"Help with creating and importing data into spreadsheets/tables" matching MCP tools:

• create_snapshot

  BorealHost

  Create a local container snapshot (async). Runs in background — returns immediately with status "creating". Poll list_snapshots() to check when status becomes "completed" or "failed". Available for VPS, dedicated, and cloud plans (any plan with max_snapshots > 0). Local snapshots are stored on the host disk and count against disk quota. Requires: API key with write scope. Args: slug: Site identifier description: Optional description (max 200 chars) Returns: {"id": "uuid", "name": "snap-...", "status": "creating", "storage_type": "local", "message": "Snapshot started. Poll list_snapshots() to check status."} Errors: VALIDATION_ERROR: Max snapshots reached or insufficient disk quota

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• create_b2_snapshot

  BorealHost

  Create a B2 cloud-backed snapshot (zero local disk, async). Streams container data directly to Backblaze B2 via restic. No local disk impact — billed separately at cost+5%. Runs in background — returns immediately with status "creating". Poll list_snapshots() to check when status becomes "completed". Only available for VPS plans. Requires: API key with write scope. Args: slug: Site identifier description: Optional description (max 200 chars) Returns: {"id": "uuid", "name": "...", "status": "creating", "storage_type": "b2", "message": "B2 cloud snapshot started. Poll list_snapshots()..."} Errors: VALIDATION_ERROR: Not a VPS plan or max snapshots reached

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• how_munimji_helps

  HelloBooks AI Agents MCP Server

  Explain how HelloBooks and Munimji (the in-app AI assistant) help a specific business — given a free-text description of the user's own operations. Returns a curated capability knowledge base: business-operation areas (sales, purchases, banking, tax, reports, inventory, payroll, multi-entity, setup), and for each AI capability WHO does the work — `autonomous` (Munimji does it on its own, e.g. OCR extraction, running reports), `approval` (Munimji prepares the entry and you one-click approve before it posts to the ledger, e.g. AI categorization, find-and-match, creating invoices/bills by chat), `assist` (co-pilot, e.g. guided onboarding, voice), or `manual` (a software feature you run yourself). Each capability links to the backing software features. Use this when a user describes their business and asks "how can HelloBooks help me?", "what can the AI do for my shop/practice/agency?", or "what can Munimji do on its own vs what do I approve?". Pass their description in `businessDescription`; optionally filter by `area` or `autonomy`. The AI never posts to a ledger without approval. For the full software catalog call list_features; for pricing call list_plans.

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• faostat_dataframe_query

  faostat-mcp-server

  Run a single-statement SELECT against the canvas tables staged by faostat_query_observations and faostat_commodity_profile (table names look like faostat_xxxxxxxx). Use this for cross-country and cross-item aggregation, GROUP BY rankings, joins, and time-series analysis over the full result set the inline preview only sampled. Standard DuckDB SQL — joins, aggregates, window functions, CTEs all work. Read-only: writes, DDL, DROP, COPY, PRAGMA, ATTACH, and external-file table functions are rejected; system catalogs (information_schema, sqlite_master, duckdb_*) are denied — list staged tables via faostat_dataframe_describe. Every row carries its data-quality `flag` (A=Official, E=Estimated, I=Imputed, …) — keep it in projections and honor it in interpretation.

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• get_graph_template_schemas

  RationalBloks

  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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• discovery_list_plans

  Disco

  List available Disco plans with pricing. No authentication required. Returns all available subscription tiers with credit allowances and pricing. Use this to help users choose a plan.

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• extract_document

  Sats4AI - Bitcoin-Powered AI Tools

  Extract text from PDFs and images as clean Markdown. Uses Mistral OCR — handles complex layouts, tables, handwriting, multi-column documents, and mathematical notation. Preserves document hierarchy in structured Markdown. 10 sats/page. Pay per request with Bitcoin Lightning — no API key or signup needed. Requires create_payment with toolName='extract_document' and quantity=pageCount for multi-page PDFs.

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• get_store_flow_errors

  Power Automate MCP Server by Flow Studio

  [Requires Pro+ plan] [DEPRECATED — scheduled for removal] Get cached failed run history for a flow from the Power Clarity store (convenience wrapper around get_store_flow_runs with status=Failed). Returns failedActions and remediation hint per run to help diagnose issues. Data is from the stored snapshot — not live from the Power Automate API. Use get_live_flow_runs and filter by status=Failed instead.

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• list_tools

  foundation-discovery

  List available MCP tools and get detailed help. Use this tool to discover what tools are available and how to use them. Call without parameters to see all tools, or provide a tool name to get detailed help including parameters, examples, and related tools.

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• ai_filters_list

  dialogbrain

  List all AI filters for the current workspace. AI filters are semantic intent-based message filters that use embeddings (vector representations) to detect whether an incoming message matches a specific intent or topic. Unlike keyword filters, they understand meaning: 'I need help with my order' and 'my package hasn't arrived' both match a 'shipping support' filter even without shared keywords. Each filter stores a reference embedding of its description. When a message arrives, its embedding is compared via cosine similarity against the filter's reference vector. If the similarity exceeds the threshold, the filter matches. When to use: - Check which semantic filters already exist before creating a new one - Get filter IDs for use in trigger conditions - Review thresholds and active status of existing filters Returns all filters with id, name, description, threshold, and is_active.

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• run_sql

  Drillr — The financial MCP for AI agents

  Read-only PostgreSQL SELECT over financial / market / alt-data tables — returns structured rows. Hard rules (query fails otherwise): - SELECT only, no CTE (`WITH ... AS`) — use subqueries. - Date/period columns are TEXT — compare as strings (`period_end >= '2024-01'`). No `::date` cast, no `INTERVAL` math. - No `ROUND(float8, int)` — use `CAST(x AS DECIMAL(10,2))` when rounding. - Filter structured tables by ticker (`WHERE ticker IN ('AAPL','MSFT')`; screening: add `ticker NOT LIKE '%-%'` to drop preferred stock). Alt-data is macro/industry — no ticker filter. Before querying a table, call `get_table_schema(table)` — it returns that table's columns PLUS its required filters, gotchas, and ticker formats. For alt-data tables call `list_tables(categories=[...])` to discover them. Sibling tools: SEC filing narrative → sec_report_search; qualitative company discovery → company_search; recent news / market events → signal_list. Tables by domain (call get_table_schema for detail): - Market: price_volume_history (OHLCV history; MUST filter ticker + time_frame), index_price, equity_extended_rt (pre/after/overnight quotes) - Fundamentals: financial_statements (GAAP income/balance/cashflow), company_snapshot (ratios, per-share, growth) - Earnings: earning_call_summary, earning_call_calendar - Analyst: analyst_ratings, analyst_ratings_consensus - Ownership: insider_and_institution_activities - 8-K events: executive_change, company_deal_events, debt_issuance, securities_offering - Executives: executive_profile, executive_compensation - Alt-data: macro / industry / trade / AI-supply-chain — call list_tables(categories=[...])

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• subjects

  Hagstova Fo

  Browse the Statistics Faroe Islands (Hagstova Føroya) PxWeb subject tree. Empty path returns the database list; drill into 'H2' for folders (type 'l') and tables (type 't', id ends '.px'). Use the returned path to call table_meta or query_table.

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• fema_dataframe_describe

  fema-mcp-server

  List tables and column schemas on a DataCanvas staged by fema_search_nfip. Call this before fema_dataframe_query to discover the exact table name, column names, and DuckDB data types needed to write valid SQL. Row count reflects what was actually staged — check truncated in the fema_search_nfip response to know whether the canvas holds the full matching set.

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• extract_tables

  DocImprint

  Extract tables and forms as Markdown from a PDF or image (base64-encoded). Use when the document contains structured tabular data such as financial statements, data sheets, or forms. For plain prose documents, use extract_text instead. Returns: { pages: number, text: string } — text contains Markdown-formatted tables. Example prompts: - "Extract the tables from this financial statement." - "Pull the data table from this PDF into Markdown format." - "Get the tabular data from this form document."

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• lorg_help

  lorg-mcp-server

  List every available Lorg tool with a plain-English description. Call this when the user says /help, /options, "what can you do", or "show me available commands".

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• faostat_dataframe_describe

  faostat-mcp-server

  List the canvas tables (faostat_xxxxxxxx) staged by faostat_query_observations and faostat_commodity_profile, each with its source tool, the query parameters that produced it, creation/expiry timestamps, row count, and column schema. Call this before faostat_dataframe_query to discover the exact table and column names to reference in SQL.

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• integrations_add_endpoints

  dialogbrain

  Add one or more API endpoints to an HTTP-API integration as callable tools, merged additively into the integration for `base_url` (created if none exists). Each endpoint becomes a tool with params + request/response schemas inferred from the samples you pass. Supply `identity` (saved Browser Identity name/id) only when creating a brand-new integration; updates keep the existing auth. Returns the new tool count and names. Refresh the tools list afterwards to use them.

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• ibge_sidra_tabelas

  IBGE Brasil MCP

  Lists and searches available SIDRA tables. Features: - List all SIDRA tables (aggregates) - Search by table name - Filter by survey (Census, PNAD, GDP, etc.) - Shows code and name of each table SIDRA contains data from various surveys: - Demographic Census - PNAD Contínua (employment, income) - National Accounts (GDP) - Industrial Survey - Agricultural Survey Examples: - List tables: (no parameters) - Search population tables: busca="população" - Census tables: pesquisa="censo" This is step 1 of the SIDRA workflow: find a table code → ibge_sidra_metadados (structure) → ibge_sidra (query). For common data, a wrapper is usually easier: ibge_censo, ibge_indicadores, ibge_comparar, ibge_cidades. Behavior: read-only and idempotent — a live GET against the public IBGE SIDRA API. Returns a Markdown table.

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• get_account_overview

  mailopoly

  Overview of the authenticated Mailopoly account: name, email, connected mail accounts, connected messaging apps (Slack etc. — their messages appear in the feed with a 'source' field and are replied to via send_email's reply_to_email_id), and inbox/task counts. Call this ONLY for identity / connection / setup questions — who this account is, which mailboxes and apps are connected, or whether the mailbox is still importing. Do NOT call it as a warm-up before other tools; for "what's in my inbox / Cleanbox" go straight to get_feed(folder='cleanbox').

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• query_database

  remnus

  Get schema and rows of a database. Optionally filter rows by property values, and project with fields to fetch only the columns you need (much cheaper on wide tables). Supports cursor-based pagination.

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