ApplyWise

io.github.tanmayagrawal21由 GitHub 账号 tanmayagrawal21 发布v0.1.0更新于 Oct 30, 2026

Job search and form filling; dry run by default, real submits need your approval or consent.

概览

AI 生成的概览

本地 MCP 服务器:搜索招聘网站、规划并填写求职申请,仅在用户批准或开启同意窗口后才真正提交。

可以做什么
  • 搜索与查看职位:并行搜索多个招聘平台并分页,查看搜索进度、单条职位详情与申请表结构
  • 规划与起草申请:策略与重复检查、按个人档案填充答案、起草文字内容、批量规划
  • 提交与跟踪:受控提交、验证码录入、批量申请、运行报告、申请记录与反馈
  • 档案与溯源:按优先级列出待补档案问题(仅由用户作答)、文本溯源记录与核验
  • 安全与状态:控制层检查与状态、同意与授权状态、凭据保险库状态、健康检查
  • 邮件去重:导入或同步确认邮件,并与未决提交进行核对
适用场景
适合希望让助手在 Greenhouse、Lever、Ashby、SmartRecruiters、Workday 等平台搜索职位、依据个人档案准备申请,并保持默认演练、真正发送前需人工批准的流程的用户。
运行要求
以本地 stdio 进程运行,通过 uvx 启动(需 uv 或 pipx),支持 macOS、Linux 与 Windows。需先运行 init 和 doctor 生成配置、档案与控制文件。可选扩展提供 Playwright 浏览器自动化、本地或云端 LLM 以及钥匙串存储。清单未声明任何环境变量或请求头。
安装前请注意
处于 Alpha 阶段,README 说明尚未有申请在无人值守下成功提交。真实提交不可撤销,可能创建账号并向雇主网站发送数据,建议保持 dry_run 开启并核对批准令牌。同意窗口会自动批准提交并可能读取邮件验证码。凭据存放于操作系统钥匙串,不会暴露给模型。确认邮件同步以只读方式访问邮箱。

安装

在 SourceWeft 中

  1. 打开 控制台中的 ApplyWise,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

README

job-apply-mcp (ApplyWise)

An MCP server that finds jobs and fills applications for you, and stops before anything irreversible. It is modular (pluggable platforms, LLM providers, browser drivers), parallel, token-frugal (compact, paginated output) and local-first (routine form fields go to Ollama, LM Studio or MLX on your machine; only hard prose escalates). Works with any MCP client on macOS, Linux and Windows.

[!WARNING] Alpha. Field results from the first live dogfooding run (one user, one night, ~330 discovered postings): search, ranking, dedupe and planning work end to end, and the browser driver now fills and verifies complete Greenhouse and Lever forms, but no application has yet been submitted unattended. Most Greenhouse boards are reCAPTCHA-protected, so the tool fills the form and hands the final click to you (handoff), which is the intended behaviour. Free-text questions need writing.reviewer = "router" (local strict review) to go out without you. Expect rough edges; every irreversible step is gated, logged and never retried when the outcome is uncertain.

Install as a Claude Code plugin

The repository is also a Claude Code plugin marketplace. The applywise plugin starts the MCP server for you (pinned to a reviewed version) and adds a skill that tells Claude how to use the tools safely:

bash
claude plugin marketplace add tanmayagrawal21/job-apply-mcpclaude plugin install applywise@applywise

Then run init and doctor from the quickstart below in your own terminal, and check /mcp for plugin:applywise:applywise. The same safety model applies: dry run by default, a human approves every real submit, and visible CAPTCHAs always come back to you; logins, codes and account creation stay with you unless you open a consent window yourself (safety model, items 7 and 8). To update, run claude plugin update applywise@applywise. How releases and the version pin work: docs/release.md.

5-minute quickstart

You need uv (or pipx). No clone required.

bash
# 1. Create config.toml, profile.toml, controls.toml (asks a few questions; --yes to skip them)uvx --from git+https://github.com/tanmayagrawal21/job-apply-mcp job-apply-mcp init
# 2. Put your real details in the profile it printed the path of, then check everythinguvx --from git+https://github.com/tanmayagrawal21/job-apply-mcp job-apply-mcp doctor
# 3. Add the printed snippet to your MCP client (guides for ten clients: docs/clients/)claude mcp add --transport stdio job-apply -- uvx --from git+https://github.com/tanmayagrawal21/job-apply-mcp job-apply-mcp

Then ask your assistant: "search jobs at greenhouse:examplecorp for data roles, plan the best one, and do a dry run." Everything is a dry run until you set dry_run = false.

Install alternatives: pipx install git+https://github.com/tanmayagrawal21/job-apply-mcp (then the command is just job-apply-mcp), or pip install into a virtualenv. After the first PyPI release, uvx applywise (the PyPI distribution is applywise; the job-apply-mcp command stays as an alias). Optional extras: [browser] (Playwright), [agent], [jobspy], [mlx], [hf], [litellm], [keyring].

Features

AreaWhat you get
DiscoveryParallel search over Greenhouse, Lever, Ashby, SmartRecruiters, Workday and JobSpy boards, paginated
Policy gatesSkip by sponsorship, citizenship, clearance, experience, graduation window, salary floor, employer patterns
Runsrun_applications / job-apply-mcp run: links you pass, job links you emailed yourself (read-only mail) and discovery in one run, a run report and feedback applied to the next run
ApplyingPlatform API where possible, browser driver otherwise, generic LLM-assisted adapter for other sites
Local LLM routingComplexity-scored tiers (small/medium/large/narrative), fallbacks, optional cloud, your MCP client as last resort
Profile builderCollects the questions your profile could not answer, ranks them, and asks you (profile_questions, answer_profile_question, job-apply-mcp profile ask); the model never supplies an answer
AuthorizationPer-country facts ([authorization] for your home_country, [authorization.<CC>] for others); no default country, and unknown countries stay unresolved
WritingCover letters and answers with style rules, banned phrases and gap-avoidance checks
ProvenanceEvery generated text is recorded and can be verified or edited by you
DedupeStore of applications plus optional confirmation-email ingest so you never apply twice
Control layerQuotas, mode switch, attestation and recipient guards, prose lint, prompt-injection screen
Transportsstdio (default) and streamable HTTP with bearer token
Operationsinit, doctor, Dockerfile, CI on Linux/macOS/Windows

Run statuses

Every posting in a run_applications / run_report result has exactly one status, with a why where useful (ADR-0049):

StatusMeaning
submittedLive submit sent; a confirmation may follow
confirmedReconciliation confirmed the submission
dry_run_okDry run complete: a live run would submit it (see live_preview for quotas; the row's captcha mode says whether a captcha would stop it: docs/tools.md)
needs_humanYou must act; why says what (unresolved fields, review gate, awaiting approval, verification code)
quota_blockedA daily, per-platform or per-run quota refused the live submit; nothing was sent
skippedNot attempted; why says why (policy, duplicate, prose not approved yet, max_applications reached)
unsupported_siteNo enabled adapter handles the host
unknownOutcome unclear (for example a roadblock after the click); verify by hand
failedAn error

max_applications (a whole number >= 1) caps the eligible postings a run handles (ready to submit, or needing you), the same in dry and live mode; skipped and unsupported postings do not count. A dry run also returns live_preview with what the current live quotas would allow. Live submits also count against the daily (25 per rolling 24 h), per-platform (10) and per-run (10) limits; a user config can lower or raise them.

Safety model

  1. Dry-run by default. dry_run = true unless you change it; init always writes it.
  2. Approval tokens. plan_application returns a token bound to a hash of the exact answers. A real submit needs that token, so what you reviewed is what is sent (apply.auto_approve turns this off; do not).
  3. Control layer. Independent checks run before every side effect: daily and per-run quotas, single-submit guard, recipient deny-list, prose lint, page-text injection screen, apply_enabled kill switch. Add your own rules in controls.toml.
  4. Hard stops. Visible CAPTCHA challenges and attestation checkboxes matching policy.stop_phrases (for example "no AI used") always return needs_human. They are not configurable away. Verification codes are entered only when the USER types them, confirms a granted prefill (ADR-0026/0027), or consented to unattended runs from a terminal (item 8). Account creation is off by default; it needs accounts.auto_create = true in your own user config file AND an open credentials consent window (ADR-0046).
  5. No invented facts. Answers come from your profile or are marked; unresolved required fields stop the run. Autonomy level (ADR-0052). [answers] autonomy in your own user config decides what the agent may assume when you are not available: strict (default: every unresolved field waits for you), safe_default (decline contact/marketing permission, the configured "how did you hear" default, "decline to self-identify"), or infer (also skill/experience questions about a tool or technology, answered from your resume: Yes only when it clearly says so, otherwise No; willingness, availability, location and terms questions are never inferred). Authorization/visa/identity, background and other screening, accommodation, recording, attestations, legal agreements and employment terms, salary without a policy, start date and location facts are never assumed. Every assumed answer is labelled (assumed, plan, evidence, run report); after promote_after (3) assumptions of one question you are asked once and your answer is reused. A project file or env var can only make the level stricter. init asks which level to use; control_status shows it.
  6. Privacy. Profile and secrets stay on your machine, are never committed, and API keys are read only from the environment. See SECURITY.md.
  7. Credentials never reach the model. ATS logins live in the OS keychain (job-apply-mcp vault add <host> --username U, password prompted without echo). The browser fills them straight into the page; MCP exposes only vault_status (hosts, never secrets). At most 2 sign-in attempts per host per run; a lockout or wrong password stops that host (ADR-0046).
  8. Consent window (optional, ADR-0048). job-apply-mcp consent --for 24h (or --per-run, --max N, --scopes ...) is typed once, in a terminal, per period you choose. Inside the window submissions are approved automatically (logged with the consent id), a page whose only bot check is an invisible widget is submitted with one click, and an emailed code is read from the newest message of the expected sender and entered once. Unattended codes stay off until verification.trusted_authserv_ids lists your own mail server's Authentication-Results id (user config only), so a spoofed sender cannot supply a code. You review the results afterwards (list_applications). consent --revoke ends it; consent_status (MCP) is read-only and no tool can create one.
  9. Owner-only questions (ADR-0050). Contact, messaging and marketing permissions (SMS, WhatsApp, calls, email, job alerts, talent community) are never answered Yes; only your own optin:<channel> answer applies, and only to a single, plain permission question. Otherwise they stay with you, or are declined (labelled assumed) at answers.autonomy = "safe_default" or "infer" (item 5). Authorization and sponsorship come only from structured per-country facts.
  10. You make the final click (optional, ADR-0058). Set [browser] final_click = "human" with headless = false. The agent fills and verifies each form, brings the tab to the front, and never clicks Submit. You click. A watcher reads the page every 3 s, for up to human_click_timeout_s (900 s by default), and records the submission once the site shows its success page. run_applications then hands you one filled tab at a time. The setting only tightens: any config layer can set human, and only your own user config can switch it back to agent.

Known limitation: Ashby with reCAPTCHA Enterprise. Ashby forms protected by reCAPTCHA Enterprise silently reject or challenge automated submit clicks, even when the widget is invisible. Use final_click = "human" for these postings.

Transports

bash
job-apply-mcp                                                  # stdio (what clients launch)job-apply-mcp --transport http --host 127.0.0.1 --port 8765   # http://127.0.0.1:8765/mcpJOB_APPLY_MCP_TOKEN=... job-apply-mcp --transport http --host 0.0.0.0   # non-local: token required

HTTP binds loopback by default; any other address refuses to start without JOB_APPLY_MCP_TOKEN (Authorization: Bearer ...). Use a TLS reverse proxy for network access. A Dockerfile is included (no browser by default; --build-arg BROWSER=1 adds Playwright and Chromium).

Documentation

Development

bash
git clone https://github.com/tanmayagrawal21/job-apply-mcp && cd job-apply-mcpuv sync --extra devuv run ruff check . && uv run pytest -q      # offline; live tests need JAM_LIVE=1uv run python scripts/gen_config_docs.py     # after changing config.py

Privacy scan: python scripts/privacy_scan.py --terms ~/.config/job-apply-mcp/privacy_terms.txt. Owner-accepted findings go in ~/.config/job-apply-mcp/privacy_allow.txt (outside the repo, --allow FILE); see ADR-0051. The committed .privacy-allow holds only fully anchored regexes for fictional fixtures and the public project identity in manifests (ADR-0042); never add private terms or fingerprints to it.

MIT licensed. Contributions welcome under the Code of Conduct.

来源:README.md,提交 8e98ff2

工具

33

search_jobs

Search postings across enabled platforms in parallel. Returns compact rows: ref, co, title, loc, pay, flags. The first call runs the whole search once; pass the returned `next` as `cursor` for more pages (instant).

输入参数limitqueryboardscursorlocationplatformssince_daysapply_policy

search_status

Progress of a search_jobs session: status, boards done/total, rows, elapsed. Accepts a session id or cursor.

输入参数session_id必填

get_job

Fetch one posting. Add 'description' to fields to include the (trimmed) description.

输入参数fieldsref_or_url必填

get_form

Return the application form schema (keys, labels, kinds, required, options).

输入参数ref_or_url必填

plan_application

Run policy gates + duplicate check, fill answers from the profile and local LLMs, and list unresolved fields. Unresolved free-text fields come back as `client_tasks` for the calling agent to write. `src` names the source of every answer that is not "profile". A result too large for one response is paged: it carries `next` and `total`; call again with `cursor=next` to get the next page of the SAME plan (from memory, no re-plan) until `next` is null. Pages keep the shape (answers/src stay dicts) so they merge. The first call of a session may ask the user the top open profile questions (elicitation) before planning.

输入参数cursorref_or_url必填

draft_answers

Draft the prose fields a plan left open (writing.mode="deferred", or ones that timed out): local writer + reviewer under writing.timeout_s. Returns the same shape as plan_application with a fresh approval_id, paged the same way (`cursor=next` pages the last draft from memory).

输入参数cursorref_or_url必填

submit_application

Submit using the best available path (platform API, else browser driver). Honors global dry_run; a per-call dry_run can only make it safer. `approval_id` is the server-issued id from plan_application. With approval_mode=human a person must approve (dialog, or `job-apply-mcp approve <id>`).

输入参数tokenanswersdry_runref_or_url必填approval_id

provide_verification_code

The user types the code they received (email/SMS) for a submission in status `awaiting_code`. Ask the USER; never try to read their mail or guess. Only the format is checked; the code is typed into the open page, the page's verify button is clicked once, then the normal confirmation check runs. One attempt per code; the application is never resubmitted; after `verification.code_ttl_s` it becomes a `handoff`.

输入参数code必填pending_id必填

apply_batch

Plan + submit many applications concurrently. Returns one compact status row per ref. Open profile questions are asked once, before the batch starts (never mid-batch).

输入参数refs必填dry_runmax_parallel

list_applications

List recorded applications from the local store.

输入参数limitcursorstatus

request_feature

Propose (and, if a coder backend is configured, implement as a PR for human review) a change to this tool. kind: platform_adapter | control | config | new_tool | bug (auto-detected if omitted).

输入参数kinddescription必填

improvement_report

Ranked improvement proposals learned from recent run failures (compact). Page with `cursor` (= `next`).

输入参数limitcursor

record_text

Record provenance for a text artifact (kind: resume_bullet|cover_letter|answer|profile_fact). origin: user_written | llm_generated (llm_generated needs `model`). `context` = job/question the text answers.

输入参数kind必填text必填modelorigin必填parentpromptcontext

verify_text

User approves LLM text. Without edited_text -> user_verified; with it -> user_edited child plus diff.

输入参数id必填edited_textverified_by

provenance

Origin, model, prompt hash and ancestor chain for a text id.

输入参数id必填include_text

health

Report enabled platforms, LLM providers and which local models are reachable.

无需输入参数。

control_check

Check a side-effecting action against the control layer. action: apply|submit|send_message| write_prose|merge. payload: ref, platform, company, dry_run, text, recipient, page_text, form_labels, attestations. Returns {decision: pass|block|needs_human, violations, warnings}.

输入参数action必填payload

control_status

Active mode, quotas used/remaining, enabled controls and recent blocks.

无需输入参数。

tune_status

Local style-tuning state: backend, promoted/previous adapter, new user texts vs threshold, last run.

无需输入参数。

tune_run

Train a LoRA on the user's own texts, gate it against the incumbent, promote only if better. trigger: manual | new_data (skips below the configured threshold) | rollback (restore previous adapter). wait=False starts in the background; poll tune_status.

输入参数waittrigger

facts_report

Resume-first fact precedence: counts, profile/resume conflicts, and user-letter facts excluded because they conflict with or are outdated relative to the resume (with the reason and the resume's version).

无需输入参数。

grants_status

Active human-issued grants (scope, seconds left, uses left). Read-only: only a human can create or revoke a grant, via `job-apply-mcp grant` in a terminal.

无需输入参数。

vault_status

Which ATS hosts have a stored login (host and count only, never a username's password), whether the credentials consent window is open, accounts awaiting email verification, and this run's login flags (lockout, wrong_password, captcha). Read-only: logins are added by a human with `job-apply-mcp vault add`.

无需输入参数。

ingest_confirmations

Record the user's own application-confirmation emails so those jobs are never re-applied to. Pass message summaries from the user's mail tool: [{sender, subject, date, snippet}] (snippet = first ~500 chars, optional). Read-only on mail; the server stores only company, title and date. Returns counts plus up to a few new matches. preview=true parses without writing.

输入参数previewmessages必填

sync_confirmations

Pull confirmation emails from the configured read-only source (ingest.source: mbox or imap) for the last `since_days` days and record them as already applied. Never sends, moves, flags or deletes mail.

输入参数sourcepreviewsince_days

reconcile_submissions

Match open submissions (submitted/unknown/submitting/handoff) to confirmation emails and mark confident matches `confirmed` (evidence = email subject/date; never bodies). Checks run at ingest.reconcile_delays_min after each submit; force=true checks now. With the default client mail source and no `messages`, returns a `client_task`: fetch recent confirmation-email summaries and pass them here or to ingest_confirmations. An unknown with no match after the last window stays unknown and is listed under `unresolved`. Read-only on mail; never resubmits.

输入参数forcemessages

seed_from_confirmations

Seed dedupe from confirmation-email history (default ingest.seed_since_days=180) before a run, so no side files are needed. mbox/imap sources are read directly; with the client source and no `messages` this returns a `client_task` to fetch summaries and call it again with them.

输入参数previewmessagessince_days

run_applications

Apply from any mix of sources in one run: explicit `links` (or `links_file`, one URL per line), job links the user emailed to themselves (read-only mail; sender, recipient and label come from config only; `mail` may only narrow with {query, since, since_days}), and discovery (`discovery` = search_jobs arguments). Priority: links, then mail, then discovery. `sources` subsets ["links","mail","discovery"]. `max_applications` (whole number >= 1; default intake.max_applications or run_size feedback, capped at intake.max_applications_cap) caps the eligible postings handled, the same in dry and live mode; skipped and ineligible ones do not count. Every URL goes through adapter detection, plan, gates, dedupe and submit. Prose is deferred: jobs needing unapproved prose are skipped, not blocking. With the client mail source pass `messages` [{id, from, to, subject, date, body}]. Pending feedback is applied first (see plan_context). Returns the run report: one status per posting, each with `why`: submitted, confirmed, dry_run_ok (a live run would submit it), needs_human (the owner must act: unresolved fields, review gate, awaiting approval), quota_blocked (a live quota refused it), skipped (policy, duplicate, prose not approved, max_applications reached), unsupported_site, unknown (verify by hand), failed. A dry run adds `live_preview` (would_submit, quota_blocked, warning) from the live quotas.

输入参数maillinksdry_runsourcesmessagesdiscoverylinks_filemax_applications

run_report

Report of a run (default: the latest): counts plus rows per status (submitted, confirmed, dry_run_ok, needs_human, quota_blocked, skipped, unsupported_site, unknown, failed; see run_applications), each with `why`. `category` shows one only (the old names handed_off and dry_run still work).

输入参数limitrun_idcategory

give_feedback

Feedback on a run (optionally on one `ref` of it), applied at the start of the next run. Structured: {"kind":"deny_company"|"deny_title", "pattern"?} (no pattern + ref = that item's company/title), {"kind":"answer","pattern","value"} for plain questions only; any authorization, demographic, consent, attestation, legal or AI-use question (or {"kind":"profile_answer","key"|"question","value","scope": "global|company|role_family","scope_value"}) goes to the profile builder's answer_profile_question. {"kind":"salary","salary_floor"|"base_salary"|"default_ask"|"expected"|"delta"|"percent"}: never below the configured floor, capped at intake.salary_max_multiple. {"kind":"run_size","value"|"delta"}. Free text is shown in the next run's plan_context. Answers given here (and pay changes in human approval mode) apply only after the USER confirms them on a terminal: `job-apply-mcp feedback --confirm <id>`.

输入参数refrun_id必填feedback必填

profile_questions

Top open profile gaps (questions the tool could not answer, or answered with a default), ranked by frequency x impact (blocked applications weigh most). Ask the user these, then call answer_profile_question.

输入参数limit

answer_profile_question

Ask the USER (MCP elicitation) to type the answer for a gap key from profile_questions. This tool takes no value: the answer comes only from the user's own input and is stored as user_written. If the client cannot elicit, nothing is stored; tell the user to run `job-apply-mcp profile ask`. Scope: global | company | role_family (+ scope_value, or 'company:Acme'). Demographics are never stored here.

输入参数key必填scopescope_value

版本历史

1
  1. v0.1.0最新Oct 23, 2026

评分

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