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166,954 tools. Last updated 2026-06-02 20:00

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  • Search the Charity Commission register of England and Wales by name or keyword. Returns matching charities with registration number, status, and registration date. Use charity_profile for full details once you have the charity number. The upstream `searchCharityName` endpoint returns the full list in one shot — pagination is applied client-side via offset/limit.
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  • Get comprehensive token screening data across multiple blockchain networks with advanced filtering. A maximum of 25 results are returned out of 1000s of tokens. Use the sorting and filtering options to narrow down the results. A maximum of 5 chains can be specified per request (excess chains are automatically trimmed). This tool helps with token discovery and finding trending tokens by combining different metrics: volume, liquidity, market cap, smart money activity, and token age. **IMPORTANT - Hyperliquid Special Case:** - Hyperliquid chain queries perpetual futures (perps), not spot tokens - When hyperliquid is mixed with other chains, two sections of up to 25 results each are returned - one for spot tokens and one for perps. - For perps, only these filters are supported: volume, buyVolume, sellVolume, openInterest, netflow, nofTraders, traderType - Additional orderBy fields for perps: openInterest, funding - Unsupported filters/orderBy will fallback to defaults INPUT EXAMPLES: # Find tokens which are going up in price. # Added some liquidity filter to remove spam and low quality tokens. ``` { "chains": ["ethereum", "solana", "bnb", "base"], "timeframe": "24h", "liquidity": {"from": 100000}, "nofTraders": {"from": 10}, "orderBy": "price_change", "orderByDirection": "desc" } ``` # Find top stablecoins by market cap ``` { "chains": ["ethereum", "solana", "bnb", "base"], "timeframe": "7d", "sectors": ["Stablecoin"], "orderBy": "market_cap_usd", "orderByDirection": "desc" } ``` # Find AI memecoins with high trading activity { "chains": ["ethereum", "solana", "bnb", "base"], "timeframe": "7d", "sectors": ["AI Meme"], "liquidity": {"from": 100000}, "volume": {"from": 1000000} } # Find DeFi lending tokens { "chains": ["ethereum", "solana", "bnb", "base"], "timeframe": "24h", "sectors": ["DeFi Lending (Money Markets)"], "netflow": {"from": 1000000} } # Find tokens which have a lot of buying activity (high nofBuyers and buyVolume) # Note that we added some filters to remove spam and low quality tokens. We added liquidity filter so that we only surface tokens which we can buy or sell. # We sort by `netflow` descending to get tokens with the most net buying activity. ``` { "chains": ["ethereum", "solana", "bnb", "base"], "timeframe": "24h", "liquidity": {"from": 100000}, "buyVolume": {"from": 1000000}, "marketCapUsd": {"from": 1000000}, "nofBuyers": {"from": 10}, "orderBy": "netflow", "orderByDirection": "desc" } ``` # Find Hyperliquid perps with high open interest and positive net flow ``` { "chains": ["hyperliquid"], "timeframe": "7d", "openInterest": {"from": 100000}, "volume": {"from": 1000000}, "netflow": {"from": 0}, "nofTraders": {"from": 10}, "orderBy": "netflow", "orderByDirection": "desc" } ``` WARNING: To avoid timeouts, it's recommended to: - Use 4 chains or less at a time (API tends to timeout with more chains) - Use shorter timeframes (e.g., 24h or 1h instead of 7d or 30d) Args: Returns: Comprehensive token metrics as markdown. Returns empty string if no tokens found. Columns returned: - **Token Address**: Token address (e.g., 0x1234567890123456789012345678901234567890) - **Symbol**: Token trading symbol (e.g., ETH, BTC, DOGE) - **Chain**: Blockchain network (ethereum, solana, polygon, etc.) - **Price USD**: Current token price in USD (currency formatted) - **Price Change**: Price change percentage over the date range (percentage, can be negative) - **Market Cap**: Current market capitalization (currency formatted) - **Fully Diluted Valuation (FDV)**: Market cap if all tokens were circulating (currency formatted) - **FDV/MC Ratio**: Ratio indicating how much supply is locked/vested (numeric, >1 means locked supply) - **USD Volume**: Total trading volume in USD (currency formatted) - **Buy USD Volume**: Total buy volume in USD (currency formatted) - **Sell USD Volume**: Total sell volume in USD (currency formatted) - **Net Flow USD**: Net flow (buys minus sells) in USD (currency formatted, can be negative) - **DEX Liquidity**: Available liquidity for trading (currency formatted) - **Inflow/FDV**: Inflow as percentage of FDV (percentage formatted) - **Outflow/FDV**: Outflow as percentage of FDV (percentage formatted) - **Token Age (Days)**: Days since token was first deployed - **Sectors**: List of token sectors/categories Hyperliquid perps columns (smart-money mode, when `onlySmartTradersAndFunds=true`): - **Net Position** (`LONG $X` / `SHORT $X` / `FLAT`): current net direction. Use this when answering long/short questions. - **Current Longs USD** / **Current Shorts USD**: gross notional on each side; sizing only, not direction. - **Net Position Change**: delta over the timeframe — can be positive while Net Position is still SHORT. Notes: - Positive Net Flow on spot tokens indicates more buying than selling - High FDV/MC Ratio suggests significant locked or vested tokens **Filtering Options** (filters parameter): - **Numeric Ranges**: volume, liquidity, marketCapUsd, netflow, tokenAgeDays, nofTraders, nofBuyers, nofSellers, nofBuys, nofSells, buyVolume, sellVolume, fdv, fdvMcRatio, inflowFdvRatio, outflowFdvRatio - **Categories**: sectors (e.g. ["AI", "Meme"]), includeSmartMoneyLabels - **Trader Type**: traderType (string: "all", "sm", "whale", "public_figure") - Use "sm" ONLY when user explicitly asks for "smart money". - Use "whale" ONLY when user specifically asks for whales or large holders. - Use "public_figure" ONLY when user asks for KOLs or popular figures. - Data with "sm", "whale", and "public_figure" is sparse — "whale" and "public_figure" are even sparser than "sm". Pairing any of these with other filters (volume, liquidity, netflow) is likely to return no results. - Only pair traderType="sm/whale/public_figure" with other filters (volume, liquidity, netflow) if the user request explicitly requires it. - Instead of pairing this with other filters, you can rely on orderBy to sort by netflow, volume, liquidity, etc. **CRITICAL WARNING:** 'priceChange' is NOT a valid filter. You cannot filter for "tokens up > 10%". Use `orderBy="priceChange"` instead. **Sorting Options** (orderBy field): Available fields (use with orderByDirection: "asc" or "desc"): - **priceUsd**: Sort by token price - **priceChange**: Sort by price change percentage - **marketCapUsd**: Sort by market capitalization - **volume**: Sort by total trading volume - **buyVolume**: Sort by buy volume - **sellVolume**: Sort by sell volume - **netflow**: Sort by net flow (buys - sells) - **liquidity**: Sort by DEX liquidity - **nofTraders**: Sort by number of traders (Note: Fields like `tokenAgeDays` or `outflowFdvRatio` are for FILTERING only, not sorting) Default: orderBy="netflow", orderByDirection="desc"
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  • Get comprehensive token screening data across multiple blockchain networks with advanced filtering. A maximum of 25 results are returned out of 1000s of tokens. Use the sorting and filtering options to narrow down the results. A maximum of 5 chains can be specified per request (excess chains are automatically trimmed). This tool helps with token discovery and finding trending tokens by combining different metrics: volume, liquidity, market cap, smart money activity, and token age. **IMPORTANT - Hyperliquid Special Case:** - Hyperliquid chain queries perpetual futures (perps), not spot tokens - When hyperliquid is mixed with other chains, two sections of up to 25 results each are returned - one for spot tokens and one for perps. - For perps, only these filters are supported: volume, buyVolume, sellVolume, openInterest, netflow, nofTraders, traderType - Additional orderBy fields for perps: openInterest, funding - Unsupported filters/orderBy will fallback to defaults INPUT EXAMPLES: # Find tokens which are going up in price. # Added some liquidity filter to remove spam and low quality tokens. ``` { "chains": ["ethereum", "solana", "bnb", "base"], "timeframe": "24h", "liquidity": {"from": 100000}, "nofTraders": {"from": 10}, "orderBy": "price_change", "orderByDirection": "desc" } ``` # Find top stablecoins by market cap ``` { "chains": ["ethereum", "solana", "bnb", "base"], "timeframe": "7d", "sectors": ["Stablecoin"], "orderBy": "market_cap_usd", "orderByDirection": "desc" } ``` # Find AI memecoins with high trading activity { "chains": ["ethereum", "solana", "bnb", "base"], "timeframe": "7d", "sectors": ["AI Meme"], "liquidity": {"from": 100000}, "volume": {"from": 1000000} } # Find DeFi lending tokens { "chains": ["ethereum", "solana", "bnb", "base"], "timeframe": "24h", "sectors": ["DeFi Lending (Money Markets)"], "netflow": {"from": 1000000} } # Find tokens which have a lot of buying activity (high nofBuyers and buyVolume) # Note that we added some filters to remove spam and low quality tokens. We added liquidity filter so that we only surface tokens which we can buy or sell. # We sort by `netflow` descending to get tokens with the most net buying activity. ``` { "chains": ["ethereum", "solana", "bnb", "base"], "timeframe": "24h", "liquidity": {"from": 100000}, "buyVolume": {"from": 1000000}, "marketCapUsd": {"from": 1000000}, "nofBuyers": {"from": 10}, "orderBy": "netflow", "orderByDirection": "desc" } ``` # Find Hyperliquid perps with high open interest and positive net flow ``` { "chains": ["hyperliquid"], "timeframe": "7d", "openInterest": {"from": 100000}, "volume": {"from": 1000000}, "netflow": {"from": 0}, "nofTraders": {"from": 10}, "orderBy": "netflow", "orderByDirection": "desc" } ``` WARNING: To avoid timeouts, it's recommended to: - Use 4 chains or less at a time (API tends to timeout with more chains) - Use shorter timeframes (e.g., 24h or 1h instead of 7d or 30d) Args: Returns: Comprehensive token metrics as markdown. Returns empty string if no tokens found. Columns returned: - **Token Address**: Token address (e.g., 0x1234567890123456789012345678901234567890) - **Symbol**: Token trading symbol (e.g., ETH, BTC, DOGE) - **Chain**: Blockchain network (ethereum, solana, polygon, etc.) - **Price USD**: Current token price in USD (currency formatted) - **Price Change**: Price change percentage over the date range (percentage, can be negative) - **Market Cap**: Current market capitalization (currency formatted) - **Fully Diluted Valuation (FDV)**: Market cap if all tokens were circulating (currency formatted) - **FDV/MC Ratio**: Ratio indicating how much supply is locked/vested (numeric, >1 means locked supply) - **USD Volume**: Total trading volume in USD (currency formatted) - **Buy USD Volume**: Total buy volume in USD (currency formatted) - **Sell USD Volume**: Total sell volume in USD (currency formatted) - **Net Flow USD**: Net flow (buys minus sells) in USD (currency formatted, can be negative) - **DEX Liquidity**: Available liquidity for trading (currency formatted) - **Inflow/FDV**: Inflow as percentage of FDV (percentage formatted) - **Outflow/FDV**: Outflow as percentage of FDV (percentage formatted) - **Token Age (Days)**: Days since token was first deployed - **Sectors**: List of token sectors/categories Hyperliquid perps columns (smart-money mode, when `onlySmartTradersAndFunds=true`): - **Net Position** (`LONG $X` / `SHORT $X` / `FLAT`): current net direction. Use this when answering long/short questions. - **Current Longs USD** / **Current Shorts USD**: gross notional on each side; sizing only, not direction. - **Net Position Change**: delta over the timeframe — can be positive while Net Position is still SHORT. Notes: - Positive Net Flow on spot tokens indicates more buying than selling - High FDV/MC Ratio suggests significant locked or vested tokens **Filtering Options** (filters parameter): - **Numeric Ranges**: volume, liquidity, marketCapUsd, netflow, tokenAgeDays, nofTraders, nofBuyers, nofSellers, nofBuys, nofSells, buyVolume, sellVolume, fdv, fdvMcRatio, inflowFdvRatio, outflowFdvRatio - **Categories**: sectors (e.g. ["AI", "Meme"]), includeSmartMoneyLabels - **Trader Type**: traderType (string: "all", "sm", "whale", "public_figure") - Use "sm" ONLY when user explicitly asks for "smart money". - Use "whale" ONLY when user specifically asks for whales or large holders. - Use "public_figure" ONLY when user asks for KOLs or popular figures. - Data with "sm", "whale", and "public_figure" is sparse — "whale" and "public_figure" are even sparser than "sm". Pairing any of these with other filters (volume, liquidity, netflow) is likely to return no results. - Only pair traderType="sm/whale/public_figure" with other filters (volume, liquidity, netflow) if the user request explicitly requires it. - Instead of pairing this with other filters, you can rely on orderBy to sort by netflow, volume, liquidity, etc. **CRITICAL WARNING:** 'priceChange' is NOT a valid filter. You cannot filter for "tokens up > 10%". Use `orderBy="priceChange"` instead. **Sorting Options** (orderBy field): Available fields (use with orderByDirection: "asc" or "desc"): - **priceUsd**: Sort by token price - **priceChange**: Sort by price change percentage - **marketCapUsd**: Sort by market capitalization - **volume**: Sort by total trading volume - **buyVolume**: Sort by buy volume - **sellVolume**: Sort by sell volume - **netflow**: Sort by net flow (buys - sells) - **liquidity**: Sort by DEX liquidity - **nofTraders**: Sort by number of traders (Note: Fields like `tokenAgeDays` or `outflowFdvRatio` are for FILTERING only, not sorting) Default: orderBy="netflow", orderByDirection="desc"
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  • Search notes by keyword or list recent notes. Returns summaries (id + description) only. Use get_note to retrieve the full content of a specific note. With query: Case-insensitive keyword search on description and content. Without query: Returns most recently updated notes.
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  • Search the Sovereign AI Blog for articles matching a natural language query, optionally filtered by tag and sorted by relevance or date. Behaviour matrix: - query='', sort=* -> list newest-first, optionally tag-filtered - query!='', sort=relevance -> TF-IDF ranked, optionally tag-filtered - query!='', sort=date_desc -> TF-IDF filtered (score > 0.001), then sorted by date Pure read-only, deterministic for a given KB snapshot.
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  • Delete a cron job by line number. Get line numbers from list_cron(). Requires: API key with write scope. Args: slug: Site identifier line_number: Line number of the cron entry to delete Returns: {"deleted": true}
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Matching MCP Connectors

  • iss-number MCP — wraps StupidAPIs (requires X-API-Key)

  • phoenix-number MCP — wraps StupidAPIs (requires X-API-Key)

  • Get deduplicated canonical obligations with enforcement intelligence. Returns one obligation per unique legal requirement per actor role. Each includes compliance difficulty, guidance, and enforcement metrics. Use this instead of get_obligations when you want a clean, deduplicated view of what a regulated entity must comply with, enriched with enforcement risk data. Args: regulation: Filter by regulation code (e.g. 'dora', 'mica', 'aml'). actor_role: Comma-separated actor roles (e.g. 'credit_institution,significant_institution'). entity_type: Filter by entity type code (e.g. 'credit_institution'). compliance_difficulty: Filter by difficulty: 'low', 'medium', 'high', 'critical'. min_enforcement_count: Only return obligations with at least this many enforcement actions. sort: Sort order. Options: 'enforcement_count_desc' (default), 'compliance_difficulty_desc', 'regulation', 'actor_role'. page: Page number (default 1). per_page: Results per page (default 20, max 100).
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  • Search for businesses by name, phone number, or location. Returns a list of business candidates with confidence scores. Use this to find existing businesses before creating a website. Requires authentication via API key (Bearer token). Generate an API key at webzum.com/dashboard/account-settings. Examples: - "Joe's Pizza Brooklyn" - search by name and location - "555-123-4567" - search by phone number - "plumber in San Diego" - search by service and location Returns up to 10 candidates ranked by confidence.
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  • Get full document content by URL from DevExpress documentation. Use this tool to retrieve the complete markdown content of a specific documentation page. PREREQUISITE: ALWAYS call `devexpress_docs_search` before using this tool to get valid URLs. The URL parameter must be obtained from the results of the `devexpress_docs_search` tool.
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  • Fetches the complete markdown content of an Apollo documentation page using its slug, or everything after https://apollographql.com/docs. Documentation slugs can be obtained from the SearchDocs tool results. Use this after ApolloDocsSearch to read full pages rather than just excerpts. Content will be given in chunks with the totalCount field specifying the total number of chunks. Start with a chunkIndex of 0 and fetch each chunk.
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  • Search the Companies House register by company name or keyword. Returns a paginated list of matching companies with name, number, status, SIC codes, incorporation date, and registered address. Use company_profile for the full record once you have the company number. Re-call with start_index=start_index+items_per_page to fetch the next page.
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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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  • Batch-score multiple npm, PyPI, Cargo, or Go packages for supply chain risk. Takes a list of package names and returns a risk table sorted by commitment score (lowest = highest risk first). Risk flags: - CRITICAL: single publisher + >10M weekly downloads (publish-access concentration risk) - HIGH: new package (<1yr) + high downloads (unproven, rapid adoption = supply chain risk) - WARN: low publisher count + high downloads Perfect for auditing a full package.json, requirements.txt, Cargo.toml, or go.mod — paste your dependency list and get a prioritized risk report. For Go: pass full module paths (e.g., "github.com/gin-gonic/gin", "golang.org/x/net") and set ecosystem="golang". The "maintainers" column shows GitHub contributor count since Go has no centralized publisher concept. Examples: score all deps in a project, compare two similar packages, identify abandonware before it becomes a CVE.
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  • Get top enforced canonical obligations. Returns obligations ranked by enforcement activity for risk prioritization. This is a focused view of canonical obligations filtered to only those with at least one enforcement action. Use this to identify which obligations regulators are actively enforcing. Args: regulation: Filter by regulation code (e.g. 'dora', 'mica', 'aml'). actor_role: Comma-separated actor roles (e.g. 'credit_institution,significant_institution'). entity_type: Filter by entity type code (e.g. 'credit_institution'). compliance_difficulty: Filter by difficulty: 'low', 'medium', 'high', 'critical'. min_enforcement_count: Minimum enforcement actions (default 1 — only enforced obligations). sort: Sort order (default 'enforcement_count_desc'). page: Page number (default 1). per_page: Results per page (default 20, max 100).
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  • List projects in the workspace. Returns project summaries with fields [id, name, workflow_state, client_id] by default. Use the `fields` parameter to request more detail. Projects are grouped into sections: recent, all, active, archived. By default all sections are merged (recent first, then the rest from `all`), deduplicated. Use `only` to restrict to a single section. When `ids` is provided, specific projects are fetched directly. `ids` is mutually exclusive with search, sort_by, sort_order, client_id, and only. A `referenced` block lists unique client_ids seen across the returned projects, so callers can fetch client details in one follow-up call. Args: workspace_id: Workspace slug (required). ids: Fetch specific projects by ID. Mutually exclusive with search, sort_by, sort_order, client_id, only. fields: List of fields to return. Defaults to [id, name, workflow_state, client_id] when omitted. Available fields: id, name, workflow_state, client_id, is_fixed_price, is_private, follower_ids, time_budget, task_counts_by_workflow_state, blocks, time_stats, time_spent_per_user, charges_stats. Note: time_stats, time_spent_per_user, and charges_stats are computed server-side and may be slower to fetch. limit: Maximum number of projects to return (default: 50). search: Free-text search query (filters by project name). sort_by: Sort field — one of: name, client_name, tasks_todo, time_spent, time_remaining. sort_order: Sort direction — asc or desc. client_id: Filter to return only this client's projects. only: Return only projects from this section: recent, all, active, or archived.
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  • Browse published Bible verse collections. Search by keyword, filter by language, sort by popularity. Args: search: Search term to filter by name, description, or publisher name. language: Language code prefix (e.g. "en", "de", "ja", "zh"). ordering: Sort order: -downloads (default), -created, name. limit: Number of results (1-100, default 20). offset: Starting position for pagination.
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  • Search the Sovereign AI Blog for articles matching a natural language query, optionally filtered by tag and sorted by relevance or date. Behaviour matrix: - query='', sort=* -> list newest-first, optionally tag-filtered - query!='', sort=relevance -> TF-IDF ranked, optionally tag-filtered - query!='', sort=date_desc -> TF-IDF filtered (score > 0.001), then sorted by date Pure read-only, deterministic for a given KB snapshot.
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  • Search sub-entities/branches (underenheter) — e.g. local establishments of a parent company. Results under _embedded.underenheter. Filter by overordnetEnhet (parent org number) and/or navn. e.g. {overordnetEnhet:"923609016"} lists Equinor branches.
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  • Fetch a disaster record by ReliefWeb numeric ID including description, affected countries, GLIDE number, profile overview, key content links, and active appeals or response plans. Use after reliefweb_search_disasters to retrieve full details.
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  • Find body sections in a GOV.UK content item matching a pattern. Returns a list of `{anchor, heading, snippet, match}` hits — small per-section snippets centred on the match — so the LLM can decide which full sections to read via govuk_get_section. Use this when answering content-based questions ("what does this guide say about X?", "find the bit about eligibility") rather than navigating by section number. Pattern is regex; if it doesn't compile, falls back to literal substring.
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