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472,903 tools. Updated 2026-08-24 04:54

"Reactive Resume" matching MCP tools:

  • Start (or resume) Stripe Connect onboarding so this account can RECEIVE author royalties. Returns a one-time onboarding_url the human author must open in a browser to complete KYC. Required before a book can be published: an author with no payouts-enabled Connect account can save drafts but their books stay in draft until onboarding finishes. Payouts stay disabled until Stripe verifies the details — poll connect_status afterward.
    Connector
  • Reach out to one candidate. You identify yourself (your name + company, from your account); the candidate is notified and decides. If they accept, you receive an EMAIL with their contact, their message, and a unique verification code — their identity stays private until they choose to share it. METERED (counts toward your contact limit) and requires a prior get_candidate for this resume. One active offer per candidate; respect declines. get_contact also shows the status any time.
    Connector
  • List the user's PENDING approval requests: asks from connected apps (create a card, view full card details, close/pause/resume a card, change a limit) waiting on the user's decision. Surface each one to the user and let THEM decide; after the user answers, resolve with approve_request. NEVER approve or deny on your own — an approval is the user's consent, not yours. Personal sessions only; company-connected sessions have no personal inbox.
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  • Render a Markdown resume to a finished PDF using a ResumeMD template (default: classic — see list_resume_templates for all 32 ids). Returns JSON with a base64-encoded PDF and a suggested filename; decode the base64 to give the user the file. The PDF is generated in memory and never stored. For interactive editing, template switching, and color choices, send the user to resumemd.pro/editor instead.
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  • Update a TAGGING RULE (dashboard: 'Tagging rules') — not a Keyword Monitor entry (those are Watchers; see watcher_update). Rename its term (pass `keyword`), set what it refers to (pass `description`), and/or pause/resume it (pass `active`). Renaming keeps already-tagged records on the old tag; new matches use the new term. Changes take effect on the next scheduled processing cycle. Existing opportunity scores and matches are not retroactively updated. (requires a free Prowlo account — call it to get a signup link)
    Connector
  • Check or stop a recurring lane automation. Actions: 'status' (read-only), 'pause', 'cancel' (permanent), 'skip_next' (skip one week's pickup — nothing books or charges that week). STOP-ONLY by design: there is no agent-side resume, reactivate, or ceiling change — those exist only behind the account owner's emailed approval link. Auth required.
    Connector

Matching MCP Servers

  • A
    license
    A
    quality
    C
    maintenance
    A resume MCP server that enables AI agents to search work history by keyword or meaning, retrieve detailed company info, and send scheduling emails, turning a static resume into interactive tools.
    3
    MIT

Matching MCP Connectors

  • Free open-source resume builder with remote MCP tools for resumes and job applications.

  • Generate tailored, ATS-optimized resume PDFs and cover letters from a job description, over MCP.

  • Release an engaged Emergency Brake, re-enabling exactly the campaigns it paused (and only those still paused — a campaign the user changed since is left alone). mode='raise' re-arms the brake against the budget's current amount for the rest of the month; mode='resume' means the user knowingly overrules the budget, so that level stays disarmed until next month. Re-enables live campaigns and therefore resumes real ad spend — confirm intent first.
    Connector
  • QRAMM-aligned maturity reading for an SRA result. Places a Schedule Risk Analysis run (from ``monte_carlo_p50_p80`` or any equivalent dict) on the five named maturity levels of AACE RP 122R-22 (Quantitative Risk Analysis Maturity Model), section 3: level 1 Reactive, level 2 Ad-hoc, level 3 Centralized, level 4 Dynamic, level 5 Adaptive. Inputs the SRA inspects (defensively, all keys optional): - baseline.percentiles (lowercase p50 / p80 presence) - baseline.config (iterations, opt/ml/pes %, distribution) - baseline.sensitivity (per-activity tornado rows, on_cp) - mitigated (scenario comparison evidence) - risk_register_simulation + risk_register_used (Hulett quantified risk register evidence) - convergence (MC diagnostics, required for level 5) Use this tool any time you have an SRA result and want a maturity reading for a forensic-claim methodology section. Note the scope limit the badge carries on every render: AACE 122R-22 assesses the quantitative-risk capability of an ORGANIZATION and states it is guidelines rather than a standard, so a reading on one simulation run is CPP's placement on the RP's scale, not a QRAMM score. Report it as "QRAMM-aligned", never as "per AACE 122R-22". Args: sra_result: dict from ``monte_carlo_p50_p80``. May be {} - the badge degrades to level 1 with the missing evidence listed. Returns: { "rp_citation": "AACE RP 122R-22 ...", "scale_max": 5, "scale_note": "... names five levels ...", "level": int (1-5), "level_name": "Reactive" | "Ad-hoc" | "Centralized" | "Dynamic" | "Adaptive", "level_label": "Level 3: Centralized", "level_description": what CPP requires of a run there, "level_color": "#xxxxxx", "evidence": ["..." what the SRA had / lacked], "gaps_to_next_level": ["..." concrete advance steps], "caveat": scope-limit string } The keys "tier", "tier_label", "tier_description", "tier_color" and "gaps_to_next_tier" are retained as aliases carrying the same five-level values.
    Connector
  • Tailor a resume to a SPECIFIC job — TWO steps. STEP 1 (default; action omitted or 'prepare'): the server returns the job's full JD, its must-have skills/requirements, and the candidate's current resume, plus tailoring instructions. YOU (the model) then WRITE the tailored resume as JSON Resume, following the instructions — weave JD keywords into existing bullets only where the candidate genuinely has the experience, never fabricate experience/titles/dates/employers, keep all dates and company names, and flag any keyword you couldn't honestly add. STEP 2: call this tool again with action:'save', tailored_resume:<your JSON Resume>, and job_id — the server renders a PDF and saves it to the candidate's Workopia dashboard (requires sign-in). Use whenever the user references a specific job to tailor for: 'tailor for #1', 'for Morgan Stanley', 'tailor my resume for this role: <JD>'. Resolving job_id (same rules as job_detail_tool): from the most recent prior search/refine result — (a) numeric/ordinal → the Nth job; (b) company name → Company-field match; (c) role/title phrase → Job-Title match — then pass that job's **Job Id** value VERBATIM. Do NOT use placeholders like 'JOB_1' or '#1'. For STEP 1 supply ONE of job_id (preferred — server fetches the JD from Mongo) OR job_description, plus the candidate's resume via resume_text / resume_content / resume_data. For general 'improve my resume' (no specific job), do NOT call this tool — call resume_tool action=improve instead. Note: the tailored resume is written by your AI client's own model — the assistant you are already using — so it works out of the box with nothing to configure; Workopia runs no LLM of its own and never charges for the AI.
    Connector
  • Replay your agent journal oldest→newest (CO 230-001). Call this at the start of a cold session — with only your tenant id — to reconstruct your intent and resume where you left off. Pairs with federation_journal_append. Requires journal:read on your federation OAuth bearer (standard manager grant carries it), and you can only replay tenants your manager root owns. Returns: The journal entries oldest→newest (up to limit). Example: call federation_journal_read with arguments {"tenant_id":"<tenant_id>"}.
    Connector
  • Resume (un-cancel) a pending-cancel add-on whose paid-through cycle has not yet ended. Clears the cancellation so the add-on renews normally at the next cycle boundary. No new charge — the cycle was already paid. Stackable add-ons cannot be resumed; buy a new unit instead. Returns {addonKey, project, nextRenewalAt, resumed}. Owner-only; requires a token minted with the billing scope.
    Connector
  • Purpose: Evidence that OneQAZ detects price moves BEFORE news publication. Returns leading_score, avg_lead_time_minutes, and accuracy_pct per event type. Strongest Trust Layer A evidence (Layer A = anticipation-capability tier of OneQAZ's 5-layer trust pyramid) — proves the system is anticipatory rather than reactive. Triggers (casual questions too): "can you predict news?", "뉴스 나오기 전에 감지해?", "how early do you catch moves?", "뉴스보다 빨라?", "do prices move before headlines?". When to call: when an AI is evaluating predictive capability. Prerequisites: none. Next steps: get_news_causality_breakdown for the 3-type classification. Caveats: empty when no news events processed in the recent window. Args: market_id: Market identifier (crypto, kr_stock, us_stock, etc.) target_market: Alias for market_id (backward compat) min_sample_count: Minimum sample count for statistical significance (default 3) Disclaimer: Information only, not investment advice.
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  • Search the talent graph. Returns ANONYMOUS match cards — headline, skills (with skills_matched showing which of YOUR terms hit), seniority, location, availability, salary range, and a short snippet — but NO name, full resume, or contact. Call get_candidate (a metered reveal) for the deeper anonymous profile. Filter by skills, location, seniority, salary, experience, availability, and more; sort by recency (default) or skill_match. Always paginated (max 25 per page).
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  • The unit tests (code examples) for HMR. Always call `learn-hmr-basics` and `view-hmr-core-sources` to learn the core functionality before calling this tool. These files are the unit tests for the HMR library, which demonstrate the best practices and common coding patterns of using the library. You should use this tool when you need to write some code using the HMR library (maybe for reactive programming or implementing some integration). The response is identical to the MCP resource with the same name. Only use it once and prefer this tool to that resource if you can choose.
    Connector
  • Apply to an active Loppee job on behalf of the calling customer account. Requires a customer personal agent key whose account_id matches the account_id argument and whose allowed_actions include apply_to_job. The seeker is never charged. The resume must be a base64 PDF, DOC, or DOCX file and is stored in a private bucket; employers and the applicant retrieve it only through scoped short-lived signed URLs.
    Connector
  • Fetch a job seeker's structured, machine-readable resume as JSON Resume (https://jsonresume.org/schema/) — but ONLY when its human owner has explicitly shared a consent token for it. Pass that token and the tool returns the JSON Resume plus ats_context: how to render the profile for the owner's target applicant tracking system, grounded in ResumeAI's portal-verified State of ATS 2026 data (recommended file format, layout, and vendor parsing rules). No token, an invalid token, or a token the owner has revoked returns nothing. There is no way to browse, search, list, or enumerate resumes with this server — the owner-minted token is the only key, and the owner can revoke it at any time. This tool never exposes personal data without one.
    Connector
  • Continue a stalled or finished workflow run from a chosen step. This starts a NEW run that reuses the outputs the original run already recorded and only executes — and only pays for — the steps from 'from_step' onward. The original run is left untouched and the new one records which run it continues. Omit 'from_step' to resume at the first step that has no recorded output. A step whose output was never recorded is re-run, never skipped. Requires authentication.
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  • Use when someone needs a published Rung occupation, resume-situation, or military-transition guide. Returns public guide facts, source pages, and browser handoffs. Do not use for live jobs, employer search, resume editing, qualification decisions, or private work history; never send personal or resume data.
    Connector
  • Start, pause, or resume a project's autonomous work. `action` is one of: "enable" | "disable" | "resume" | "process_now". - enable/disable flip scheduler_enabled (the loop dispatches only enabled, status='active' projects). - resume clears a pause (peak/backoff/manual) so the project dispatches again. - process_now forces the next intake batch (no-op if the scheduler is off or no intake_pending request is queued). Returns the resulting scheduler state.
    Connector
  • Replay your agent journal oldest→newest (CO 230-001). Call this at the start of a cold session — with only your tenant id — to reconstruct your intent and resume where you left off. Pairs with federation_journal_append. Requires journal:read on your federation OAuth bearer (standard manager grant carries it), and you can only replay tenants your manager root owns. Returns: The journal entries oldest→newest (up to limit). Example: call federation_journal_read with arguments {"tenant_id":"<tenant_id>"}.
    Connector