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128,792 tools. Last updated 2026-05-06 06:54

"A resource for in-depth exploration of scientific topics" matching MCP tools:

  • [Step 1 of crisis] Canonical crisis-resource payload (911, 988 Suicide & Crisis Lifeline, Crisis Text Line). Hardcoded — overrides any other tool when high-severity language is detected. Use when: The user mentions self-harm, suicidal ideation, recent attempt, or someone in immediate danger. Surface these resources prominently and stop other tool calls. Don't use when: No mention of crisis or imminent danger. Example: get_crisis_resources({})
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  • Recover detail from camera-shake and accidental motion blur. NAFNet (ECCV 2022, SOTA on GoPro/SIDD benchmarks). Best for: handheld shake, bumped camera, whole-frame uniform blur. NOT effective for: intentional panning blur, bokeh/depth-of-field, or artistic motion effects. Also supports denoising (grainy/noisy photos). 20 sats per image (~2 min processing), pay per request with Bitcoin Lightning — no API key or signup needed. Requires create_payment with toolName='deblur_image'.
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  • Read a JavaScript value from the browser by property path. Walks a strict property path — NO expression evaluation, NO function calls, NO arbitrary code. Accepts identifiers, integer indices in brackets, and double-quoted string keys in brackets. Use this to read runtime state that isn't visible in the DOM: - Framework hydration: window.__NEXT_DATA__.props.pageProps - Redux/Zustand/etc stores (if exposed on window): window.__STORE__._currentState - Feature flags stashed on globals: window.APP.flags - Nested config: window["site-config"].features[0] EXPLORATION MODE: pass mode="keys" to get Object.keys() at the path instead of the value. Start with path="window" to discover globals, then drill in. This is how to find exposed state without guessing: get_js_value(path="window", mode="keys") -> ["document", "__NEXT_DATA__", "store", ...] get_js_value(path="window.store", mode="keys") -> ["_currentState", "subscribe", "dispatch", ...] get_js_value(path="window.store._currentState") -> the actual state object LIMITATIONS (intentional — security): - Cannot call functions. "store.getState()" fails. Expose the value as a readable property instead, e.g. window.__STORE__.state. - No arithmetic, comparisons, or expressions. - Path must start with an identifier and walk down via dots/brackets. Responses are cycle-safe, depth-capped, and size-capped. DOM nodes and React fiber trees are summarized rather than traversed. Args: key: Session key secret: Session secret from create_session path: Property path, e.g. "window.__NEXT_DATA__.props.pageProps" or 'window["site-config"].features[0]' or 'window.arr[0].name' mode: "value" (default) returns the serialized value; "keys" returns Object.keys() at the path max_depth: Max traversal depth when serializing (default 6, capped at 10) max_bytes: Max serialized size in bytes (default 20000, capped at 100000) Returns: {path, type, value, truncated, size_bytes} in value mode {path, mode, type, keys} in keys mode {error: "..."} on bad path / function / failure Requires a connected browser session and middleware v0.9.6+ (older middleware works — the relay doesn't care; the browser needs agent.js from relay.sncro.net which auto-updates).
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  • Search the Nova Scotia Open Data catalog (data.novascotia.ca) for datasets by keyword, category, or tag. Returns dataset names, IDs, descriptions, column names, and direct portal links. Use list_categories first to see valid category and tag names. Use the returned dataset ID with query_dataset or get_dataset_metadata for further exploration.
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  • Deletes a stream, specified by the provided resource 'name' parameter. * The resource 'name' parameter is in the form: 'projects/{project name}/locations/{location}/streams/{stream name}', for example: 'projects/my-project/locations/us-central1/streams/my-streams'. * This tool returns a long-running operation. Use the 'get_operation' tool with the returned operation name to poll its status until it completes. Operation may take several minutes; do not check more often than every ten seconds.
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  • Get a snapshot of the quantum computing landscape — no parameters needed. Use when the user asks broad questions like "how's the quantum job market?", "what are trending topics?", or wants an overview of the quantum computing industry. Returns: total active jobs, top hiring companies, jobs by role type, papers published this week, total researchers tracked, and trending technology tags. For specific job/paper/researcher searches, use the dedicated search tools instead.
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  • Return statistics about the session-scoped resource cache. Useful for verifying that caching is working: call get_synset_info (or similar) twice for the same ID and check that cache_size grows by 1 on the first call but not on the second, and that cached_keys contains the expected IDs. Returns: Dict with: - cache_size: Total number of cached entries - cached_keys: List of (base_url, resource_id) pairs currently cached
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  • The unit tests (code examples) for HMR. Always call `learn-hmr-basics` and `view-hmr-core-sources` to learn the core functionality before calling this tool. These files are the unit tests for the HMR library, which demonstrate the best practices and common coding patterns of using the library. You should use this tool when you need to write some code using the HMR library (maybe for reactive programming or implementing some integration). The response is identical to the MCP resource with the same name. Only use it once and prefer this tool to that resource if you can choose.
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  • Get full details of a published collection including all verse text, references, and topics. Args: collection_id: The collection ID (from browse_collections results).
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  • Task-scoped context briefing. Returns a prioritised context payload shaped by your task description, ranked by risk-if-missed. Constraints and alerts rank above general knowledge. Use at the START of reasoning about a question to get the system's best assessment of what's relevant. Complements query_memory: this gives breadth, query_memory gives depth.
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  • Live orderbook for a Polymarket market. **When to use:** - Bid/ask depth, liquidity, and yes-share / no-share order structure. **Key fields:** - `Order Size` is share quantity, not USD. Do not describe share size as dollar depth unless you calculate `shares × price`. **Yes/No price relationship:** - Yes and No are complementary (Yes + No ≈ $1). A No bid at price $X means willingness to buy No when Yes is near $(1−X). - A cluster of No bids at low prices (e.g. $0.20) is resistance for Yes rallying to ~$0.80, NOT a support floor for the current Yes price. - When comparing OHLCV odds against orderbook depth, convert No-side prices to Yes-equivalent (1 − No price) before drawing divergence conclusions. **Pitfalls:** - Do not treat raw no-share prices as bearish yes-share odds — prefer `prediction_market_ohlcv` for current odds / implied probability. **Prerequisites:** If `marketId` is unknown, call `prediction_market_lookup` first.
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  • Search BGPT's database of scientific papers by keyword. Args: query: Search terms (e.g. "CRISPR gene editing efficiency") Short, concise queries are best. English language only. Don't include years or filters — use the days_back and num_results params instead. num_results: Number of results to return (1-100, default 16). First 50 results are free, then billed at $0.01/result for paid users. days_back: Only return papers published within the last N days. api_key: Optional: Your Stripe subscription ID for paid access. Get one at https://bgpt.pro/mcp Returns: Papers with title, DOI, Raw Data, methods, results, quality scores, and 25+ metadata fields.
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  • Quote the minimum unit price for a buy. Returns `{ minPrice }` (SUN per resource unit) from GraphQL `market.estimateMinPrice` for the given `resourceType`, `buyAmount`, and `durationSec`. Optional `address` scopes context when the API supports it. No login required; an optional session forwards auth like `tronsave_list_order_books`. Read-only and idempotent. Pair with `tronsave_estimate_buy_resource` for full buy quotes and `tronsave_list_order_books` for depth buckets.
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  • Quote the minimum unit price for a buy. Returns `{ minPrice }` (SUN per resource unit) from GraphQL `market.estimateMinPrice` for the given `resourceType`, `buyAmount`, and `durationSec`. Optional `address` scopes context when the API supports it. No login required; an optional session forwards auth like `tronsave_list_order_books`. Read-only and idempotent. Pair with `tronsave_estimate_buy_resource` for full buy quotes and `tronsave_list_order_books` for depth buckets.
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  • Search across all kapoost's pieces — poems, essays, notes, images. Matches query against title, body, tags, and description. Returns matching pieces with a preview snippet. Use this instead of reading every piece when looking for specific themes, words, or topics.
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  • Search the Nova Scotia Open Data catalog (data.novascotia.ca) for datasets by keyword, category, or tag. Returns dataset names, IDs, descriptions, column names, and direct portal links. Use list_categories first to see valid category and tag names. Use the returned dataset ID with query_dataset or get_dataset_metadata for further exploration.
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  • Search quantum computing research papers from arXiv. Use when the user asks about recent research, specific papers, or academic topics in quantum computing. NOT for jobs (use searchJobs) or researcher profiles (use searchCollaborators). Supports natural language queries decomposed via AI into structured filters (topic, tag, author, affiliation, domain). Date range defaults to last 7 days; max lookback 12 months. Returns newest first, max 50 results. Use getPaperDetails for full abstract and analysis of a specific paper. Examples: "trapped ion papers from Google", "QEC review papers this month", "quantum error correction".
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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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