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127,466 tools. Last updated 2026-05-05 16:51

"Creating a server to order medicine from Apollo Clinic using prescription uploads" matching MCP tools:

  • Get the EPP/transfer authorization code for a completed domain purchase. Use this when the domain owner wants to transfer their domain to another registrar. The order must be in "complete" status. The auth code is required by the receiving registrar to authorize the transfer. Args: order_id: The order ID of a completed domain purchase. Returns: Dict with order_id, domain, and auth_code.
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  • Retrieve all current settings of the authenticated shop account as a JSON object. Returns the full shop configuration: name, address, legal numbers, receipt options, order requirements, enabled features, delivery methods, webshop colours, and third-party integration settings. Use this to verify invoice prerequisites before creating orders: shopName, adressline1, and companyRegistrationNum must all be set for legally valid invoices. If any are missing, prompt the user to fill them in via account_edit.
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  • Switch between local and remote DanNet servers on the fly. This tool allows you to change the DanNet server endpoint during runtime without restarting the MCP server. Useful for switching between development (local) and production (remote) servers. Args: server: Server to switch to. Options: - "local": Use localhost:3456 (development server) - "remote": Use wordnet.dk (production server) - Custom URL: Any valid URL starting with http:// or https:// Returns: Dict with status information: - status: "success" or "error" - message: Description of the operation - previous_url: The URL that was previously active - current_url: The URL that is now active Example: # Switch to local development server result = switch_dannet_server("local") # Switch to production server result = switch_dannet_server("remote") # Switch to custom server result = switch_dannet_server("https://my-custom-dannet.example.com")
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  • Get the status of a domain purchase order. Polls the backend every 3 seconds (up to 120 seconds) until the order reaches a terminal state (complete or failed). Returns the final order status including nameservers and DNS token if available. Args: order_id: The order ID returned from buy_domain (e.g. "ord_abc123"). Returns: Dict with order status, domain, nameservers, and CF DNS token if complete.
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  • Get pre-built graph template schemas for common use cases. ⭐ USE THIS FIRST when creating a new graph project! Templates show the CORRECT graph schema format with: proper node definitions (description, flat_labels, schema with flat field definitions), relationship configurations (from, to, cardinality, data_schema), and hierarchical entity nesting. Available templates: Social Network (users, posts, follows), Knowledge Graph (topics, articles, authors), Product Catalog (products, categories, suppliers). You can use these templates directly with create_graph_project or modify them for your needs. TIP: Study these templates to understand the correct graph schema format before creating custom schemas.
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  • Repay debt to an Arcadia lending pool using tokens from the wallet (requires ERC20 allowance). To repay using account collateral instead (no wallet tokens needed), use write_account_deleverage. Check allowance first (read_wallet_allowances), then approve the pool if needed (write_wallet_approve). Check outstanding debt with read_account_info.
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Matching MCP Servers

Matching MCP Connectors

  • Add a document to a deal's data room. Creates the deal if needed. This is the primary way to get documents into Sieve for screening. Upload a pitch deck, financials, or any document -- then call sieve_screen to analyze everything in the data room. Provide company_name to create a new deal (or find existing), or deal_id to add to an existing deal. Provide exactly one content source: file_path (local file), text (raw text/markdown), or url (fetch from URL). Args: title: Document title (e.g. "Pitch Deck Q1 2026"). company_name: Company name -- creates deal if new, finds existing if not. deal_id: Add to an existing deal (from sieve_deals or previous sieve_dataroom_add). website_url: Company website URL (used when creating a new deal). document_type: Type: 'pitch_deck', 'financials', 'legal', or 'other'. file_path: Path to a local file (PDF, DOCX, XLSX). The tool reads and uploads it. text: Raw text or markdown content (alternative to file). url: URL to fetch document from (alternative to file).
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  • Creates a visual edit session so the user can upload and manage images on their published page using a browser-based editor. Returns an edit URL to share with the user. When creating pages with images, use data-wpe-slot placeholder images instead of base64 — then create an edit session so the user can upload real images.
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  • ⚠️ MANDATORY FIRST STEP - Call this tool BEFORE using any other Canvs tools! Returns comprehensive instructions for creating whiteboards: tool selection strategy, iterative workflow, and examples. Following these instructions ensures correct diagrams.
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  • Returns VoiceFlip MCP server health and version metadata. No authentication required. Use this first to verify the server is reachable from your MCP client.
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  • Remove the registrar transfer lock from a completed domain purchase. Domains are locked by default to prevent unauthorized transfers. Call this before initiating a transfer to another registrar. The order must be in "complete" status. Args: order_id: The order ID of a completed domain purchase. Returns: Dict with order_id, domain, and unlocked status.
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  • Restore an authenticated session using a previously saved JWT token. Call this at the start of a new session before any other tools, using a token saved from a prior check_login call. If the token is invalid, fall back to login.
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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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  • Run a read-only SQL query against the database. Call list_tables() and describe_table() first to see available tables and columns. SELECT only, 5s timeout, 1000 row limit, JSON results. Examples: query("SELECT full_name, stars FROM ai_repos ORDER BY stars DESC LIMIT 10") query("SELECT domain, COUNT(*) FROM ai_repos GROUP BY domain ORDER BY 2 DESC")
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  • [DETAIL TOOL] Search appointment slots/cards. Use directly when clinic is known, or after search_available_clinics_map selection. Params: city (required), medical_service, doctor, clinic, start_day (YYYY-MM-DD). If no results with doctor/clinic filters, automatically retries without them. Returns slots with booking_url for checkout (supports pre-filled params: &name=&last_name=&email=&phone=&tax_code=).
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  • Get the current authenticated user's profile and account settings. Requires a valid signature session from `tronsave_login` and `mcp-session-id` in request headers. Wallet signing always happens client-side; never send private keys to the server.
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  • Run a read-only SQL query in the project and return the result. Prefer this tool over `execute_sql` if possible. This tool is restricted to only `SELECT` statements. `INSERT`, `UPDATE`, and `DELETE` statements and stored procedures aren't allowed. If the query doesn't include a `SELECT` statement, an error is returned. For information on creating queries, see the [GoogleSQL documentation](https://cloud.google.com/bigquery/docs/reference/standard-sql/query-syntax). Example Queries: -- Count the number of penguins in each island. SELECT island, COUNT(*) AS population FROM bigquery-public-data.ml_datasets.penguins GROUP BY island -- Evaluate a bigquery ML Model. SELECT * FROM ML.EVALUATE(MODEL `my_dataset.my_model`) -- Evaluate BigQuery ML model on custom data SELECT * FROM ML.EVALUATE(MODEL `my_dataset.my_model`, (SELECT * FROM `my_dataset.my_table`)) -- Predict using BigQuery ML model: SELECT * FROM ML.PREDICT(MODEL `my_dataset.my_model`, (SELECT * FROM `my_dataset.my_table`)) -- Forecast data using AI.FORECAST SELECT * FROM AI.FORECAST(TABLE `project.dataset.my_table`, data_col => 'num_trips', timestamp_col => 'date', id_cols => ['usertype'], horizon => 30) Queries executed using the `execute_sql_readonly` tool will have the job label `goog-mcp-server: true` automatically set. Queries are charged to the project specified in the `project_id` field.
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  • Record a new order in the connected shop. Input includes paymentMode, and items[]. Each item can be of type 'catalog' (with productId), 'department' (with price and deptId) or 'free' (with title and price). Check if the client already exists using data_list_clients and if the client exists, only specify idClient. If provided, paymentMode should correspond to a payment ID from data_list_payments_modes tool. Returns a sale confirmation JSON including: a link to the PDF invoice, and a link to a private order page showing full order details which can also be used by the client to pay online. IMPORTANT: before creating a validated invoice (payment ≠ -2), call account_show_infos to verify that shopName, adressline1, and companyRegistrationNum are all set. If any of these fields are empty, warn the user and suggest using account_edit to fill them in before issuing invoices.
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  • Connectivity check — returns server version and current timestamp. Use to verify MCP server is reachable before calling other tools.
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