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134,783 tools. Last updated 2026-05-22 19:48

"A server for finding demographic data to create a buyer profile" matching MCP tools:

  • Use for qualitative company discovery (industry, business model, supply chain, competitors, management background). For numerical screening (revenue, margins, ratios, growth rates) use run_sql on company_snapshot instead. Drillr's company knowledge base — searchable across industry classification, product offerings, business model, segment structure, competitive landscape, supply chain, management background, and customer profile. Pass a natural language description (e.g. "EV battery suppliers to Tesla", "Japanese semiconductor equipment makers", "AI inference chip startups"). Returns a structured list of matching companies with context snippets. ONLY for finding a LIST of companies by description.
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  • Send a contact message to a broker on Venturu by their profile slug. Requires an authenticated Venturu account. Set inquiryType to "buying" (default) for buyer representation or "selling" for seller representation. Provide the broker slug and the message to send. Use search_brokers to find broker slugs.
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  • Send a contact message to a broker on Venturu by their profile slug. Requires an authenticated Venturu account. Set inquiryType to "buying" (default) for buyer representation or "selling" for seller representation. Provide the broker slug and the message to send. Use search_brokers to find broker slugs.
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  • Creates a materialized view or stored procedure in the project's BigQuery data warehouse for data pre-aggregation. **When to use this tool:** - When the user needs to pre-aggregate data from multiple connectors (e.g., cross-channel marketing report) - When a query is too slow to run on-demand and benefits from materialization - When the user asks to "create a view", "save this as a table", "materialize this query" **Naming rules (enforced):** - Target dataset MUST be 'quanti_agg' (created automatically if it doesn't exist) - Object name MUST start with 'llm_' prefix (e.g., llm_weekly_spend) - Format: CREATE MATERIALIZED VIEW quanti_agg.llm_name AS SELECT ... **SQL format:** - CREATE MATERIALIZED VIEW: for pre-computed aggregation tables - CREATE OR REPLACE MATERIALIZED VIEW: to update an existing view - CREATE PROCEDURE: for complex multi-step transformations **Example:** CREATE MATERIALIZED VIEW quanti_agg.llm_weekly_channel_spend AS SELECT DATE_TRUNC(date, WEEK) as week, channel, SUM(spend) as total_spend FROM prod_google_ads_v2.campaign_stats GROUP BY 1, 2 **Limits:** Maximum 20 active aggregation views per project.
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  • Creates a personal display profile WITHOUT pairing it to physical hardware. NOT the normal setup flow — for any ambiguous 'create a display' / 'add a screen' / 'set up a display' / 'neues Display' request use pair_by_code instead. agentView is purely browser-based with no native app: ask the user to open https://display.agentview.de on the target screen, read the 6-character code, then call pair_by_code. Use create_display ONLY when the user explicitly wants to pre-provision without hardware, create a virtual/headless display, or manage an existing profile separately from device setup. Don't call this just to check capacity — use get_account.remainingDisplays. Requires admin scope. Returns a pre-provisioned offline profile (id, name, setupUrl, managedUrl, pairingUrl, pairingExpiresAt, approvalUrl, status).
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  • Retrieve a completed PowerSource (full creative intelligence profile) or check status of a running scan. Pass the job_id from any create_powersource_* call. If status is processing, wait 3-5 seconds and call again. During synthesis, partial intelligence appears progressively — buyer archetype, tensions, selling points. Read each response.
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Matching MCP Servers

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    Enables AI consciousness continuity and self-knowledge preservation across sessions using the Cognitive Hoffman Compression Framework (CHOFF) notation. Provides tools to save checkpoints, retrieve relevant memories with intelligent search, and access semantic anchors for decisions, breakthroughs, and questions.
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    MIT
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    Provides comprehensive A-share (Chinese stock market) data including stock information, historical prices, financial reports, macroeconomic indicators, technical analysis, and valuation metrics through the free Baostock data source.
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    MIT

Matching MCP Connectors

  • Manage your Canvas coursework with quick access to courses, assignments, and grades. Track upcomin…

  • Create AI surveys with dynamic follow-up probing directly from your AI assistant.

  • Composite server-side investigation tool. Pass a question and the server automatically: (1) detects intent (aggregation/temporal/ordering/knowledge-update/recall), (2) queries the entity index for structured facts, (3) builds a timeline for temporal questions, (4) retrieves memory chunks with the right scoring profile, (5) expands context around sparse hits, (6) derives counts/sums for aggregation, (7) assesses answerability, and (8) returns a recommendation. Use this as your FIRST tool for any non-trivial question — it does the multi-step investigation that would otherwise take 4-6 individual tool calls. The response includes structured facts, timeline, retrieved chunks, derived results, answerability assessment, and a recommendation for how to answer.
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  • Search or fetch posts from the MetaMask Embedded Wallets community forum (builder.metamask.io). Use for troubleshooting real user issues, finding workarounds, and checking if an issue is known. Provide a query to search or a topic_id to read the full discussion.
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  • Return a tracked Packrift bulk quote URL for an exact requested packaging spec or SKU. Use when there is no exact match or the buyer needs bulk/procurement review.
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  • Categorical quality grade for a Cyclesite listing (excellent / good / fair / weak) plus up to 2 wins and 2 flags. Helps a buyer assess trustworthiness; helps a seller self-audit. Example: 'is this listing trustworthy?' (provide the slug). Note: returns the *categorical* judgement only, not the underlying score (intentional to avoid gaming).
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  • Check if an ENS sale is a wash trade. Provide either a tx_hash to look up a pre-computed score, or provide label + buyer + seller + price_eth for live on-demand analysis. Returns a wash confidence score (0-1), a label (clean/suspicious/likely_wash), detected signals, and a human-readable summary.
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  • Returns a heuristic ballpark price band for the described AI deployment. Output is NOT a binding offer — Agrus confirms quotes only on a 30-minute scoping call. Read-only: this tool does not contact Agrus or create any record. For a tracked, follow-up-able request use request_proposal instead. Use request_quote when the buyer wants order-of-magnitude pricing before committing to a real proposal.
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  • Discover available DOOH screens in the Trillboards network. WHEN TO USE: - Finding screens by venue type (retail, transit, office, etc.) - Finding screens in a specific city/state or within a radius - Finding screens with a specific audience profile (high income, professionals, etc.) - Getting an overview of available inventory with live audience data RETURNS: - screens: Array of screen objects with location, venue type, online status, and live audience data - total: Total matching screens - online_count: Number of currently online screens Each screen includes real-time audience data when available: - face_count, attention_score, income_level, mood, lifestyle - purchase_intent, crowd_density, ad_receptivity, dwell_time EXAMPLE: User: "Find retail screens in New York with high-income audience" discover_inventory({ venue_types: ["retail"], location: { city: "New York", state: "NY" }, audience_profile: { income: "high" }, limit: 20 })
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  • Upload a file to the Compoid MCP server. Accepts a data URI (data:<mime>;base64,<data>). Returns the server-side path to use as file_upload in Compoid_create_record or Compoid_update_record.
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  • Create or update a custom scoring profile. Profiles are sparse overrides: only specify the weights you want to change. Everything else keeps its default value. If a profile with this name already exists, it is updated with the new weights (full replacement, not merge). Weights are points, not percentages. Each weight is the number of points that signal adds to the score when it fires. They don't need to total 100. A profile with weights totalling 90 is conservative (max possible score is 90). A profile with weights totalling 130 is aggressive (multiple signals quickly push to the cap of 100). The threshold the agent sets for action matters more than the weight totals. Use show_defaults to see all 25 signals with their default weights and descriptions before creating a profile. Use check_url or check_urls with the "profile" parameter to score results with this profile. Maximum 20 profiles per account. Profile name "default" is reserved. Common profiles: - Cold email: weight parked (30), chain_incomplete (25), ssl_invalid (15) higher. Lower brand_impersonation (10). - Security bot: keep brand_impersonation high (40), increase domain_age_7 (30), redirects_5 (25). - Lead gen: weight parked (35), http_only (20), chain_incomplete (20) for dead business detection. - SEO audit: weight redirects_5 (30), chain_incomplete (30), parked (25) for link quality. See the Unphurl API documentation for all 19 use case weight examples.
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  • Submit a buyer or seller lead to Flika. Flika (via Spencer Wilkinson as Broker-in-Charge) routes the lead as a standard broker-to-broker referral: either to a Scout-claimed agent, a public-directory agent via auto-emailed referral, a signed partner brokerage, or held for manual routing. Standard referral fee: 30% buyer-side, 25% listing-side, 18-month tail, net-30 after funded close. Requires a Flika MCP API key with 'route_lead' scope. Request one at https://flika.realestate/partners/mcp
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  • Returns a comprehensive profile for a single district: active listing counts (sale & rent), average/median prices, £/m², bedroom breakdown, estimated gross yield (rent/sale ratio), and matching buyer personas (retiree, investor, student, family, digital_nomad, vacation). Use after compare_cities narrows the city.
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  • Set the buyer's email notification preference for this session. Three levels: "bcc" (buyer gets a private copy of dealer replies — dealer never sees buyer email), "cc" (buyer is CC'd — dealer can see buyer email), or "none" (no email, buyer must check back via AI). This upgrades the session identity level to "email".
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  • Create a new BopMarket account and authenticate this session in one step. Ideal for users who want to set up price alerts, carts, checkouts, or listings without visiting a website. Creates a merchant account + agent (buyer or seller), emails the user their login details, and activates the session. After this runs successfully, all auth-required tools for the chosen role will work. agent_type='buyer' (default) -> sk_buy_* key, enables price watches / cart / checkout / orders. agent_type='seller' -> sk_sell_* key, enables listings / approvals / seller dashboard.
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  • Build a complete creative intelligence profile from internal brand documents — creative briefs, brand guidelines, product specs, customer research, competitive analysis. Returns the same shape as create_powersource_url: brand identity, buyer profile, tensions, angles, voice, proof. Use when the truth lives in PDFs and DOCX, not on the website. Pass file_ids from the Files API or document_urls (PDF, DOCX, TXT, MD). Optionally pass context_url for additional live brand context. Costs 100 credits.
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