_ registry / mcp http-sse · checked 56m ago

AI Applyd

https://mcp.aiapplyd.com

Registry code: af4aeb3af47fb30a

api record

AI Applyd finds jobs that fit the user, tailors their resume and cover letter for each one, and submits the application on the employer's own hiring system. Every tool runs on the user's connected AI Applyd account and plan.

The main loop:

endpoint
https://mcp.aiapplyd.com/mcp
protocol
http-sse ·2025-06-18
authentication
none observed
public key
none — nobody has proven they own this listing
karma
0 · newcomer
reachable
live
uptime, 30 days
100%

90 days 100%· all time 100%

latency
1,422ms

last good check

priced tools
0

of 17 tools

_ answered our checks, 90 days 1 checks · signed record
  • unknown → live
_ what it is for
topic
productivity & business hr & recruiting
used for
  • find jobs matching a resume
  • tailor resume and cover letter
  • submit job applications
  • score a resume for ats
  • prepare for a job interview
takes → gives
text, documents → text, documents, data
tools
10 reads4 changes data3 sends messages
_ used through this hub 30 days

The one measurement on this page that an operator cannot produce by editing a file on its own server: somebody else chose it, and paid to. Read the accounts before the calls — volume from one account is one relationship, and calling yourself is the cheap half. Both are what the ranking is built from, printed so the order can be checked rather than taken on trust.

accounts
0

distinct, expensive to fake

calls served
0

successful, last 30 days

_ what it can do 17 tools
17 auth-required 17 of 17 classified

Price is per tool, not per server. An agent whose handshake is open can hold tools that demand a key or a payment, and one figure for the whole agent sends callers into a wall.

  • aiapplyd_review_application sends messages auth-required never probed

    Act on the user's applications. decision "approve" submits each waiting application on the employer's hiring system under the user's name: it spends one of their applications per job and cannot be undone. "reject" skips it: nothing is sent and nothing is spent. "cancel" stops one that is still queued or preparing. "refine" rewrites its resume or cover letter from instructions (document_type and instructions; uses AI credits). "re_prepare" builds its documents again (optional steps). "set_stage" records how it is going (stage). Pass up to 25 application_ids from aiapplyd_get_applications. Only approve on the user's explicit go-ahead, such as a "yes" to a specific application. On a timeout or an error, call aiapplyd_get_applications before retrying; an approve that already went through is reported as already approved. Do not use it for matches with no application yet; use aiapplyd_apply or aiapplyd_triage_matches. Next: aiapplyd_get_applications to follow the submissions.

    mcp-tool

    {
  "type": "object",
  "$schema": "http://json-schema.org/draft-07/schema#",
  "required": [
    "decision",
    "application_ids"
  ],
  "properties": {
    "stage": {
      "enum": [
        "applied",
        "callback",
        "phone_screen",
        "interview",
        "offered",
        "rejected",
        "no_response"
      ],
      "type": "string",
      "description": "For set_stage: applied, callback, phone_screen, interview, offered, rejected or no_response."
    },
    "steps": {
      "type": "array",
      "items": {
        "enum": [
          "quality_gate",
          "company_intel",
          "tailor_resume",
          "translate",
          "cover_letter"
        ],
        "type": "string"
      },
      "description": "For re_prepare: the steps to run again. Omit to run every step that is out of date."
    },
    "decision": {
      "enum": [
        "approve",
        "reject",
        "cancel",
        "refine",
        "re_prepare",
        "set_stage"
      ],
      "type": "string",
      "description": "\"approve\" submits the application to the employer and cannot be undone. \"reject\" skips it and sends nothing. \"cancel\" stops a queued one. \"refine\" rewrites a document (needs document_type and instructions). \"re_prepare\" builds its documents again. \"set_stage\" records the stage (needs stage)."
    },
    "instructions": {
      "type": "string",
      "maxLength": 2000,
      "description": "For refine: what to change, in the user's own words (up to 2,000 characters)."
    },
    "document_type": {
      "enum": [
        "resume",
        "cover_letter"
      ],
      "type": "string",
      "description": "For refine: \"resume\" or \"cover_letter\"."
    },
    "application_ids": {
      "type": "array",
      "items": {
        "type": "integer",
        "maximum": 9007199254740991,
        "exclusiveMinimum": 0
      },
      "description": "Application ids to act on, 1 to 25 (e.g. [1550, 1551]), from aiapplyd_get_applications"
    }
  }
}
    arguments 71 lines
  • aiapplyd_update_job_preferences changes data auth-required never probed

    Set what AI Applyd hunts for on the user's behalf, and re-run discovery immediately: target roles, locations, remote, salary band and currency, seniority (experience_levels), work styles, job types, visa sponsorship need, industries to exclude, or pause matching. Pass description to say it in plain words ("remote only, 120k+, senior, no crypto"); fields passed explicitly win over it. Lists REPLACE what is saved, so pass the complete list, not an addition. application_answers saves the answers employer forms ask for (phone, city, state, zip, country, LinkedIn, work authorization, relocation, start date, notice period): fill only values the user stated, never guesses. Only call this when the user asks. Read the current preferences first with aiapplyd_get_account. Do not use it to search; use aiapplyd_get_matches with query.

    mcp-tool

    {
  "type": "object",
  "$schema": "http://json-schema.org/draft-07/schema#",
  "properties": {
    "paused": {
      "type": "boolean",
      "description": "True pauses new matches for the user; false resumes them. It never changes auto-apply."
    },
    "job_types": {
      "type": "array",
      "items": {
        "enum": [
          "full_time",
          "part_time",
          "contract",
          "internship",
          "freelance",
          "temporary"
        ],
        "type": "string"
      },
      "description": "Job types to match: full_time, part_time, contract, internship, freelance, temporary. REPLACES the saved list."
    },
    "locations": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Full list of preferred locations. REPLACES the saved list."
    },
    "salary_max": {
      "type": "number",
      "minimum": 0,
      "description": "Highest yearly salary to target, in salary_currency."
    },
    "salary_min": {
      "type": "number",
      "minimum": 0,
      "description": "Lowest yearly salary the user accepts, in salary_currency (e.g. 120000)."
    },
    "description": {
      "type": "string",
      "maxLength": 2000,
      "description": "What the user wants, in their own words (e.g. \"remote only, 120k+, senior, no crypto\"). Fields passed explicitly win over it. Uses AI credits."
    },
    "remote_only": {
      "type": "boolean",
      "description": "Deprecated name of include_remote. Use include_remote."
    },
    "work_styles": {
      "type": "array",
      "items": {
        "enum": [
          "onsite",
          "hybrid",
          "remote"
        ],
        "type": "string"
      },
      "description": "Work styles to match: onsite, hybrid, remote. REPLACES the saved list."
    },
    "target_roles": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Full list of job titles to hunt for. REPLACES the saved list."
    },
    "include_remote": {
      "type": "boolean",
      "description": "Include remote jobs in the user's region alongside their locations."
    },
    "salary_currency": {
      "enum": [
        "usd",
        "eur",
        "gbp",
        "cad",
        "aud",
        "inr"
      ],
      "type": "string",
      "description": "Currency of the salary band (default usd)."
    },
    "experience_levels": {
      "type": "array",
      "items": {
        "enum": [
          "entry",
          "mid",
          "senior",
          "lead",
          "executive"
        ],
        "type": "string"
      },
      "description": "Seniority to match: entry, mid, senior, lead, executive. REPLACES the saved list."
    },
    "exclude_industries": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "Industries to never match (e.g. [\"Crypto\"]). REPLACES the saved list."
    },
    "application_answers": {
      "type": "object",
      "properties": {
        "city": {
          "type": "string"
        },
        "phone": {
          "type": "string"
        },
        "state": {
          "type": "string"
        },
        "country": {
          "type": "string"
        },
        "zip_code": {
          "type": "string"
        },
        "linkedin_url": {
          "type": "string"
        },
        "notice_period": {
          "enum": [
            "immediately",
            "two_weeks",
            "one_month",
            "two_months",
            "three_months",
            "flexible"
          ],
          "type": "string"
        },
        "work_authorization": {
          "enum": [
            "us_citizen",
            "permanent_resident",
            "visa_holder",
            "require_sponsorship",
            "other"
          ],
          "type": "string"
        },
        "willing_to_relocate": {
          "type": "boolean"
        },
        "available_start_date": {
          "type": "string"
        }
      },
      "description": "Answers employer forms ask for, saved to the user's application profile: phone, city, state, zip_code, country, linkedin_url, work_authorization, willing_to_relocate, available_start_date, notice_period. Only values the user stated, never guesses."
    },
    "needs_visa_sponsorship": {
      "type": "boolean",
      "description": "True when the user needs visa sponsorship to take the job."
    }
  }
}
    arguments 162 lines
  • aiapplyd_generate_cover_letter reads auth-required never probed

    Write a cover letter for a specific job from the base resume saved on the user's AI Applyd account, in their own voice and free of recruiter cliches. Returns the finished letter as text and saves it to the account. Pass application_id instead to get the letter already written for that application (no new letter), with instructions to change it. Needs a resume on file (see aiapplyd_set_resume) and a paid plan (Hired in 30+); without either it says so and links the fix. Uses the user's AI credits. Do not use it for applications: aiapplyd_apply already writes a cover letter for every one.

    mcp-tool

    {
  "type": "object",
  "$schema": "http://json-schema.org/draft-07/schema#",
  "properties": {
    "company_name": {
      "type": "string",
      "maxLength": 200,
      "minLength": 1,
      "description": "Name of the company you are applying to"
    },
    "instructions": {
      "type": "string",
      "maxLength": 2000,
      "description": "With application_id: what to change in that letter, in the user's own words."
    },
    "application_id": {
      "type": "integer",
      "maximum": 9007199254740991,
      "description": "Return the cover letter already written for this application (an id from aiapplyd_get_applications) instead of writing a new one.",
      "exclusiveMinimum": 0
    },
    "job_description": {
      "type": "string",
      "maxLength": 50000,
      "minLength": 50,
      "description": "Full text of the target job description. Pass with company_name, or pass application_id instead."
    }
  }
}
    arguments 29 lines
  • aiapplyd_get_account reads auth-required 56m ago

    Show the user's AI Applyd account: plan, token balance, applications left in the current 30-day window, the job preferences their matches are found against, and readiness: whether a resume is on file, whether setup is finished, and which profile fields employer forms require that are still empty. Also lists their resumes and the default apply mode. Call it first, and before applying to several jobs. Read-only: it spends no credits and changes nothing. Do not use it to change anything; use aiapplyd_update_job_preferences or aiapplyd_set_resume. Next: aiapplyd_set_resume when no resume is on file, otherwise aiapplyd_get_matches.

    mcp-tool

    {
  "type": "object",
  "$schema": "http://json-schema.org/draft-07/schema#",
  "properties": {}
}
    arguments 5 lines
  • aiapplyd_get_applications reads auth-required 56m ago

    List the user's applications and where each one stands, or read one by application_id to see what will be or was sent: the tailored resume, the cover letter, the screening answers, why it stopped, and its place in the queue, plus the employer's confirmation page as an image when that page is the proof. Use this to check progress, to find applications waiting for the user's approval (status "waiting_for_review"), or to see whether an employer confirmed a submission. An application is reported as employer-confirmed only when the employer sent a receipt or showed its confirmation page. Other status filters: queued_to_apply, submitted, verified, not_landed, taken_down. Returns 20 per page. Read-only: it spends no credits. Do not use it to act on an application; use aiapplyd_review_application. Next: aiapplyd_review_application to approve, reject or change what is waiting.

    mcp-tool

    {
  "type": "object",
  "$schema": "http://json-schema.org/draft-07/schema#",
  "properties": {
    "page": {
      "type": "integer",
      "maximum": 9007199254740991,
      "description": "Page number, starting at 1 (e.g. 2 for the next page)",
      "exclusiveMinimum": 0
    },
    "status": {
      "enum": [
        "waiting_for_review",
        "queued_to_apply",
        "verified",
        "submitted",
        "not_landed",
        "taken_down"
      ],
      "type": "string",
      "description": "Filter the list: waiting_for_review (the review queue), queued_to_apply, submitted, verified, not_landed or taken_down. Omit for all."
    },
    "application_id": {
      "type": "integer",
      "maximum": 9007199254740991,
      "description": "Read one application by its id (e.g. 1550). Omit to list applications.",
      "exclusiveMinimum": 0
    }
  }
}
    arguments 30 lines
  • aiapplyd_get_matches reads auth-required 56m ago

    List the user's matched jobs: the roles AI Applyd found for them against their saved job preferences, best matches first, each with a job_match_id, title, company, location, match score, a 500-character excerpt of the posting and the apply URL. Pass job_match_ids (up to 10) to read the full posting, skills and benefits of specific matches; job_url to read any posting without saving it; query, location or remote_only to narrow the list; after_job_match_id with the newestJobMatchId you stored to see only matches newer than your last check. Read-only: it spends no credits and changes nothing. Do not use it to change what the user is matched against; use aiapplyd_update_job_preferences for that. Next: pass a job_match_id to aiapplyd_apply, or save or skip a match with aiapplyd_triage_matches.

    mcp-tool

    {
  "type": "object",
  "$schema": "http://json-schema.org/draft-07/schema#",
  "properties": {
    "page": {
      "type": "integer",
      "maximum": 9007199254740991,
      "description": "Page number, starting at 1 (e.g. 2 for the next page)",
      "exclusiveMinimum": 0
    },
    "limit": {
      "type": "integer",
      "maximum": 50,
      "minimum": 1,
      "description": "Matches per page, 1 to 50 (default 10)"
    },
    "query": {
      "type": "string",
      "maxLength": 200,
      "description": "Narrow the list to titles containing this text (e.g. \"Product Designer\")."
    },
    "job_url": {
      "type": "string",
      "format": "uri",
      "description": "Read any job posting by URL without saving it (e.g. \"https://jobs.lever.co/acme/123\")."
    },
    "location": {
      "type": "string",
      "maxLength": 200,
      "description": "Preferred location (e.g. \"San Francisco, CA\", \"New York\", \"Remote\")"
    },
    "saved_only": {
      "type": "boolean",
      "description": "If true, only return the matches the user saved"
    },
    "remote_only": {
      "type": "boolean",
      "description": "If true, only show remote-friendly positions"
    },
    "job_match_ids": {
      "type": "array",
      "items": {
        "type": "integer",
        "maximum": 9007199254740991,
        "exclusiveMinimum": 0
      },
      "description": "Read these matches in full: up to 10 job_match_ids (e.g. [48213]). Returns the full posting, skills, benefits and work arrangement."
    },
    "after_job_match_id": {
      "type": "integer",
      "maximum": 9007199254740991,
      "description": "Return only matches newer than this job_match_id. Store newestJobMatchId from each answer and pass it back.",
      "exclusiveMinimum": 0
    }
  }
}
    arguments 56 lines
  • aiapplyd_auto_apply sends messages auth-required never probed

    Deprecated alias of aiapplyd_apply, use aiapplyd_apply. Applies to ONE job posting by job_url, end to end, on the employer's own hiring system (Workday, Greenhouse, Lever, Ashby, Workable, iCIMS, Personio, Recruitee, Teamtailor, Rippling, Breezy, SmartRecruiters, BambooHR, JazzHR, softgarden), following the account's review setting. Spends one of the user's applications.

    mcp-tool

    {
  "type": "object",
  "$schema": "http://json-schema.org/draft-07/schema#",
  "required": [
    "job_url"
  ],
  "properties": {
    "job_url": {
      "type": "string",
      "format": "uri",
      "description": "URL of the job posting to apply to"
    }
  }
}
    arguments 14 lines
  • aiapplyd_build_pdf changes data auth-required never probed

    Build a formatted, ATS-clean resume from raw text in the user's AI Applyd resume builder, where it stays editable and downloads as a PDF. Templates: modern, classic, or minimal. Private to the account by default; set make_public to true only if the user explicitly asks for a shareable public link. Requires a paid plan (Hired in 30+). Uses the user's AI credits. Do not use it to rewrite a resume; use aiapplyd_optimize_resume.

    mcp-tool

    {
  "type": "object",
  "$schema": "http://json-schema.org/draft-07/schema#",
  "required": [
    "resume_text"
  ],
  "properties": {
    "template": {
      "enum": [
        "classic",
        "modern",
        "minimal"
      ],
      "type": "string",
      "description": "Resume template style (default: classic)"
    },
    "make_public": {
      "type": "boolean",
      "description": "Publish a public share link. Anyone with the link sees the resume INCLUDING its contact details. Defaults to false (private). Only set true when the user explicitly asks to share it."
    },
    "resume_text": {
      "type": "string",
      "maxLength": 50000,
      "minLength": 50,
      "description": "Full text of the resume"
    }
  }
}
    arguments 28 lines
  • aiapplyd_apply sends messages auth-required never probed

    Apply to one job on the user's behalf. Pass job_match_id from aiapplyd_get_matches, or job_url for any posting. AI Applyd rewrites the resume and cover letter for that role, then completes and submits the application on the employer's own hiring system (Workday, Greenhouse, Lever, Ashby, iCIMS and the other major ATS platforms). mode "auto" submits with no review step; mode "review" prepares everything and holds it for the user's approval; omit mode to follow the review setting on the user's account. The mode applies to this one application and never changes the user's settings. Spends one of the user's applications and AI credits, and a submitted application cannot be withdrawn, so apply only to jobs the user chose. Returns the application id and a tracking link; when the job already has an application, that one comes back with alreadyExisted true instead of a second. On a timeout or an error, call aiapplyd_get_applications before retrying, and never re-apply by job_url to a job already applied to by job_match_id. Do not use it to save or skip a match; use aiapplyd_triage_matches. Next: aiapplyd_get_applications to follow it, and aiapplyd_review_application if it waits for approval.

    mcp-tool

    {
  "type": "object",
  "$schema": "http://json-schema.org/draft-07/schema#",
  "properties": {
    "mode": {
      "enum": [
        "auto",
        "review"
      ],
      "type": "string",
      "description": "\"auto\" submits with no review step. \"review\" holds the prepared application for the user's approval. Omit to follow the user's account setting. Applies to this application only."
    },
    "job_url": {
      "type": "string",
      "format": "uri",
      "description": "URL of any job posting to apply to (e.g. \"https://boards.greenhouse.io/acme/jobs/123\"). Pass this OR job_match_id."
    },
    "job_match_id": {
      "type": "integer",
      "maximum": 9007199254740991,
      "description": "The job_match_id of a match from aiapplyd_get_matches (e.g. 48213). Pass this OR job_url.",
      "exclusiveMinimum": 0
    }
  }
}
    arguments 25 lines
  • aiapplyd_set_resume changes data auth-required never probed

    Put the user's resume on their AI Applyd account as the base every application is tailored from. Pass exactly one: resume_text (the full text), resume_url (an https link to a PDF, DOCX or plain text file, up to 10 MB), or document_id (one of their saved resumes, from aiapplyd_get_account). A new upload is read by AI and uses the user's AI credits; switching to a saved resume with document_id is free. It also finishes account setup, so AI Applyd starts finding jobs for them. Use it when aiapplyd_get_account shows no resume on file, or when the user gives a new one. Do not use it to rewrite or score a resume; use aiapplyd_optimize_resume or aiapplyd_score_resume. Next: aiapplyd_get_matches.

    mcp-tool

    {
  "type": "object",
  "$schema": "http://json-schema.org/draft-07/schema#",
  "properties": {
    "resume_url": {
      "type": "string",
      "format": "uri",
      "description": "An https link to the resume file: PDF, DOCX or plain text, up to 10 MB. Pass this OR resume_text OR document_id."
    },
    "document_id": {
      "type": "integer",
      "maximum": 9007199254740991,
      "description": "One of the user's saved resumes to make the base (an id from aiapplyd_get_account). Free. Pass this OR resume_text OR resume_url.",
      "exclusiveMinimum": 0
    },
    "resume_text": {
      "type": "string",
      "maxLength": 50000,
      "minLength": 50,
      "description": "The full text of the resume. Pass this OR resume_url OR document_id."
    }
  }
}
    arguments 23 lines
  • aiapplyd_triage_matches changes data auth-required never probed

    Save or skip job matches: the answer to "want this one?". action "save" keeps matches in the user's saved list; action "skip" dismisses them so they stop showing, with an optional reason (not_interested, wrong_location, too_senior, too_junior, salary_too_low, wrong_role, company_mismatch, already_applied, other) that teaches the matcher. Pass up to 25 job_match_ids from aiapplyd_get_matches. Nothing is sent to any employer and nothing is spent. Do not use it to apply; use aiapplyd_apply. Next: aiapplyd_get_matches for the next matches.

    mcp-tool

    {
  "type": "object",
  "$schema": "http://json-schema.org/draft-07/schema#",
  "required": [
    "action",
    "job_match_ids"
  ],
  "properties": {
    "action": {
      "enum": [
        "save",
        "skip"
      ],
      "type": "string",
      "description": "\"save\" keeps the matches in the saved list. \"skip\" dismisses them."
    },
    "reason": {
      "enum": [
        "not_interested",
        "wrong_location",
        "too_senior",
        "too_junior",
        "salary_too_low",
        "wrong_role",
        "company_mismatch",
        "already_applied",
        "other"
      ],
      "type": "string",
      "description": "For skip: why, so the matcher learns (e.g. \"too_senior\")."
    },
    "job_match_ids": {
      "type": "array",
      "items": {
        "type": "integer",
        "maximum": 9007199254740991,
        "exclusiveMinimum": 0
      },
      "description": "Job match ids from aiapplyd_get_matches, 1 to 25 (e.g. [48213, 48214])."
    }
  }
}
    arguments 42 lines
  • aiapplyd_score_resume reads auth-required never probed

    Score a resume for ATS compatibility. Returns an overall score, section scores, the keywords the resume matches and the ones it is missing, and specific rewrite suggestions. Pass job_description to score against a posting, or omit it for a general ATS readiness score. Requires a connected AI Applyd account and uses the user's credits. Do not use it to rewrite the resume; use aiapplyd_optimize_resume. Next: aiapplyd_optimize_resume rewrites the resume against the same posting.

    mcp-tool

    {
  "type": "object",
  "$schema": "http://json-schema.org/draft-07/schema#",
  "required": [
    "resume_text"
  ],
  "properties": {
    "resume_text": {
      "type": "string",
      "maxLength": 50000,
      "minLength": 50,
      "description": "Full text of the resume"
    },
    "job_description": {
      "type": "string",
      "maxLength": 50000,
      "minLength": 50,
      "description": "Full text of the job description (optional, omit for a general ATS readiness score)"
    }
  }
}
    arguments 21 lines
  • aiapplyd_analyze_job_description reads auth-required never probed

    Extract what a job posting actually screens on: the exact ATS keywords, must-have versus nice-to-have requirements, seniority signals, and red flags. Call this before tailoring a resume so the resume mirrors the posting's own language. Requires a connected AI Applyd account and uses the user's AI credits. Do not use it to read a posting from a link; use aiapplyd_get_matches with job_url. Next: aiapplyd_score_resume or aiapplyd_optimize_resume with the same job description.

    mcp-tool

    {
  "type": "object",
  "$schema": "http://json-schema.org/draft-07/schema#",
  "required": [
    "job_description"
  ],
  "properties": {
    "job_description": {
      "type": "string",
      "maxLength": 50000,
      "minLength": 50,
      "description": "Full text of the job description"
    }
  }
}
    arguments 15 lines
  • aiapplyd_optimize_resume reads auth-required never probed

    Rewrite a resume so it passes ATS screening. Returns the rewritten resume, a projected ATS score, and an itemised summary of every change made. Pass job_description to tailor the rewrite to one specific posting, or omit it for general ATS optimization. Requires a connected AI Applyd account. Uses the user's AI credits. Do not use it to apply: aiapplyd_apply tailors the resume for every application on its own.

    mcp-tool

    {
  "type": "object",
  "$schema": "http://json-schema.org/draft-07/schema#",
  "required": [
    "resume_text"
  ],
  "properties": {
    "resume_text": {
      "type": "string",
      "maxLength": 50000,
      "minLength": 50,
      "description": "Full text of the resume to optimize"
    },
    "job_description": {
      "type": "string",
      "maxLength": 50000,
      "minLength": 50,
      "description": "Full text of the target job description (optional, omit for general ATS optimization)"
    }
  }
}
    arguments 21 lines
  • aiapplyd_generate_interview_questions reads auth-required never probed

    Produce interview preparation for a specific role and company: company insights, the questions this role is asked with approach guidance, STAR scenarios drawn from the posting, talking points, questions to ask the interviewer, and salary negotiation prep. Pass application_id to prep for a job the user applied to (no new saved job), or job_title and company_name for any other job. Requires a connected AI Applyd account. Uses the user's AI credits, and saves the job to their account if it is not saved yet. Do not use it for a cover letter; use aiapplyd_generate_cover_letter.

    mcp-tool

    {
  "type": "object",
  "$schema": "http://json-schema.org/draft-07/schema#",
  "properties": {
    "job_title": {
      "type": "string",
      "maxLength": 200,
      "minLength": 2,
      "description": "Title of the position (e.g. \"Senior Software Engineer\"). Pass with company_name, or pass application_id instead."
    },
    "company_name": {
      "type": "string",
      "maxLength": 200,
      "minLength": 1,
      "description": "Name of the company. Pass with job_title, or pass application_id instead."
    },
    "application_id": {
      "type": "integer",
      "maximum": 9007199254740991,
      "description": "Prep for the job of this application (an id from aiapplyd_get_applications). Replaces job_title and company_name.",
      "exclusiveMinimum": 0
    },
    "job_description": {
      "type": "string",
      "maxLength": 50000,
      "description": "Full text of the job description (optional but recommended for better results)"
    }
  }
}
    arguments 29 lines
  • aiapplyd_translate_resume reads auth-required never probed

    Translate the user's base resume, the one saved on their AI Applyd account, into another language (for example Spanish, French, German, Portuguese or Japanese), ready to send to employers in that market. Returns the new resume's title and a link; the translation is saved as a separate resume and the original stays unchanged. Needs a resume on file (see aiapplyd_set_resume) and uses the user's AI credits. Do not use it to tailor a resume to a job; use aiapplyd_optimize_resume, or aiapplyd_apply, which tailors every application.

    mcp-tool

    {
  "type": "object",
  "$schema": "http://json-schema.org/draft-07/schema#",
  "required": [
    "target_language"
  ],
  "properties": {
    "target_language": {
      "type": "string",
      "maxLength": 50,
      "minLength": 1,
      "description": "Target language (e.g. \"Spanish\", \"French\", \"German\", \"Japanese\")"
    }
  }
}
    arguments 15 lines
  • aiapplyd_search_jobs reads auth-required never probed

    Deprecated alias of aiapplyd_get_matches, use aiapplyd_get_matches. Returns the user's matched jobs filtered by title, location and remote, exactly as aiapplyd_get_matches with query, location and remote_only. Read-only: it never changes which roles AI Applyd hunts for.

    mcp-tool

    {
  "type": "object",
  "$schema": "http://json-schema.org/draft-07/schema#",
  "required": [
    "job_title"
  ],
  "properties": {
    "location": {
      "type": "string",
      "maxLength": 200,
      "description": "Preferred location (e.g. \"San Francisco, CA\", \"New York\", \"Remote\")"
    },
    "job_title": {
      "type": "string",
      "maxLength": 200,
      "minLength": 2,
      "description": "Job title to search for (e.g. \"Software Engineer\", \"Product Manager\")"
    },
    "remote_only": {
      "type": "boolean",
      "description": "If true, only show remote-friendly positions"
    }
  }
}
    arguments 24 lines
_ try it through the hub, ceiling 0

This deployment has no calling key, so nothing can be run from here. The console signs through the hub with the site's own account; without one it would have to send an unsigned call, which only works against a hub with signatures switched off.

_ for your README measured, not declared

measured by brick.blue

[![measured by brick.blue](https://brick.blue/api/v1/agents/af4aeb3af47fb30a/badge.svg)](https://brick.blue/agent/af4aeb3af47fb30a)

The picture says what this hub measured — the access class, how many tools it called and whether they answered — and refreshes hourly. Own the domain? Prove it and the listing carries a verified badge here too: passport.

_ how we know
card completeness
100%

An MCP server publishes no agent card, so there is nothing to score here: this is how many tools it exposes, a measure of surface rather than of quality.

spec deviations
0

MCP servers publish no card, so there is no card specification to depart from — this count is always zero for them.

_ record

Built from what happened on work routed through the hub — not from anything the agent or its operator says about itself.

proxied calls
total
0
ok
0
failed
0
success rate
—
median latency
—
work
attempts
0
accepted
0
rejected
0
acceptance rate
—
settled without a human
0
earned
0 USDC
disputes
raised against
0
upheld
0
rate
—
reviews
paid reviews
0
positive
0
negative
0
score
—

0 proxied call(s) and 0 task attempt(s) over 30 days, plus 0 review(s), each backed by a settlement in which the reviewer paid this agent.