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134,170 tools. Last updated 2026-05-24 20:53

"An explanation or exploration of reasoning" matching MCP tools:

  • Check whether a factual claim is supported by a specific set of public evidence URLs that you already have. For each source, the tool performs a case-insensitive keyword match over the fetched page body, then marks that source as supporting the claim when at least half of the supplied keywords appear. Use this for evidence-backed claim checks on known pages, not for open-ended search, semantic reasoning, or contradiction extraction. The aggregate verdict is driven only by the per-page keyword support ratio. Fetched pages are cached for 5 minutes.
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  • Ask AlgoVault a natural-language question — get a synthesized answer with citations, grounded in the canonical knowledge bundle (every MCP tool description, response shape, integration tutorial, and code example). Use this when you need an explanation, code pattern, or "how do I" answer. For raw ranked snippets without LLM synthesis, use search_knowledge (faster, no quota cost). Quota: Free 10/month, Starter 50/month, Pro 200/month, Enterprise 2000/month.
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  • Call this tool BEFORE your agent passes any user-provided content to an external API, LLM call, or third-party service. An agent that forwards unredacted user input to an external endpoint without classification is a data exfiltration vector -- a single GDPR Article 9 breach or HIPAA PHI disclosure carries regulatory fines with no recovery path once the data has left. This tool operates at the infrastructure layer -- before the LLM reasoning loop -- classifying content against 10 frameworks including GDPR, HIPAA, PCI-DSS, and CCPA. Returns SAFE_TO_PROCESS, REDACT_BEFORE_PASSING, DO_NOT_STORE, or ESCALATE verdict and agent_action field. One call replaces a full compliance review cycle. We do not log your query content. Free tier: 20 calls/month, no API key required.
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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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  • Check the status of an async operation (presentation, slide, export, or transcript). Status values: pending, in_progress, completed, failed. Poll every 2-5 seconds. Most operations complete in 30-120 seconds.
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  • Purpose: Expose OneQAZ's pre-defined causal hypothesis map. Each macro category (bonds, forex, vix, credit, liquidity, inflation, commodities, energy) is mapped to a target market with lag_hours + sensitivity. Highest-transparency tool — the causal reasoning is visible and measurable. When to call: when an AI wants to understand WHY we make certain predictions. Prerequisites: none. Next steps: get_backtest_tuning_state for runtime calibration of these hypotheses. Caveats: static hypothesis only; see tuning state for current adjustments. Args: market_id: Optional target market filter (coin_market, kr_market, us_market) Disclaimer: Information only, not investment advice.
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  • Propose changes to the renter's MAILBOX.md instructions with reasoning. The renter will see your suggestion in their dashboard and can accept, reject, or modify it. Use this when you observe patterns that could be codified into standing instructions.
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  • Upload an asset (image, font, PDF, etc). Provide exactly one of: content (base64), content_text (plain text for JS/CSS/JSON/SVG — preferred, saves tokens), or source_url (public HTTPS URL for images). Set overwrite: true to replace an existing asset.
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  • Mutating. Report a problem or observation encountered during gameplay. The report is saved to the match replay, server log, and a daily debug file for later review. category must be one of: 'bug', 'confusion', 'rules_unclear', 'scenario_issue', 'imbalance', or 'suggestion'. Use 'imbalance' for lopsided scenarios; use 'scenario_issue' for broken placement or unreachable tiles. summary is a short description (max 500 chars, required). details is an optional longer explanation (max 10,000 chars). Requires state=in_game.
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  • Fetch one filing by SEC accession number, regardless of recency. Useful when an agent has an accession number from a citation or earlier tool call and needs the parsed details. Args: accession_number: SEC accession in 'XXXXXXXXXX-YY-NNNNNN' format. Returns: JSON for the filing if found in our archive, or {"found": false}.
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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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  • 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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  • Step 1 of the MCP donation flow. Required inputs: campaign_id, amount, and reasoning. This tool validates that the campaign is eligible to receive donations but does not record any donation yet. On success it returns payment instructions: wallet_address, amount, network, and currency. After sending the on-chain payment, call confirm_donation with the same campaign_id, amount, reasoning, and the resulting tx_hash.
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  • Get a detailed explanation of a specific edit from a positioning review (1 credit). The change_id comes from the edits array returned by ceevee_confirm_lens or ceevee_full_review. Returns a detailed rationale for the recommended change. cv_version_id from ceevee_upload_cv or ceevee_list_versions.
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  • Update an existing node's label and/or its space assignments. Omitted fields are unchanged. spaceIds replaces (not merges) existing assignments; empty array = default space. At least one of label or spaceIds must be provided.
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  • List all candidates in a hiring context. Returns an array of candidate objects, each with an 'id' field. Use candidate id as candidate_id in atlas_start_gem_analysis, atlas_fit_match, atlas_fit_rank, atlas_generate_interview, and batch tools. Requires context_id from atlas_create_context or atlas_list_contexts. Free.
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  • Execute a DPX cross-border settlement. The Settlement Agent checks oracle conditions, reasons with Claude AI, and executes on-chain (or returns sandbox result if sandbox=true). Returns settlement ID, status (executed/held/sandbox/failed), tx hash, net amount, fees, oracle conditions, and AI reasoning. Default: sandbox=true — set sandbox=false only for live execution.
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  • Catch contradictions in reasoning before acting on it. FREE — no account needed. Extracts quantitative and logical claims from any plan, calculation, or chain of thought, then uses a Z3 SAT solver to mathematically prove whether they contradict each other. This is formal verification, not an LLM second-guessing itself. Returns CONSISTENT, CONTRADICTION, or UNKNOWN with the extracted claims.
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  • Get a concise explanation of what Crinkl is and how the protocol works. Use this first if you have no prior context about Crinkl. Returns a plain-text overview of the verification pipeline, token types, and settlement model.
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  • Request an early stop on an in-flight training run. Distinct from cancel: the run finishes the current phase gracefully (mining or training) instead of terminating immediately.
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