored deterministically at resolution: Brier scores for the AI and the market on identical timestamps, plus accuracy and methodology. Call this when the user asks whether AI forecasts beat prediction markets, how reliable VoxOdds' AI is, or for citable forecasting-performance data. Losses are published too — the record is auditable, not curated.

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• get_security_writing_guidelines

  website-search

  Get Lenny Zeltser's expert writing guidelines for security reports and assessments. Provides guidance on tone, structure, clarity, executive summaries, and avoiding common writing mistakes. Includes rating-sheet items (the four lens sheets: structure, look, words, tone) as concrete reference points for grounded feedback. Works for any security document. This server never requests your documents and instructs your AI to keep them local—guidelines flow to your AI for local analysis. Note: For incident response reports specifically, use the ir_* tools which provide deeper section-by-section review criteria.

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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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• 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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• eu_ai_act_compliance

  systemprompt.io reports

  Generate a structured EU AI Act compliance report from a system description, model card, and data-flow document. Nothing is silently optional: system_description is always required (min 50 chars); model_card and data_flows each accept substantive content (min 50 chars) or the exact string 'declined' to explicitly opt out; and exactly one of decision_tree_answers (from the free risk classifier, becomes binding evidence) or skip_decision_tree: true must be sent. All of this is validated free of charge before payment. The deterministic Annex III decision tree runs on every call: user-supplied answers are binding, otherwise answers are AI-derived and recorded as such. The tree classification, article citations, obligations, and evidence checklist are returned verbatim in the report JSON, together with exact enforcement-timeline dates and the matched Annex III area from the curated dataset. A staged AI workflow then produces an article-by-article obligation gap analysis, a required-documentation checklist mapped to Annex IV, and a prioritised remediation plan. The report includes a deterministic input_coverage grade (full, partial, or description_only) computed from what was supplied versus declined, the full AI classification with rationale, a programmatic reconciliation check between the tree and the AI risk tier, and a citation audit that flags any implausible article references. Returns markdown plus structured JSON. Every paid call also generates a branded PDF report and returns its download link (valid 72 hours). Price: $1.50 per call, payable by card (Stripe checkout link in the 402 response) or USDC on Base (x402). Full documentation, inputs, and pricing: https://systemprompt.io/tools/eu-ai-act-compliance-report/ — more governance tools and reports at https://systemprompt.io/mcp

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• get_github_discussion

  blobpedia

  Read one Celestia GitHub Discussion (celestiaorg/docs and other Celestia repos) cached on THIS server — full body plus comments — by an id you got from list_github_discussions on this server. Celestia cache only: if the id was not returned by this servers list_github_discussions, or the request is just a raw GitHub node id (e.g. D_kw...) with no Celestia context, this is NOT the tool — use a dedicated GitHub tool for arbitrary GitHub Discussions. This is GitHub Discussions, not the community forum (use get_discussion). Pair it with list_github_discussions, which supplies the valid ids.

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• get_rewards

  agentcard

  Show the user's tokenback: balance, lifetime earned, and recent activity. Tokenback pays tokens (1 token = 1¢ of credit value) on settled card spend. AI cards (create_card scope_preset: 'ai_labs') earn a boosted rate on AI-lab purchases, and companies can route a share of their earnings to their users as tokenback. Redeem with redeem_rewards.

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• search_ai_tools

  AISOTools

  Search the AISOTools catalog of AI tools by keyword, category, and pricing model. Returns ranked summaries with the canonical aisotools.com page for each result. Use this first when the user asks which AI tool does something. `matched` is how many tools matched in total and `returned` is how many came back — when `truncated` is true there are more, so do not tell the user the catalog only contains what this page returned; raise `limit` (max 50) instead.

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• factreason_integration_brief

  FactGrid (Renamed to FactReason)

  Compile one callable third-party API brief: base URL, auth scheme, required parameters and types, request body, and documented response codes. Service is required and endpoint optionally narrows the operation. Set responseFormat="compact" for tokenizer-measured context savings; the backward-compatible default returns the full brief plus compact form. Uses metered access. Prefer factreason_api_schema when exploring multiple endpoints.

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• discover

  AgentMarketplace

  Discover AgentMarketplace's capabilities, tools, auth methods, and scopes. Call this first when connecting to AgentMarketplace to understand what's available and how to authenticate. No authentication required. Returns a catalog of available tools, resources, auth methods, and scopes.

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• deadpool_digest

  RightAIChoice — verified AI tool data

  Use this when the user asks how many AI tools die, AI startup failure or shutdown rates, which AI categories decay fastest, how risky the AI tool market is, or for data behind "most AI tools fail" claims. Returns two clearly separated datasets: (1) LIVE catalog decay — 8,000+ verified AI tools with broken vendor-link rates, dead-homepage counts, pricing opacity, and the fastest/slowest-decaying categories, updated daily; (2) a FROZEN dated survival study of 2,291 top Product Hunt launches (of the 2,066 with a determinable outcome, 24.4% are dead within ~2 years). Every figure carries its as-of date. Data comes from the RightAIChoice verification engine; link-decay figures count only VENDOR-published links (site/docs/changelog/repo), never our own derived URLs. Not for: checking one specific tool (use check_tool_status) or predicting a specific tool's future (use viability_score). Decay rates describe categories and cohorts, not individual products.

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