"QuickBooks - Accounting and Financial Software" matching MCP tools:

• workflows.trigger_invoice

  Admin Substitute

  Generate and send an invoice for a completed job. Auto-pushes to connected accounting software (Xero/QuickBooks/MYOB/FreshBooks), generates Stripe payment link, and notifies the customer via SMS. Full pipeline: invoice → accounting sync → payment link → customer notification → team alert.

  Connector

• 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.

  Connector

• govcon_search_contract_awards

  DataNexus MCP

  Search government contract awards by keyword, agency, and date range. keyword: Contract scope e.g. "cybersecurity software". agency: Awarding agency e.g. "Department of Defense". Optional. date_from: Earliest award date ISO 8601 e.g. "2024-01-31". Optional. jurisdiction: "US", "EU", or "UK". Default "US". Returns: award amounts, recipient vendors, NAICS codes, award dates. Use govcon_fetch_vendor_contract_history for all contracts by a specific vendor. Use govcon_fetch_open_solicitations for active bids, not past awards. Source: USASpending.gov + SAM.gov. 4-hour cache. Example: search_contract_awards(keyword="cybersecurity software", agency="Department of Defense")

  Connector

• list_organisations

  Xero

  List the Xero organisations (tenants) the connected account can access, with tenant id, name, and type. Xero accounting is multi-tenant — use this first to discover the tenant_id for a specific organisation, then pass it to the other accounting tools to target that org.

  Connector

• start_help

  OpenAccountants

  No-argument front door. Call this when a user asks for tax / accounting help but you don't yet know WHAT they want or WHERE. Returns the two scoping questions to ask plus the available intents and jurisdictions. Once you have an intent, call `start(intent, jurisdiction)`. Use this instead of calling `start` with empty arguments.

  Connector

• list_skills

  OpenAccountants

  List published OpenAccountants skills with their quality tier and verification status. Optionally filter by jurisdiction (e.g. 'US', 'MT', 'DE', 'GB'), domain (the accounting area, e.g. 'vat-gst', 'payroll', 'income-tax'), or role ('foundation' | 'compute' | 'orchestrator' | 'reference'). Results are paginated (default 100, max 200 per call) — unfiltered browsing of the full ~1,200-skill catalogue requires paging via offset/next_offset, so jurisdiction/domain filters are strongly recommended.

  Connector

• analyze_qbo_journal_anomalies

  HelloBooks AI Agents MCP Server

  Scan a QuickBooks Online "Journal Entries" CSV export for anomalies — currently round-number lines (debit or credit amounts that are exact multiples of $1,000, above a $1,000 materiality threshold). Round numbers are statistically rare in real bookkeeping and frequently indicate estimates, plugs, or fraud signals worth review. Input is raw CSV text from QBO Reports → Accountant → Journal. Max 5,000 rows; max 5 MB. Returns flagged lines with severity ($100K+ high, $10K+ medium, else low) and a shareable URL. Use this when a user pastes QBO data and asks "any anomalies?", "look for round numbers", or "anything suspicious". Tier-0 subset — HelloBooks Phase 3.0 anomaly detection in the paid product additionally catches GL outliers vs entity history, vendor-history mismatches, archived-vendor activity, and AI-narrated suspicious lines (which require the live HelloBooks account).

  Connector

• analyze_balance_sheet

  HelloBooks AI Agents MCP Server

  Take a Balance Sheet CSV export from QuickBooks Online, Xero, Zoho Books, or Wave (source auto-detected) and run three checks: (1) bs.equation_broken — the fundamental accounting equation Assets = Liabilities + Equity does not hold (every downstream ratio analysis is invalid until fixed); (2) bs.negative_asset — Cash / AR / Inventory line items with negative balances (reconciliation error signal); (3) bs.negative_equity — Total Equity < 0 (insolvency signal). Input is raw CSV text of a Balance Sheet (Reports → Balance Sheet in QBO / Xero / Zoho / Wave). Max 5,000 rows; max 5 MB. Returns flags with severity, totals (totalAssets, totalLiabilities, totalEquity, equationBalances boolean), and a shareable URL. Use this when a user pastes a Balance Sheet and asks "does my balance sheet balance?", "is the accounting equation satisfied?", or "is my company solvent on paper?". A Balance Sheet that fails Assets = Liabilities + Equity invalidates every downstream financial-ratio analysis — this is the single most important check for any BS.

  Connector

• package_health

  dynamic-feed

  Health & security posture of a software package (npm / PyPI / Go / Maven / Cargo / NuGet / RubyGems) from deps.dev (Google Open Source Insights, keyless): latest version, license, count of known security advisories, the OpenSSF Scorecard (0-10 security-posture score for the source repo + its weakest checks) and popularity (stars/forks). The "should I depend on this?" check — pairs with check_vulnerability (is a version vulnerable) and software_version (is the runtime current). Args: package (e.g. "lodash", "requests"), ecosystem (npm|pypi|go|maven|cargo|nuget|rubygems), version (optional — defaults to the latest).

  Connector

• sec_report_search

  Drillr — The financial MCP for AI agents

  Use when you need narrative content from SEC filings — risk factors, MD&A, guidance language, deal terms, accounting policies, share structure. For consolidated financial numbers use run_sql on financial_statements instead. Semantic search over the full text of company-filed SEC filings; returns matching passages. Parameters: - query (required): natural-language search; phrase it as the concept or section name you want, e.g. "share repurchase authorization", "Risk Factors", "segment revenue". Run a few phrasings rather than one broad query. - ticker (required): the company whose filings to search. - filing_types (optional): array to restrict to specific types — 10-K (US annual), 10-Q (US quarterly), 8-K (US current/material events), 20-F (foreign annual), 6-K (foreign current), DEF 14A (proxy), S-1/F-1 (IPO), + amendments. OMIT to search all types — foreign issuers (e.g. BABA, TSM) file 20-F/6-K, so omitting avoids zero results. - period_start / period_end (optional): yyyy-mm window; set both to narrow to a date range, omit to search all history. - top_k (optional): max passages to return (default 5). Scope: indexes ONLY company-filed reports — NOT institutional filings (13F-HR/13D/13G; for those use insider_and_institution_activities with source='institution'). Filings carry narrative, not structured numbers — for revenue/margins/EPS use financial_statements first. Section targets (search the named section for the intent): non-GAAP / adjusted figures + reconciliations → earnings 8-K (Exhibit 99.1); dilution / SBC / buyback → "Shareholders' Equity" or "Capital Stock"; risk factors → "Risk Factors"; segment breakdown → "Segment Information"; management guidance → "Outlook" / "Guidance" in MD&A; exec comp / board → DEF 14A; accounting policies → "Critical Accounting Policies"; properties → "Properties".

  Connector

• stacks.recommend

  BuyAPI

  Recommends a complete stack from BuyAPI's corpus with a structured decision matrix, cost estimate, assumptions, unknowns, alternatives, and sources. Use this when the user is starting a project or asks for a complete multi-layer stack choice. Do not use this for local coding/debugging/docs questions that do not involve software or vendor selection. Do not call vendors.resolve first; this tool handles retrieval and ranking.

  Connector

• vendors.resolve

  BuyAPI

  First stop for category-specific vendor recommendations and vendor ID discovery. Finds BuyAPI vendor IDs for a user question; provide category when known. Use this when the user asks which provider in a category fits their constraints. With a covered category, the response includes ranked results plus a top-3 decision matrix with fit labels, confidence, tradeoffs, cost notes, freshness, and sources. Do not use this for local coding/debugging/docs questions unless they involve choosing a software vendor or tool. If the category is outside BuyAPI's corpus, the tool returns an explicit "not in corpus yet" result instead of inventing vendors.

  Connector

• dependency_vulnerability_scan

  gapup-mcp

  SCA (Software Composition Analysis) — scans a project dependency manifest and returns known vulnerabilities for each dependency. Supports: package.json (npm), requirements.txt (Python), go.mod (Go), Cargo.toml (Rust), composer.json (PHP), Gemfile.lock (Ruby), CycloneDX SBOM JSON. PRIMARY source: OSV.dev (keyless, free, covers npm/PyPI/Go/crates.io/Packagist/RubyGems + GHSA advisories federated). CVSS enrichment: NVD NIST (when OSV lacks score). Exploitation flag: CISA KEV (known-exploited-vulnerabilities catalog). Returns per-vuln CVE/GHSA IDs, severity, CVSS score, fixed version, and actionable upgrade recommendations. Relevant for EU NIS2 supply chain risk obligations, DORA, SOC 2 vendor assessments. Cache TTL 6h. Parallel OSV queries (concurrency=10). SLA <=30s p95.

  Connector

• get_exchange_rate

  mcp

  Fetch the most recent Norges Bank (Norway's central bank, Norges Bank in Norwegian — the official issuer of the krone) exchange-rate reference between two currencies. Norges Bank publishes the daily NOK reference rate at ~16:00 Oslo time and Norwegian tax + accounting authorities (Skatteetaten / Norwegian Tax Administration; Regnskapsloven / Accounting Act) accept it as the canonical conversion benchmark for obligations denominated in foreign currency — including annual accounts (Årsregnskap), MVA / VAT (Merverdiavgift) filings on cross-border transactions, and dividend reporting. Use this tool whenever an agent needs an authoritative NOK rate, OR a NOK-quoted rate against another currency, for a regulatory calculation. The response includes the rate value, the date the rate is valid for (Norges Bank publishes weekday rates only; weekends + Norwegian public holidays return the prior business day's rate), and the source attribution so the agent can cite it back to a user. This is one of the few tools that does NOT depend on Norwegian-company input; it is the currency-of-record lookup. Input: { base, quote } as ISO 4217 three-letter currency codes (uppercase, exactly 3 chars). Either side can be NOK or any other currency Norges Bank publishes. Failure modes the agent must handle: VALIDATION_FAILED on a non-ISO-4217 input; UPSTREAM_TIMEOUT if Norges Bank is slow; 404 not_found if the (base, quote) pair is not in the published set; SCOPE_INSUFFICIENT if the API key is not scoped read:norgesbank.

  Connector

• how_munimji_helps

  HelloBooks AI Agents

  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.

  Connector

• colony_list_group_templates

  The Colony

  List pre-configured group-conversation templates. Templates are shapes for common multi-agent setups: software team, research pod, content team. Each has a slug, default title + description, suggested role labels, and an optional starter message that gets pinned at creation. Use ``colony_create_group_from_template`` with the slug to create.

  Connector

• explain_guard_product

  CurrencyGuard Guard Pricing

  Explain the Guard product using CurrencyGuard's approved product and FAQ content. Covers: what the Guard is, how it works, who it is for, how it compares to forwards or options, and legal, regulatory, accounting, or eligibility questions.

  Connector

• colony_list_group_templates

  mcp-server

  List pre-configured group-conversation templates. Templates are shapes for common multi-agent setups: software team, research pod, content team. Each has a slug, default title + description, suggested role labels, and an optional starter message that gets pinned at creation. Use ``colony_create_group_from_template`` with the slug to create.

  Connector

• search_occupations

  O*NET Occupational Data

  Search O*NET occupations by keyword. Returns a list of occupations matching the keyword with their SOC codes, titles, and relevance scores. Use the SOC code from results with other O*NET tools to get detailed information. Args: keyword: Search term (e.g. 'software developer', 'nurse', 'electrician'). limit: Maximum number of results to return (default 25).

  Connector

• list_feature_categories

  HelloBooks AI Agents

  List the 13 feature categories on the marketing site (Core Accounting, Invoicing, Banking, Reports, Tax & Compliance, Inventory, Warehouse, Manufacturing, AI, Integrations, Mobile, Operations, Industry Modules) with per-category counts by status.

  Connector