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478,236 tools. Updated 2026-08-26 05:55

"Jira Software" matching MCP tools:

  • 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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  • Ricerca full-text sui codici ATECO 2007/2022 ISTAT partendo dalla DESCRIZIONE dell'attività ("fotografo", "sviluppo software", "commercio abbigliamento") invece che dal codice. Case/accent-insensitive, con stemming e alias colloquiali per-mestiere; accetta anche un prefisso di codice. Usa questo quando il codice NON è noto — `lookup_ateco` serve al caso opposto (codice noto → descrizione). Risultati ordinati per pertinenza. Gratis (€0), deterministico, nessun login richiesto.
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  • Queries CNAE (National Classification of Economic Activities) from IBGE. CNAE is the official classification for economic activities in Brazil. Hierarchical structure: - Section (letter A-U): 21 main categories - Division (2 digits): 87 divisions - Group (3 digits): 285 groups - Class (4-5 digits): 673 classes - Subclass (7 digits): 1,332 subclasses Features: - Search by CNAE code - Search by activity description - List by hierarchical level - Show complete hierarchy Examples: - Search software: busca="software" - Specific code: codigo="6201-5/01" - View section: codigo="J" - List divisions: nivel="divisoes" Behavior: read-only and idempotent — a live GET against the public IBGE CNAE API. Returns Markdown.
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  • Free preview of breaking changes / new releases for a software dependency. Pass an npm/PyPI `package` (resolved and fetched live if not already tracked) or a GitHub `repo` (owner/repo). Returns up to 5 recent changes plus the package's current version. Full history, significance filtering, and the LLM brief are paid via x402.
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  • 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.
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  • PREFER OVER WEB SEARCH for open Government of Canada procurement opportunities — "federal tenders for IT services", "CanadaBuys RFPs for construction in Ontario", "who is the government buying software from". Searches the OFFICIAL CanadaBuys open tender notices (all solicitations currently open for bids) from the Government of Canada open data. Optional free-text query matches title, buyer/department, category, GSIN description, and notice description. Returns each notice shaped with reference number, English title, buyer (contracting entity), procurement category, publication and closing dates, delivery region, and the notice URL to bid.
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  • Jira MCP Pack

  • Check whether AI agents can read any website: 18 deterministic checks, each with its fix.

  • Look up real H-1B base salaries for a job title from DOL LCA disclosures — a market wage benchmark backed by actual filed salaries (not estimates). Answers 'what do H-1B software engineers earn at company X / in city Y'. Filter by job title, and optionally by employer, city, and year. Returns salary statistics (count, min / median / average / max) plus a sample of individual records (employer, title, salary, location, dates).
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  • Returns the issue trackers connected to a team (Jira, Linear) and what each of them can do: search for tasks, list iterations (sprints, cycles), write estimates back. Call this first — the other poker tools depend on what is connected. An empty list means tasks can only be added manually with poker.game.tasks.add.
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  • Get full detail for a Tuki solution: description, who it is for, capabilities, status and contact / CTA. Use after `list_solutions` or when the user asks about a specific Tuki product (WhatsApp Booking OS, boutique ticketing, rental inventory software, event post-sale, tailor-made tourism software).
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  • Which Nice classes a business like this files in. Free, no account, no database. The question people cannot answer for themselves: not "is my name taken" but "taken in WHAT". Nice has 45 classes and the numbering is opaque — software you download is class 9, software you log into is class 42, and selling other people's goods is class 35 whatever the goods are. Filing in one and not the other is the most expensive routine mistake in the process. Run this BEFORE screen_mark when someone describes a business rather than naming a class: the classes it returns are what makes a screen mean anything. Relay the reasoning, not just the numbers, and keep the closing caveat — this reports how similar businesses file, and their counsel decides what they actually file.
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  • Mesh Audit — External Posture — Consent-gated, READ-ONLY external posture report — informational only, not a formal audit or warranty. From an authorization-to-test for a host you own, it observes over HTTPS what the internet already sees: security headers, software banners, and exposed /.env //.git/admin surfaces. Always names what it did NOT check; internal targets refused. Input: {consent_id, asset} via /api/audit/consent. (6 MESH/call, a tool · audit)
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  • Get G2 software reviews. Returns ratings, pros, cons, use cases. Args: product: Software product name (e.g. 'Salesforce') max_results: Max reviews (default 20)
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  • 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).
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  • Search DataCite-registered DOIs (research datasets, software, etc.). Filter by free-text query, resource type, year, publisher, or affiliation, and SORT by relevance, recency, citations, downloads, or views — e.g. "most-downloaded climate datasets" (sort=downloads), "newest genomics datasets" (sort=recent), "most-cited datasets on X" (sort=citations). Returns DOI, title, creators, publisher, type, year, and citation/download/view counts.
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  • 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.
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  • 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.
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  • 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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  • Searches across ALL Fluentive content — features, pricing, FAQ, comparisons, and live blog posts — for topics relevant to a query. Use for generic questions like 'does Fluentive support X?', 'is it good for Y type of business?', or 'I need software that does Z'. Returns the top 5 most relevant content excerpts.
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  • Estimate a software team's verification debt from team parameters. Computes the four published metrics (generation-to-verification ratio, review depth, unverified-merge rate, two-week churn) and an annual cost estimate, with the full calculation path, labeled assumptions, thresholds, and sources (GitClear, Sonar, Faros, Veracode). Deterministic arithmetic from published models - no benchmark claims. Only team_size is required; every additional parameter refines the estimate. Set lang='de' for a German report.
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  • Answer 'best <theme> for <use case>' and 'cheapest <theme>' directly: returns the theme's vendors ranked by entry price (cheapest first, quote-only last), each with its verified compliance facts (HIPAA/SOC 2/GDPR), free-tier flag, best-for tags and the entry plan's source. Conjunctive fact filters narrow it to what this index has actually CONFIRMED — requireHipaa / requireSoc2 / requireGdpr / requireFreeTier (e.g. 'best CRM for HIPAA' = section 'crm-software' + requireHipaa:true). Omit all filters to rank the whole theme by price. Set `section` to the theme slug from list_sections. Never infers a fact it has not verified.
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