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163,884 tools. Last updated 2026-05-30 20:37

"Artifact Hub" matching MCP tools:

  • Looks up each submitted domain in the TunnelMind tracker database, aggregates risk metrics (avg score, max score, fingerprinters, high-risk domains, entity ownership), and issues a signed surveillance receipt. The receipt is stored in the public registry and can be verified at `/verify/{receipt_id}`. Use this tool when: - You want a verifiable record of which trackers were observed in a context (page, app, session). - You need a signed evidence artifact for a privacy audit or compliance report. - You want to know the overall surveillance exposure level for a set of domains. - You are generating a receipt to share with a user as evidence of tracker presence. Do NOT use this tool when: - You want full tracker details per domain — use `get_domain` instead. - You want to look up an existing receipt — use `get_receipt` instead. - You need live probes (HTTP headers, stack detection) — use `/v1/intel/*` instead. Inputs: - `domains` (body, required): Array of 1–50 fully qualified domain names. Duplicates are deduplicated. URLs are stripped to host component. - `domain` (body, alternative): Single domain string (shorthand for `domains: [domain]`). Returns: - `receipt_id`: Unique receipt ID (e.g. `rcpt_01JXYZ...`). - `receipt`: Full receipt document including domains submitted, tracker findings, high-risk domains, fingerprinters, unique entities, and exposure metrics. - `content_hash`: SHA-256 of the canonical receipt JSON. - `signature`: Base64 Ed25519 signature (empty string if signing key not configured). - `signed`: Boolean — true if the receipt is cryptographically signed. - `verify_url`: Path to retrieve this receipt from the public registry. Exposure levels: `minimal` / `moderate` / `high` / `critical` Based on average tracker score and proportion of high-risk domains (score ≥ 70). Cost: - Counts as one request against the daily limit regardless of domain count. Latency: - Typical: <100ms (pure D1 lookup, no outbound probing). p99: <300ms.
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  • Retrieve a zero-knowledge proof circuit by its circuitId via GET /v1/circuits/{circuitId}. A circuit defines the constraints that proofs must satisfy and binds to a single schema. Returns CircuitMeta { circuitId, schema, description?, inputs?, verifier?: { type: 'onchain'|'offchain', address?, chainId? }, artifact?: { location: { type: 'ipfs'|'https', wasm, zkey } } }. Use this before lemma_submit_proof to confirm the circuit's schema, public inputs, and verifier configuration. Circuits are immutable; new variants get new circuitIds.
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  • Search the MITRE D3FEND catalog of defensive techniques by keyword, tactic, or targeted artifact. Default response is SLIM (drops `uri` from each row — saves ~60 chars/row, ~30% on popular drills); pass include='full' for the verbose record. Pass exclude_id when chaining from d3fend_defense_lookup to skip self in sibling-artifact searches. Use to discover defenses applicable to a given threat model — e.g. 'what defenses harden access tokens?' (tactic=Harden + artifact='Access Token'). Drill into d3fend_defense_lookup with any returned defense_id for the ATT&CK technique mappings. Free: 30/hr, Pro: 500/hr. Returns {query, total, results [{defense_id, label, uri (only when include=full), parent_label, tactic, artifact}], next_calls}.
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  • Returns file metadata (content_type, download_url, download_size, expires_at) for the report or zip artifact. Use artifact='report' (default) for the interactive HTML report (~700KB, self-contained with embedded JS for collapsible sections and interactive Gantt charts — open in a browser). Use artifact='zip' for the full pipeline output bundle (md, json, csv intermediary files that fed the report). While the task is still pending or processing, returns {ready:false,reason:"processing"}. Check readiness by testing whether download_url is present in the response. Once ready, present download_url to the user or fetch and save the file locally. Download URLs expire after 15 minutes (see expires_at); call plan_file_info again to get a fresh URL if needed. Terminal error codes: generation_failed (plan failed), content_unavailable (artifact missing). Unknown plan_id returns error code PLAN_NOT_FOUND.
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  • Show the structure of all three pitakas with coverage statistics. 💡 **Use this tool when:** - The user asks for an overview of the Tipiṭaka (what's in it / which collections). - You need to check coverage before promising a search will find something — `segment_count > 0` is the active-loaded signal. - Verifying scope when compiling an artifact. 📊 **Current state (v1.1+, at parity with SuttaCentral bilara-data):** - **Sutta Piṭaka** complete: DN 37, MN 155, SN 1,829, AN 1,419, KN 2,351 sections (~284,702 segments) — Pāli + Sujato EN - **Vinaya Piṭaka** complete: Bhikkhu Vibhaṅga 222, Bhikkhunī Vibhaṅga 127, Khandhaka 22, Parivāra 51 + Pātimokkha 2 (~71,557 segments) — Pāli + Brahmali EN - **Abhidhamma Piṭaka** complete: 7 books (ds, vb, dt, pp, kv, ya, patthana) ~88,414 segments — Pāli only (bilara has no English for any Abhidhamma book) - **Total ~444,673 segments** in the DB ⚠️ **Known quirks:** - The schema carries duplicate legacy + SC-modern codes side by side: - Vinaya: `vin-v/vin-m/vin-c/vin-p` (legacy, segment_count = 0) alongside `pli-tv-bu-vb/pli-tv-bi-vb/pli-tv-kd/pli-tv-pvr` (active, populated). - Abhidhamma: `ym/pt` (legacy = 0) alongside `ya/patthana` (active). - **Always pick the code with `segment_count > 0`** — the others are metadata placeholders from an older migration. 🌐 **Languages:** Returns Pāli + Thai + English labels regardless of enabled set (these are metadata, not segment text). Text content follows ENABLED_LANGUAGES. Thai translations aren't loaded yet — Thai users can fall back to the cross_reference 84000.org link. Returns: Hierarchical structure: - pitakas{vinaya/sutta/abhidhamma} → nikayas[] - Each nikaya: code, name (3 languages), sutta_count, segment_count.
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  • Use this read-only tool to check whether the Azure-native ATLAS-7 full-universe regression audit is healthy. It reads the latest audit summary artifact from Azure Blob and reports last successful run time, issuer count, operation count, failure counts, historical route status, composite route status, and artifact prefix. Parameters: none. Behavior: read-only and idempotent; it has no destructive side effects, does not run the audit, mutate data, or access raw issuer evidence. Use this before trusting historical ATLAS-7 surfaces in an agent workflow or when an operator asks whether the nightly 215-issuer audit is current.
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  • Fetch the next page of a large tool response. Use the nextCursor from _pagination in a previous response. This tool loads data into the context window — prefer the artifact download URL when available.
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  • Get a swap quote from the SODAX solver. IMPORTANT: tokenSrc/tokenDst must be hub-chain asset addresses — the SODAX hub is Sonic (chainId 146); spoke-chain token addresses are rejected with 'not compatible with the quote service'. Call sodax_get_solver_oracle with chainId='146' to look up valid token addresses. quote_type='exact_input' quotes the destination amount you'd receive; 'exact_output' quotes the source amount you'd need to supply. Returns 'No path found' if the solver can't route between the tokens.
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  • Get comprehensive US energy market status for supply chain cost analysis. Returns crude oil prices (WTI and Brent), natural gas spot prices (Henry Hub), retail fuel prices (gasoline, diesel), natural gas storage versus capacity, refinery utilization rates, petroleum stock levels with week-over-week changes, and import/export flows. This is the disaggregated view behind the GDI Energy pillar — instead of a single risk number, you get the full picture of energy costs affecting manufacturing, freight, and logistics. Used by supply chain cost analysts, transportation managers, and energy procurement teams.
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  • Returns the RAW body of one agent-onboarding artifact shipped with a store template (system prompt, Agent Skills SKILL.md, MCP-config snippet, …). Placeholders ({{slot:KEY.prop}}) are NOT substituted — use this BEFORE installing the template, when there is no display yet to resolve slot slugs against. After install, use get_display_agent_artifact for the placeholder-substituted body ready to paste/save. Discover available artifact keys via get_store_template_details (agentArtifacts array). No authentication required.
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  • Inventory mode. List all 19 AXIS programs, their generators, pricing tier, and artifact paths. Free, no auth, and no side effects. Use search_and_discover_tools instead when you only have a keyword, or discover_commerce_tools when you need install and onboarding metadata.
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  • Use this read-only tool to check whether the Azure-native ATLAS-7 full-universe regression audit is healthy. It reads the latest audit summary artifact from Azure Blob and reports last successful run time, issuer count, operation count, failure counts, historical route status, composite route status, and artifact prefix. Parameters: none. Behavior: read-only and idempotent; it has no destructive side effects, does not run the audit, mutate data, or access raw issuer evidence. Use this before trusting historical ATLAS-7 surfaces in an agent workflow or when an operator asks whether the nightly 215-issuer audit is current.
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  • Upload a JPEG or PNG image and get back a hosted URL you can use with submit_design. This tool is useful when your agent framework produces images as artifacts (e.g. base64 strings) and you need to upload them before submitting a design. Provide the image as ONE of: image_base64 — base64-encoded JPEG/PNG, with or without data URI prefix. image_url — publicly accessible image URL (max 5 MB). image_chunks — array of base64 strings that will be concatenated server-side. Use this if your base64 string is too large for a single parameter. Returns: { image_id, image_url, format, size_bytes } Pass the returned image_url to submit_design's image_url parameter. ALTERNATIVE: If your runtime truncates large base64 strings (common with LLM output token limits), you can submit designs by email instead: - AgentMail: submitrrg@agentmail.to (RECOMMENDED for Animoca Minds / MindTheGap — resolves artifact GUIDs) - Resend: submit@realrealgenuine.com Attach the image as JPEG/PNG. Subject: "RRG: Title". Body: wallet: 0x...
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  • Return the full structured dossier for a named entity — the canonical citable artifact for any actor, organization, ordinance, or project the corpus references. Returns: voxel_lead (134-167 word voxel-disciplined identity prose), canonical_role, the class-specific cluster (person.voting_record for board members; organization.type + jurisdiction; legislation.legal_status + effective_date + sunset_date + citation; creative_work.work_type + status + case_number), the bidirectional graph references (appears_in_meetings, appears_in_briefs, appears_in_watches, exhibits_patterns, related_entities, related_places, related_corridors), the provenance_chain, and the canonical surfaces (dossier URL, schema_id, decoder_index_hub). Each schema_id (`/entities/{slug}#{class.toLowerCase()}`) is the stable cross-page Schema.org reference — Person / Organization / Legislation / CreativeWork — that AI agents resolve to when citing the entity. Use when grounding a citation, when reasoning about an entity's full role across the corpus, or when traversing the entity graph from a single name.
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  • Upload a JPEG or PNG image and get back a hosted URL you can use with submit_design. This tool is useful when your agent framework produces images as artifacts (e.g. base64 strings) and you need to upload them before submitting a design. Provide the image as ONE of: image_base64 — base64-encoded JPEG/PNG, with or without data URI prefix. image_url — publicly accessible image URL (max 5 MB). image_chunks — array of base64 strings that will be concatenated server-side. Use this if your base64 string is too large for a single parameter. Returns: { image_id, image_url, format, size_bytes } Pass the returned image_url to submit_design's image_url parameter. ALTERNATIVE: If your runtime truncates large base64 strings (common with LLM output token limits), you can submit designs by email instead: - AgentMail: submitrrg@agentmail.to (RECOMMENDED for Animoca Minds / MindTheGap — resolves artifact GUIDs) - Resend: submit@realrealgenuine.com Attach the image as JPEG/PNG. Subject: "RRG: Title". Body: wallet: 0x...
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  • Module visualization tool. Use when the user wants to understand how a module's modes work, how parameters change between modes, or what a specific mode does — a visualization communicates the per-mode behavior better than prose. The host renders the result inline in the chat as an interactive visualization (mode buttons, per-mode descriptions, schematic curves); you do not need to build an artifact yourself — just call this tool. Do not use for general module specs (HP, jacks, capabilities) — call get_module instead. After calling, your prose can reference what the user is seeing in the visualization (e.g. "in formant mode, all three outputs become bandpass filters") rather than describing the visualization itself. Currently supported viz families: - filter_response — filters with characterized response curves (e.g. Three Sisters, Ripples, Belgrad, A-124, Filter 8, QPAS, SVF 1U, Cinnamon, C4RBN, Ikarie) - oscillator_morph — multi-mode oscillators and excited resonators (e.g. Rings, Loquelic Iteritas, Plaits) A module is supported when every one of its modes has a behavior_model_id the renderer knows. If you're unsure whether a given module qualifies, just call this tool — the error names the gap. Errors: - "Module not found: <id>" if no module with that id exists. - "Module not yet supported by visualize_module: <id>" when one or more modes lack a renderer-known behavior_model_id, or when the module mixes incompatible viz families. Suggest get_module for the underlying spec. The returned spec is a JSON object with: module_id, module_name, manufacturer, viz_type, params[], modes[], response_model_id, presets[]. Each mode has a behavior_model_id that the renderer uses to pick the curve set (e.g. crossover_lp_bp_hp vs formant_three_bp for filter_response). `response_model_id` (top-level) vs per-mode `behavior_model_id`: for multi-mode modules the top-level field is intentionally null — each mode carries its own behavior_model_id since the modes use different curve sets (e.g. Three Sisters' crossover vs formant). Read the per-mode values from `modes[].behavior_model_id`. The top-level is populated only for single-curve modules where one model applies across the whole module. `null` at top-level + populated per-mode = "modes carry distinct models," not a bug.
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  • Scrape Docker Hub image page with tag history, dockerfile signals. Heavier than lookup/dockerhub. Use for supply-chain audits. Example call: {"image": "library/nginx"} Cost: $0.005–$0.05 USDC on Base per call.
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  • P80 — query the persistent proof ledger. USE WHEN the user (or a dashboard) asks 'what has ChiefLab actually shipped for this workspace?' or 'show me the launch history.' Returns the proof rows for executed publishes / sends / manual-posts with the artifact URLs, channels, execution modes, and measurement state. Persistent across cold starts when deps.proofLedgerStore is wired to Supabase; falls back to in-memory (warm function lifetime) otherwise.
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  • Get real-time air cargo disruption status at major US and international freight hub airports. Returns FAA ground delays, ground stops, arrival and departure delays with estimated minutes, closure status, disruption score, and traffic collapse detection. Covers major cargo hubs including Memphis (FedEx), Louisville (UPS), Anchorage, Chicago O'Hare, Los Angeles, Miami, New York JFK, and Dallas-Fort Worth. Used by air freight forwarders, express carriers, and logistics planners to reroute time-sensitive shipments around airport disruptions.
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  • Creates a tester group for a Release Management connected app. Tester groups can be used to distribute installable artifacts to testers automatically. When a new installable artifact is available, the tester groups can either automatically or manually be notified via email. The notification email will contain a link to the installable artifact page for the artifact within Bitrise Release Management. A Release Management connected app can have multiple tester groups. Project team members of the connected app can be selected to be testers and added to the tester group. This endpoint has an elevated access level requirement. Only the owner of the related Bitrise Workspace, a workspace manager or the related project's admin can manage tester groups.
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