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521,397 tools. Updated 2026-09-06 11:00

"Atlassian" matching MCP tools:

  • Search jobs across 90+ countries by title, location, salary, remote/hybrid work mode, or employment type. Find roles in tech, finance, product, design, marketing, and every other vertical — aggregated from 1000+ ATS sources globally. Default action is search; use refine when the user asks for more matches or gives feedback on a prior result set; use save to bookmark a job for the signed-in user (requires OAuth). REFINE PROTOCOL (action=refine has THREE distinct modes): (1) Pure continuation / 'show me more' / 'next batch' / 'another set' / 'more like these': pass refine_recommendations.exclude_ids = the full array of **Job Id** values from the most recent search/refine result's content text (verbatim) + refine_recommendations.session_id = prior response's session_id if present. Server returns next 10 unique jobs. (2) 'Show me more like #N' / 'similar to the Atlassian one' / 'jobs like #2': pass refine_recommendations.liked_indexes = [N] (1-based position from prior numbered list) + exclude_ids + session_id. Equivalently you may pass refine_recommendations.liked_job_ids = [<that job's **Job Id** value verbatim>]. Server seeds the recommendation from that job's title/skills/company profile. (3) 'Less like #N' / 'no more N-style jobs' / 'avoid jobs like that': pass refine_recommendations.disliked_indexes = [N] (or disliked_job_ids = [<Job Id>]) + exclude_ids + session_id. Server suppresses similar jobs. All three modes: if you skip exclude_ids, the user sees duplicates — that's a failure. The handler layers exclude_ids with server-side AgentKit memory, so partial lists still work. NEVER invent 'JOB_1' / '#1' as job_id values — always use the real **Job Id** string from the prior result's content text. For detail requests (user asks about a specific job from the list, e.g. 'details for #1', 'show me this job', 'tell me more about <company>'), DO NOT call this tool — call job_detail_tool instead. That separate tool binds to the job-detail widget card so the full job card renders in chat. OUTPUT BEHAVIOR: Render the search results as a numbered markdown list, one line per job, in this exact compact format: `N. **[Job Title](View_Job_URL)** — Company · Location · Job Type · Compensation · Posted MMM DD`. Embed the View Job URL as a markdown link on the title (so the user can click to apply). Keep URLs intact — don't strip parameters. Skip a field entirely if it's missing — never print 'N/A' placeholders. The numbered list IS the canonical user-facing answer. REQUIRED follow-up: after the list, output EXACTLY these two sentences as two parallel questions (same pattern for action=search and action=refine): Sentence 1 — 'Would you like to see full details on any of these? Reply with the number (#1), the company name, or the role title.' Sentence 2 — 'Or would you like to refine the list — what should change (work mode, level, salary, sector)?' These two sentences must be separate and parallel; do NOT merge them into one 'detail ... or refine' clause (that buries the detail CTA). Both questions must be asked every time after a search or refine result. When the user replies referring to a specific job from the list, identify which job they mean and call job_detail_tool immediately. Identifying the job (use flexibly — users rarely type '#N' literally): (a) any numeric or ordinal reference ('#1', '1', 'first', 'the 1st', 'top one', 'job 3', 'the third') → the Nth job in your prior numbered list; (b) a company name, partial or full ('Morgan Stanley', 'Morstan', 'Capital One') → case-insensitive substring match on the Company field of the prior list, pick the first match; (c) a role/title phrase ('the analyst role', 'the credit risk one') → case-insensitive substring match on the Job Title field. If multiple jobs match, prefer the earliest. Only if no reasonable match exists, ask a one-line clarifying question. Then pass that job's **Job Id** value from the prior search result's content text VERBATIM as job_id to job_detail_tool / tailor_resume_tool / cover_letter_tool. Do NOT invent a placeholder like 'JOB_1' or '#1' — those are not server-valid IDs. For save, pass job_id + optional job_title/company/job_url in save_job. Put search fields in search_jobs or parameters; refine in refine_recommendations; save in save_job.
    Connector
    Destructive
    No auth
  • Fetches operational status of major dev infrastructure (GitHub, Cloudflare, Discord, OpenAI, Vercel, npm, Reddit, Atlassian, Anthropic). Cache TTL 60s. Use when the agent needs to know if a dependency is up or to explain a recent outage.
    ConnectorNo auth
  • Search jobs across 90+ countries by title, location, salary, remote/hybrid work mode, or employment type. Find roles in tech, finance, product, design, marketing, and every other vertical — aggregated from 1000+ ATS sources globally. Default action is search; use refine when the user asks for more matches or gives feedback on a prior result set; use save to bookmark a job for the signed-in user (requires OAuth). REFINE PROTOCOL (action=refine has THREE distinct modes): (1) Pure continuation / 'show me more' / 'next batch' / 'another set' / 'more like these': pass refine_recommendations.exclude_ids = the full array of **Job Id** values from the most recent search/refine result's content text (verbatim) + refine_recommendations.session_id = prior response's session_id if present. Server returns next 10 unique jobs. (2) 'Show me more like #N' / 'similar to the Atlassian one' / 'jobs like #2': pass refine_recommendations.liked_indexes = [N] (1-based position from prior numbered list) + exclude_ids + session_id. Equivalently you may pass refine_recommendations.liked_job_ids = [<that job's **Job Id** value verbatim>]. Server seeds the recommendation from that job's title/skills/company profile. (3) 'Less like #N' / 'no more N-style jobs' / 'avoid jobs like that': pass refine_recommendations.disliked_indexes = [N] (or disliked_job_ids = [<Job Id>]) + exclude_ids + session_id. Server suppresses similar jobs. All three modes: if you skip exclude_ids, the user sees duplicates — that's a failure. The handler layers exclude_ids with server-side AgentKit memory, so partial lists still work. NEVER invent 'JOB_1' / '#1' as job_id values — always use the real **Job Id** string from the prior result's content text. For detail requests (user asks about a specific job from the list, e.g. 'details for #1', 'show me this job', 'tell me more about <company>'), DO NOT call this tool — call job_detail_tool instead. That separate tool binds to the job-detail widget card so the full job card renders in chat. OUTPUT BEHAVIOR: Render the search results as a numbered markdown list, one line per job, in this exact compact format: `N. **[Job Title](View_Job_URL)** — Company · Location · Job Type · Compensation · Posted MMM DD`. Embed the View Job URL as a markdown link on the title (so the user can click to apply). Keep URLs intact — don't strip parameters. Skip a field entirely if it's missing — never print 'N/A' placeholders. The numbered list IS the canonical user-facing answer. REQUIRED follow-up: after the list, output EXACTLY these two sentences as two parallel questions (same pattern for action=search and action=refine): Sentence 1 — 'Would you like to see full details on any of these? Reply with the number (#1), the company name, or the role title.' Sentence 2 — 'Or would you like to refine the list — what should change (work mode, level, salary, sector)?' These two sentences must be separate and parallel; do NOT merge them into one 'detail ... or refine' clause (that buries the detail CTA). Both questions must be asked every time after a search or refine result. When the user replies referring to a specific job from the list, identify which job they mean and call job_detail_tool immediately. Identifying the job (use flexibly — users rarely type '#N' literally): (a) any numeric or ordinal reference ('#1', '1', 'first', 'the 1st', 'top one', 'job 3', 'the third') → the Nth job in your prior numbered list; (b) a company name, partial or full ('Morgan Stanley', 'Morstan', 'Capital One') → case-insensitive substring match on the Company field of the prior list, pick the first match; (c) a role/title phrase ('the analyst role', 'the credit risk one') → case-insensitive substring match on the Job Title field. If multiple jobs match, prefer the earliest. Only if no reasonable match exists, ask a one-line clarifying question. Then pass that job's **Job Id** value from the prior search result's content text VERBATIM as job_id to job_detail_tool / tailor_resume_tool / cover_letter_tool. Do NOT invent a placeholder like 'JOB_1' or '#1' — those are not server-valid IDs. For save, pass job_id + optional job_title/company/job_url in save_job. Put search fields in search_jobs or parameters; refine in refine_recommendations; save in save_job.
    Connector
    Destructive
    No auth
  • Post the output of jira_to_test_suite as a formatted comment on the source Jira ticket. Converts Gherkin, E2E steps, API tests, and ambiguities into Atlassian Document Format (ADF). STATEFUL — creates a comment on the issue.
    ConnectorNo auth
  • Check the current health status for one or more vendors. Accepts registered vendor slugs (e.g., "github", "aws", "gcp", "gitlab") or raw Atlassian Statuspage base URLs. Registry entries are served by each vendor's native status API (Statuspage, Status.io, Slack, AWS Health, Google Cloud Service Health, Firehydrant) and normalized to one shape. Returns per-vendor operational indicator (none = all clear, minor, major, critical, maintenance = scheduled window), degraded components, and active incidents. Use mode: "detailed" for component lists and maintenance windows, narrowed with component_filter and bounded by component_limit. Batch-friendly — pass a list to check your full stack in one call; a vendor that cannot be resolved or reached is reported in its own result row, so one bad entry never discards the rest.
    ConnectorNo auth
  • Which companies this service-status pack can answer for: 190 verified Atlassian Statuspage hosts across AI and model providers, cloud and hosting, databases and observability, developer tools, payments and fintech, communications, and business SaaS. Returns the total count plus each vendor's lookup key, display name, category and status hostname, so a vendor name can be confirmed before calling statuspage_check instead of guessed. Also lists well-known companies whose status pages use a different format, together with the URL a human should open. Filter by category or search text.
    ConnectorNo auth

Matching MCP Servers

Matching MCP Connectors

  • Use this when the user wants accessibility findings exported from a site to go to a different Jira project, or is setting one up for the first time. WRITES to this website's Inclusify configuration, never to the site itself and never to Jira — it records which project key exports should use, and files no tickets by itself. It CANNOT connect Jira: authorising Atlassian is a browser OAuth flow on the Inclusify panel's Integrations page and no assistant can do it, so this refuses until the workspace is connected. It also cannot list the available projects — ask the user for the project key, or have them read it off the board. REQUIRES CONFIRMATION, because pointing this at the wrong board sends the work to a team that did not ask for it while the team that did sees nothing, and nobody notices until they ask why no tickets were ever raised. The account owner is emailed a record, including the previous key. Needs the PRO plan, matching the panel.
    Connector
    Destructive
    API key
  • Incident and outage history for a vendor's status page — what broke, when, and whether it is fixed. Covers 190 verified Atlassian Statuspage vendors across AI providers, clouds, developer platforms, payments and communications. Each incident returns its title, lifecycle status (investigating / identified / monitoring / resolved), impact level (none / minor / major / critical), the time it started, the time it resolved, how long it lasted, the affected components, and the text of the latest update the vendor posted. Set unresolved_only to see only incidents that are still open. Use for outage history, past downtime, current incidents and postmortem timelines. Pass status_host for vendors outside the curated map.
    ConnectorNo auth
  • Everything about a domain in one call: who registered it and when, when it expires, its DNS records, the mail and DNS providers behind them, the SaaS vendors its TXT verification tokens reveal (Google Workspace, Microsoft 365, Salesforce, Atlassian, Okta, …), SPF/DMARC posture, and risk flags like newly-registered or no-registrar-lock. Use for vendor due diligence, security triage, phishing checks and prospect research. Price: $0.005
    ConnectorNo auth
  • Is a service down right now? Live service status, outage and uptime check for 190 vendors that publish an Atlassian Statuspage — OpenAI, Anthropic/Claude, GitHub, Cloudflare, Vercel, Netlify, DigitalOcean, MongoDB, Snowflake, Datadog, Twilio, SendGrid, Zoom, Discord, Shopify, Coinbase, Plaid, Figma, Dropbox, Atlassian/Jira and more. Returns the current status indicator (none / minor / major / critical / maintenance), the vendor's own status line such as "All Systems Operational" or "Partial System Outage", every component currently degraded or offline, open incidents with their latest update text and how long they have been running, and upcoming scheduled maintenance where the page publishes it. Use for questions about downtime, outages, service health, incidents in progress and whether an API or platform is working. Pass status_host to check any other vendor running a Statuspage.
    ConnectorNo auth
  • Browse available content design systems — brand voice and tone guides (Conversational Product Voice, GOV.UK, Shopify Polaris, Atlassian). Filter by category or search by name.
    ConnectorNo auth