keywordise

Auto-apply to jobs: matches your CV, tailors a fresh CV per posting, and applies for you.

Should I use this

Quality & Safety

B
Description quality
99%
Schema completeness
61%
Naming quality
96%
Poisoning risk
80%
Permission match
100%
Protocol compliance
100%

Findings (3)

  • HIGHTool poisoning patterns detected
  • MEDIUMTool description contains URL to non-standard domainin create_account
  • LOWTool 'get_sent_cv_pdf' description lacks action verbin get_sent_cv_pdf

Based on automated analysis of tool definitions and protocol compliance.

Context Cost

~6,132Tokens (tool definitions)
~479 BTypical response size
Significant attention impact (4.79% of 128k context)

This is the approximate number of tokens consumed each time the server's tools are loaded into a model's context. Higher counts reduce the attention available for other tasks.

Install

One-Click Install

Add this to your `claude_desktop_config.json` file:

{
  "mcpServers": {
    "keywordise": {
      "url": "https://keywordise.com/mcp"
    }
  }
}

Remote endpoints

https://keywordise.com/mcpstreamable-http

What it can do

Tool inventory

Tools (49)

🟢 Read-only🟡 Write🔴 Delete⚪ Unknown
🟡create_account(email, password, accept_terms)

Register a new Keywordise account from the terminal and receive an API key for it. Requires accept_terms=true: the person accepts the Terms and Privacy Policy (https://keywordise.com/terms) and authorises Keywordise to apply for jobs on their behalf. A confirmation email is sent; applying opens once the address is confirmed. Trial: 7 days and 27 applications, then $49/month.

Input Schema

{
  "type": "object",
  "properties": {
    "email": {
      "type": "string",
      "format": "email"
    },
    "password": {
      "type": "string",
      "minLength": 8,
      "maxLength": 256
    },
    "accept_terms": {
      "type": "boolean"
    }
  },
  "required": [
    "email",
    "password",
    "accept_terms"
  ],
  "additionalProperties": false
}
⚪login(email, password, label)

Exchange the account's email and password for a new API key, so a terminal or an assistant can act on the account. The key is shown once; keep it. Up to five keys may be active per account (revoke_api_key frees a slot).

Input Schema

{
  "type": "object",
  "properties": {
    "email": {
      "type": "string",
      "format": "email"
    },
    "password": {
      "type": "string",
      "maxLength": 256
    },
    "label": {
      "type": "string",
      "maxLength": 60,
      "description": "A name for this key, e.g. the machine it lives on."
    }
  },
  "required": [
    "email",
    "password"
  ],
  "additionalProperties": false
}
🟢get_account

The account behind this key: email and whether it is confirmed, plan state (trial days left, applications used and remaining, subscription), and how many API keys are active.

Input Schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}
🟡resend_verification_email

Send the email-confirmation link again to this account's address. Applying is blocked until the address is confirmed; nothing else is.

Input Schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}
🟢get_upgrade_link

A checkout link for the Pro plan ($49/month, 200 applications a month) from the active payment provider. The person opens it in a browser to pay; the account upgrades automatically when the payment lands.

Input Schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}
🟢get_billing_portal_link

A link to the payment provider's customer portal for this account's subscription, where invoices, the payment method and cancellation live.

Input Schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}
🔴cancel_subscription

Cancel the Pro subscription at the end of the current billing period. Access stays until then. Irreversible from here; the person can resubscribe later.

Input Schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}
🟢list_api_keys

The active API keys on this account: prefix, label, created and last used. Never the key itself.

Input Schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}
🟡create_api_key(label)

Mint an additional API key for this account, for another machine or assistant. Shown once. Five active keys maximum.

Input Schema

{
  "type": "object",
  "properties": {
    "label": {
      "type": "string",
      "maxLength": 60
    }
  },
  "additionalProperties": false
}
🔴revoke_api_key(key_id)

Revoke one of this account's API keys immediately. Any terminal or assistant using it stops working at once. Revoking the key you are calling with ends this session.

Input Schema

{
  "type": "object",
  "properties": {
    "key_id": {
      "type": "string",
      "description": "From list_api_keys."
    }
  },
  "required": [
    "key_id"
  ],
  "additionalProperties": false
}
🟢export_my_data

The account's complete data as one JSON file (profile, targeting, matched jobs, applications, saved answers, run history, audit trail). Returned as a file; large accounts are told to download it in the app instead.

Input Schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}
🔴delete_my_account(confirm_email)

Erase the account and everything in it: profile, CV files, matches, applications, answers, keys. Irreversible. Requires confirm_email equal to the account's address.

Input Schema

{
  "type": "object",
  "properties": {
    "confirm_email": {
      "type": "string",
      "format": "email"
    }
  },
  "required": [
    "confirm_email"
  ],
  "additionalProperties": false
}
🟢get_my_profile

Use when the person asks what is on their profile or CV. Not needed before searching or applying: those tools read the saved CV themselves. The CV profile Keywordise holds for this account (name, contact, summary, skills, roles, education), the job-targeting rules (countries, remote preference, keywords) and the plan status (applications remaining). Call this first.

Input Schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}
🟡upload_cv(filename, content_base64, save)

Use when the person shares or mentions their resume/CV ('here's my resume', 'use my CV'). Upload a CV file and turn it into the account's profile: the same parser the app uses reads the document into name, contact, summary, roles, skills, languages and education. With save=true (default) the profile is saved and the job feed is built from it; with save=false the parsed profile is returned for review only. Max 8 MB.

Input Schema

{
  "type": "object",
  "properties": {
    "filename": {
      "type": "string",
      "maxLength": 120,
      "description": "e.g. cv.pdf"
    },
    "content_base64": {
      "type": "string",
      "description": "The file's bytes, base64-encoded."
    },
    "save": {
      "type": "boolean",
      "default": true
    }
  },
  "required": [
    "filename",
    "content_base64"
  ],
  "additionalProperties": false
}
🟡update_profile(patch)

Change fields of the saved profile without re-uploading the CV. Send only the fields to change (full_name, contact_email, phone, location, city, address, postcode, professional_summary, skills, pinned_skills, languages, experience, education, projects, certifications, links, …); everything else is untouched. The feed is re-ranked against the new CV.

Input Schema

{
  "type": "object",
  "properties": {
    "patch": {
      "type": "object",
      "description": "Profile fields to change, by name."
    }
  },
  "required": [
    "patch"
  ],
  "additionalProperties": false
}
🟢get_profile_gaps

The gaps in the saved profile that weaken applications (missing dates on a role, no contact phone, empty summary, …), each with a severity, so they can be fixed with update_profile.

Input Schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}
🟢suggest_keywords

Search keywords derived from the saved profile, useful as include_keywords in update_targeting.

Input Schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}
🟢list_cv_designs

The CV designs a tailored CV can be rendered in, with the account's current pick.

Input Schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}
🟡set_cv_design(design)

Set the design every tailored CV is rendered in (a key from list_cv_designs).

Input Schema

{
  "type": "object",
  "properties": {
    "design": {
      "type": "string",
      "maxLength": 40
    }
  },
  "required": [
    "design"
  ],
  "additionalProperties": false
}
🟢get_my_cv_pdf(design)

The account's base CV (the saved profile, untailored) rendered as a PDF in the chosen design, returned as a file. No model call.

Input Schema

{
  "type": "object",
  "properties": {
    "design": {
      "type": "string",
      "maxLength": 40,
      "description": "Optional; defaults to the saved design."
    }
  },
  "additionalProperties": false
}
🟢get_targeting

Every targeting rule the feed and the apply run obey: remote mode, geo scope and countries, locations, include/exclude keywords, title allow/block lists, seniority, salary, languages, work authorisation, company allow/block, daily and per-company caps, cover-letter and CV settings, screening defaults.

Input Schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}
🟡update_targeting(patch)

Change targeting rules; send only the keys to change (remote_mode any|remote|hybrid|onsite, geo_scope worldwide|region|country, geo_countries [ISO-2], locations, include_keywords, exclude_keywords, title_allow, title_block, seniority, salary_min, currency, languages, company_block, max_apps_per_day, max_apps_per_company, cover_letter_enabled, cv_tone, tailor_instructions, years_experience, salary_expectation, notice_period, …). The feed re-matches in the background.

Input Schema

{
  "type": "object",
  "properties": {
    "patch": {
      "type": "object",
      "description": "Targeting fields to change, by name."
    }
  },
  "required": [
    "patch"
  ],
  "additionalProperties": false
}
🟢describe_what_i_want(sentence, preset, apply)

Use when the person says what they are looking for in their own words ('senior remote data roles in the US, no agencies'). Turn a plain sentence ('remote data roles in Germany or the Netherlands, senior, not agencies') plus the saved CV into concrete targeting rules. Returns the inferred rules and the chips a person would confirm; with apply=true they are saved and the feed re-matches. preset: balanced | broad | focused.

Input Schema

{
  "type": "object",
  "properties": {
    "sentence": {
      "type": "string",
      "maxLength": 1000
    },
    "preset": {
      "type": "string",
      "enum": [
        "balanced",
        "broad",
        "focused"
      ],
      "default": "balanced"
    },
    "apply": {
      "type": "boolean",
      "default": false
    }
  },
  "required": [
    "sentence"
  ],
  "additionalProperties": false
}
🟢get_feed_reach

How many jobs the current targeting shows versus how many each single rule is hiding, and which one change would widen the feed most. Every number comes from re-asking the feed's own predicate with one control relaxed.

Input Schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}
🟢list_countries_with_jobs

The countries the live pool actually has inventory in (ISO-2, name, job count), for choosing geo_countries in update_targeting.

Input Schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}
🟢list_matching_jobs(limit, offset, sort, match, fresh, ...)

Use when the person wants jobs or their best matches: 'find me jobs', 'my top matches', 'remote marketing jobs that fit my resume', 'what's new for me this week'. It already uses the saved CV, so there is no need to read the profile first. Live vacancies matched to this account's CV, ranked. Each job carries a calibrated match percentage, a recruiter-pass verdict with a one-line reason, and whether an application was already sent. Filter by match tier and freshness; page with offset.

Input Schema

{
  "type": "object",
  "properties": {
    "limit": {
      "type": "integer",
      "minimum": 1,
      "maximum": 50,
      "default": 10
    },
    "offset": {
      "type": "integer",
      "minimum": 0,
      "default": 0
    },
    "sort": {
      "type": "string",
      "enum": [
        "fit",
        "fresh"
      ],
      "default": "fit",
      "description": "fit = best match first; fresh = newest day first, best match within it."
    },
    "match": {
      "type": "string",
      "enum": [
        "good",
        "strong",
        "all"
      ],
      "default": "good",
      "description": "Match tier. 'all' includes weak matches the recruiter pass rejected."
    },
    "fresh": {
      "type": "string",
      "enum": [
        "new",
        "all"
      ],
      "default": "new",
      "description": "new = posted in the last two weeks; all = the last month."
    },
    "applied": {
      "type": "string",
      "enum": [
        "show",
        "hide"
      ],
      "default": "show",
      "description": "hide = leave out jobs already applied to."
    }
  },
  "additionalProperties": false
}
🟢get_job_posting(job_id)

The full description of one matched vacancy, with a short summary and highlights, plus the link that opens the posting from the app.

Input Schema

{
  "type": "object",
  "properties": {
    "job_id": {
      "type": "string",
      "description": "A job_id from list_matching_jobs or list_my_applications."
    }
  },
  "required": [
    "job_id"
  ],
  "additionalProperties": false
}
🟢explain_job_match(job_id, narrative)

Use for 'is this job a good fit', 'why this match', 'what am I missing for this role'. For one vacancy: the match percentage, the requirements this account's CV covers and the ones it is missing. With narrative=true, also a short written assessment with strengths and gaps (a paid model call; limited to 60 per hour).

Input Schema

{
  "type": "object",
  "properties": {
    "job_id": {
      "type": "string",
      "description": "A job_id from list_matching_jobs or list_my_applications."
    },
    "narrative": {
      "type": "boolean",
      "default": false
    }
  },
  "required": [
    "job_id"
  ],
  "additionalProperties": false
}
🟢preview_tailored_cv(job_id)

Use for 'tailor my resume for this job' or 'what would you send for this one'. Rewrite this account's CV for one vacancy the way Keywordise would send it: headline, summary, the roles selected for this job with rewritten bullets, curated skills and a cover letter, every segment labelled tailored, verbatim or pinned. Nothing is sent. A paid model call, limited to 20 per hour; the same billing gate as applying.

Input Schema

{
  "type": "object",
  "properties": {
    "job_id": {
      "type": "string",
      "description": "A job_id from list_matching_jobs or list_my_applications."
    }
  },
  "required": [
    "job_id"
  ],
  "additionalProperties": false
}
⚪rate_job(job_id, action, reason)

Feedback on one job: hide or dislike removes it from the feed and teaches the matcher what this person rejects; interested is a positive signal. Undo with unhide_job.

Input Schema

{
  "type": "object",
  "properties": {
    "job_id": {
      "type": "string",
      "description": "A job_id from list_matching_jobs or list_my_applications."
    },
    "action": {
      "type": "string",
      "enum": [
        "hide",
        "dislike",
        "interested"
      ]
    },
    "reason": {
      "type": "string",
      "maxLength": 300
    }
  },
  "required": [
    "job_id",
    "action"
  ],
  "additionalProperties": false
}
⚪unhide_job(job_id)

Undo hide or dislike: the job returns to the feed and the negative signal is dropped.

Input Schema

{
  "type": "object",
  "properties": {
    "job_id": {
      "type": "string",
      "description": "A job_id from list_matching_jobs or list_my_applications."
    }
  },
  "required": [
    "job_id"
  ],
  "additionalProperties": false
}
🟢list_hidden_jobs

The jobs this account hid or disliked, newest first, so one can be put back.

Input Schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}
🟢refresh_matches(force, rebuild)

Match the account's CV against the vacancies added since it last looked, in the background. Idempotent and cheap when nothing is new. force=true runs a full re-match regardless. rebuild=true rebuilds the feed from scratch through the same build as the app's Rebuild button (use it when the feed looks wrong). Every answer carries `feed_build`: poll get_match_status until its state is `ready` before reading list_matching_jobs, because a feed that is still building is not an empty feed.

Input Schema

{
  "type": "object",
  "properties": {
    "force": {
      "type": "boolean",
      "default": false
    },
    "rebuild": {
      "type": "boolean",
      "default": false
    }
  },
  "additionalProperties": false
}
🟢get_match_status

Only for checking on a match or feed rebuild that is already running (after upload_cv, update_targeting or refresh_matches); to find or show jobs use list_matching_jobs. Live status of the latest match run (scanned, inserted, elapsed), the feed counts it produced, and `feed_build`: where the feed is in its build (queued, building, ready, failed). Poll after upload_cv, update_targeting or refresh_matches; the feed is final only when feed_build.feed_state.state is `ready`.

Input Schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}
🔴start_apply_run(limit, match, fresh, dry_run, job_id)

Use when the person says 'apply for me', 'apply to the best matches' or 'apply to this job' (pass job_id). Show them the jobs first. Start an application run: Keywordise takes up to `limit` of the matching jobs (same filters as list_matching_jobs, best fit first, never one already applied to), tailors the CV and cover letter for each, answers the employer's screening questions from the saved answers, and SUBMITS inside the employer's own system. Real applications leave in the person's name; needs a confirmed email and an active plan; counts against the plan. dry_run=true does everything except submit. Poll get_apply_run_status.

Input Schema

{
  "type": "object",
  "properties": {
    "limit": {
      "type": "integer",
      "minimum": 1,
      "maximum": 100,
      "default": 10
    },
    "match": {
      "type": "string",
      "enum": [
        "good",
        "strong",
        "all"
      ],
      "description": "Match tier to draw from; defaults to the account's saved filter."
    },
    "fresh": {
      "type": "string",
      "enum": [
        "new",
        "all"
      ],
      "description": "Freshness window; defaults to the account's saved filter."
    },
    "dry_run": {
      "type": "boolean",
      "default": false
    },
    "job_id": {
      "type": "string",
      "description": "Apply to exactly this ONE job (an id from list_matching_jobs) instead of a filtered batch — the same run, scoped to it. limit/match/fresh are ignored when set."
    }
  },
  "additionalProperties": false
}
🟢get_apply_run_status

Live progress of the latest run: running or not (from a heartbeat, not a status claim), processed of total, the job being worked on now, confirmed, needs review, skipped, closed.

Input Schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}
⚪stop_apply_run

Use for 'stop applying', 'pause', 'hold off'. Ask the running application run to stop after the job it is on. Nothing is left half-done; applications already sent stay sent.

Input Schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}
🟢list_my_applications(limit, only_waiting_on_me, include_cover_letter)

Use for 'what did I apply to', 'any replies', 'status of my applications'. Every application sent for this account: company, title, stage, outcome, when it went out, how many screening questions it still waits on, and the employer's acknowledgement where one was received.

Input Schema

{
  "type": "object",
  "properties": {
    "limit": {
      "type": "integer",
      "minimum": 1,
      "maximum": 200,
      "default": 50
    },
    "only_waiting_on_me": {
      "type": "boolean",
      "default": false,
      "description": "Only applications stalled on unanswered screening questions."
    },
    "include_cover_letter": {
      "type": "boolean",
      "default": false
    }
  },
  "additionalProperties": false
}
🟢list_blocking_questions(limit)

Questions employers asked on applications that are stalled until this account answers them, grouped by application, each with a suggested answer drawn from what the person answered before. Answer with answer_screening_question.

Input Schema

{
  "type": "object",
  "properties": {
    "limit": {
      "type": "integer",
      "minimum": 1,
      "maximum": 100,
      "default": 20,
      "description": "Maximum number of applications to expand."
    }
  },
  "additionalProperties": false
}
🔴answer_screening_question(application_id, question_id, answer)

Record the person's answer to one screening question on one application. The answer is written in the person's name and saved to their answer book, so the same question is never asked again. When it is the last required answer, the application is SUBMITTED to the employer. Only give an answer the person actually stated.

Input Schema

{
  "type": "object",
  "properties": {
    "application_id": {
      "type": "string"
    },
    "question_id": {
      "type": "string"
    },
    "answer": {
      "type": "string",
      "maxLength": 5000
    }
  },
  "required": [
    "application_id",
    "question_id",
    "answer"
  ],
  "additionalProperties": false
}
🟢get_sent_cv_pdf(application_id)

The tailored CV PDF that went to the employer for one application, returned as a file.

Input Schema

{
  "type": "object",
  "properties": {
    "application_id": {
      "type": "string"
    }
  },
  "required": [
    "application_id"
  ],
  "additionalProperties": false
}
🟢list_run_history

The last five match runs and the last five application runs, with their counts and status.

Input Schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}
🟢list_saved_answers

The answer book: every screening answer this account has given or taught, which future applications reuse automatically in any phrasing or language.

Input Schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}
🟡save_answer(question, answer, kind, options)

Add or replace a screening answer in the answer book ('What is your notice period?' → '1 month'). Applications already waiting on that fact are completed and sent in the background. Only save what the person actually stated.

Input Schema

{
  "type": "object",
  "properties": {
    "question": {
      "type": "string",
      "maxLength": 500
    },
    "answer": {
      "type": "string",
      "maxLength": 5000
    },
    "kind": {
      "type": "string",
      "enum": [
        "text",
        "boolean",
        "select",
        "number"
      ],
      "default": "text"
    },
    "options": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "For select questions: the choices the form offers."
    }
  },
  "required": [
    "question",
    "answer"
  ],
  "additionalProperties": false
}
🔴delete_saved_answer(answer_id)

Remove one answer from the answer book (an answer_id from list_saved_answers).

Input Schema

{
  "type": "object",
  "properties": {
    "answer_id": {
      "type": "string"
    }
  },
  "required": [
    "answer_id"
  ],
  "additionalProperties": false
}
🟢list_facts_to_provide

The universal screening facts this account has not answered yet (right to work, notice period, salary expectation, …), ranked by how many waiting applications each one unblocks. Answer them with save_answer.

Input Schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}
🟢get_tracker

The tracker board: applications grouped by the stage the person set (saved, applied, interview, offer, rejected) with their own notes.

Input Schema

{
  "type": "object",
  "properties": {},
  "additionalProperties": false
}
🟡move_tracker_card(application_id, stage)

Set the tracker stage of one application: saved, applied, interview, offer or rejected.

Input Schema

{
  "type": "object",
  "properties": {
    "application_id": {
      "type": "string"
    },
    "stage": {
      "type": "string",
      "enum": [
        "saved",
        "applied",
        "interview",
        "offer",
        "rejected"
      ]
    }
  },
  "required": [
    "application_id",
    "stage"
  ],
  "additionalProperties": false
}
🟡set_tracker_note(application_id, notes)

Replace the person's own note on one tracked application (interview date, contact, next step).

Input Schema

{
  "type": "object",
  "properties": {
    "application_id": {
      "type": "string"
    },
    "notes": {
      "type": "string",
      "maxLength": 2000
    }
  },
  "required": [
    "application_id",
    "notes"
  ],
  "additionalProperties": false
}

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