原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

grad-agent

作者:i-ninte版本 0.2.9i★ –i在你的电脑上运行
注册名称io.github.i-ninte/grad-agent

安装

概览

作者提供的说明(英文原文)

Autonomous MCP agent for grad school applications: prof discovery, cold emails, SOP, tracking.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 其他
  • 你需要填写:ANTHROPIC_API_KEY, SMTP_SERVER, SMTP_PORT, SMTP_USERNAME, SMTP_PASSWORD, SMTP_FROM, GITHUB_TOKEN, HF_TOKEN

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 需要你自己填写: ANTHROPIC_API_KEY, SMTP_SERVER, SMTP_PORT, SMTP_USERNAME, SMTP_PASSWORD, SMTP_FROM, GITHUB_TOKEN, HF_TOKEN, GRAD_AGENT_HOME, LOR_LETTERHEAD_PATH, LOR_LETTERHEAD_WIDTH

标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。

你需要

  • PyPI已安装 Python 的 uv(用于 uvx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "grad-agent": {
      "command": "uvx",
      "args": [
        "grad-agent"
      ],
      "env": {
        "ANTHROPIC_API_KEY": "your-value",
        "SMTP_SERVER": "your-value",
        "SMTP_PORT": "your-value",
        "SMTP_USERNAME": "your-value",
        "SMTP_PASSWORD": "your-value",
        "SMTP_FROM": "your-value",
        "GITHUB_TOKEN": "your-value",
        "HF_TOKEN": "your-value",
        "GRAD_AGENT_HOME": "your-value",
        "LOR_LETTERHEAD_PATH": "your-value",
        "LOR_LETTERHEAD_WIDTH": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add grad-agent --env ANTHROPIC_API_KEY=your-value --env SMTP_SERVER=your-value --env SMTP_PORT=your-value --env SMTP_USERNAME=your-value --env SMTP_PASSWORD=your-value --env SMTP_FROM=your-value --env GITHUB_TOKEN=your-value --env HF_TOKEN=your-value --env GRAD_AGENT_HOME=your-value --env LOR_LETTERHEAD_PATH=your-value --env LOR_LETTERHEAD_WIDTH=your-value -- uvx grad-agent

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "grad-agent": {
      "command": "uvx",
      "args": [
        "grad-agent"
      ],
      "env": {
        "ANTHROPIC_API_KEY": "your-value",
        "SMTP_SERVER": "your-value",
        "SMTP_PORT": "your-value",
        "SMTP_USERNAME": "your-value",
        "SMTP_PASSWORD": "your-value",
        "SMTP_FROM": "your-value",
        "GITHUB_TOKEN": "your-value",
        "HF_TOKEN": "your-value",
        "GRAD_AGENT_HOME": "your-value",
        "LOR_LETTERHEAD_PATH": "your-value",
        "LOR_LETTERHEAD_WIDTH": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "grad-agent": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "grad-agent"
      ],
      "env": {
        "ANTHROPIC_API_KEY": "your-value",
        "SMTP_SERVER": "your-value",
        "SMTP_PORT": "your-value",
        "SMTP_USERNAME": "your-value",
        "SMTP_PASSWORD": "your-value",
        "SMTP_FROM": "your-value",
        "GITHUB_TOKEN": "your-value",
        "HF_TOKEN": "your-value",
        "GRAD_AGENT_HOME": "your-value",
        "LOR_LETTERHEAD_PATH": "your-value",
        "LOR_LETTERHEAD_WIDTH": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

  • ANTHROPIC_API_KEY 机密 必填 env
    Anthropic API key used by Claude Haiku for hook synthesis and verification.
  • SMTP_SERVER 必填 env
    SMTP host for the review mailer.
  • SMTP_PORT 必填 env
    SMTP port.
  • SMTP_USERNAME 必填 env
    SMTP username; used as From address by default.
  • SMTP_PASSWORD 机密 必填 env
    SMTP password. Gmail App Password recommended.
  • SMTP_FROM 必填 env
    Envelope From address for drafts emailed to the user's review inbox.
  • GITHUB_TOKEN 机密 env
    Optional. Personal access token used to enumerate the user's public and private GitHub repos during catalog sync.
  • HF_TOKEN 机密 env
    Optional. HuggingFace token used to enumerate the user's published models and datasets during catalog sync.
  • GRAD_AGENT_HOME env
    Optional. Override the default ~/.grad-agent/ location for profile, programs, secrets, and data.
  • LOR_LETTERHEAD_PATH env
    Optional. Absolute path to a letterhead / company logo image (.png / .jpg / .pdf) embedded at the top of Letters of Recommendation during LaTeX compile. Leave unset for a plain top block. Can also be…
  • LOR_LETTERHEAD_WIDTH env
    Optional. LaTeX length for the letterhead image width (e.g. '2.5in'). Used only when LOR_LETTERHEAD_PATH is set.

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 i-ninte 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 32709 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32709 个服务器的 49% 更新
  • 基础检查结果等于或优于此分类中其他 32709 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

grad-agent 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

你需要填写:ANTHROPIC_API_KEY, SMTP_SERVER, SMTP_PORT, SMTP_USERNAME, SMTP_PASSWORD, SMTP_FROM, GITHUB_TOKEN, HF_TOKEN

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.2.9)于43天前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。

有什么可以替代它?

同一分类中有:Spec Driven Development, Remote Desktop Commander, SwarmMemo

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Spec Driven Development

作者:formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

在你的电脑上运行★ 440MIT14个月前更新
安装

Remote Desktop Commander

作者:desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

在云端运行★ 211前天更新
安装

SwarmMemo

作者:Hugo0

Talk with agent swarms: rooms, private messages and paid tasks for AI agents

在云端运行今天更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

grad-agent

An autonomous MCP agent that helps you apply to fully funded MS and PhD programs.

Discover and draft

  • Discovers professors on arXiv in your research areas, or deadline-driven per program (run_program_batch)
  • Resolves each professor's identity by anchoring on the trigger paper's canonical Semantic Scholar authorId, not the name string — name collisions like "Wei Zhang" are structurally impossible to confuse
  • Refuses to draft when identity cannot be anchored; the specific mismatch (e.g. identity ambiguous: 2 comparable candidates, h=40 vs h=38) is persisted to a skipped sheet for audit
  • Verifies each candidate is actually faculty (h-index and paper-count gates)
  • Filters by region (target_regions: [US, Canada] in your profile; keyword table + homepage TLD + LLM fallback)
  • Scrapes their lab page for a recruiting signal + email address
  • Matches them to your strongest shipped project (tag overlap + TF-IDF semantic layer + learned response-rate bias)
  • Drafts a specific, fact-checked cold email: Claude Haiku writes a hook spanning the prof's recent papers, then a second call verifies every claim against the abstracts and rewrites anything unsupported
  • Scores each draft 1 to 10 for fit, with a one-line reason, so you can triage in seconds
  • Freshness warnings on every draft: cross-checks the S2 affiliation against the prof's live homepage (flags MISMATCH if they may have moved labs) and flags researchers who have not published in 2+ years

Learn and follow through

  • Detects professor replies via read-only IMAP and tags the log automatically
  • Learns from outcomes: projects that earn replies rank up in future matching (outcome_report shows what works)
  • Drafts follow-up nudges for profs silent 10+ days; never nudges the same prof twice
  • Generates an interview prep one-pager when a prof replies: their papers summarised, likely questions, your talking points

Track everything

  • Compiles per-school SOPs to PDF (LaTeX), versioned so no draft is ever overwritten
  • Tracks outreach, LOR requests, program deadlines, and external scholarships (Mastercard, Commonwealth, Fulbright, Rhodes, and more) in xlsx/yaml
  • Emails every draft to your inbox for review; nothing is ever sent to a professor without you

Bundled Claude Code / Claude Desktop skills

Installing grad-agent ships a set of Anthropic Skills you can invoke from any Claude client that supports them (Claude Code, Claude Desktop, MCP-aware IDEs). grad-agent init symlinks them into ~/.claude/skills/ automatically; to (re)install without running init, use grad-agent install-skills (add --force to replace existing entries, or --target to link elsewhere).

  • `sop-writing` — rules for MS/PhD Statement of Purpose drafting, synthesized from MIT CommLab, MIT CAPD, Berkeley Grad Div, Harvard GSAS, Stanford, and CS-faculty guides. Pairs with the LaTeX SOP compile step.
  • `lor-writing` — rules for letters of recommendation, including the common case where the applicant ghost-drafts a letter for a recommender to sign. Encodes multi-letter differentiation, recommender realism, HHMI bias hygiene, and a banned-phrase regex sweep. Supports an optional letterhead / company logo via the LOR_LETTERHEAD_PATH env var (with LOR_LETTERHEAD_WIDTH, default 2.2in) so the LaTeX compile drops your image into the top of the letter — leave it unset for a plain top block the recommender can paste onto their own letterhead. grad-agent init will prompt for the letterhead path interactively; to change it later (or swap letterheads between recommenders) run grad-agent set-letterhead /path/to/image.png --width 2.5in (pass no path to clear it).
  • Cold-email drafter (grad_agent/drafters/cold_email.py) — rewritten around PhD outreach best-practices (specific paper anchor, one concrete overlap, no un-anchored superlatives, no "I read your paper" claims).

Runs as a stdio MCP server for Claude Code / Claude Desktop / any MCP client, or as a plain CLI.

Published on:

Install

Pick one:

# Recommended for MCP clients (Claude Desktop, Claude Code, etc.)

uvx grad-agent server # single-shot, no persistent install

Persistent CLI install

pipx install grad-agent

Or in a venv

python3 -m venv .venv && source .venv/bin/activate pip install grad-agent

Set up in 5 minutes

grad-agent init

This writes:

  • ~/.grad-agent/profile.yaml — your identity, projects, preferences
  • ~/.grad-agent/programs.yaml — target programs (seeded)
  • ~/.grad-agent/scholarships.yaml — external scholarships with deadlines (seeded)
  • ~/.grad-agent/.env — secrets template

Fill in ~/.grad-agent/.env:

ANTHROPIC_API_KEY=sk-ant-...

SMTP_SERVER=smtp.gmail.com # presets for Outlook/Yahoo/Zoho in the template SMTP_PORT=587 SMTP_USERNAME=you@gmail.com SMTP_PASSWORD= SMTP_FROM=you@gmail.com

Optional:

S2_API_KEY= # free Semantic Scholar key, dedicated rate limits

(client-side throttle already enforces >=1.1s between requests)

IMAP_SERVER=imap.gmail.com # read-only reply detection; defaults to SMTP creds GITHUB_USERNAME=your-gh GITHUB_TOKEN=github_pat_... HF_USERNAME=your-hf

Fill in the important bits of ~/.grad-agent/profile.yaml:

  • name, identity_line, portfolio
  • cv_path, transcript_path (absolute paths)
  • degree_status: bachelors | masters (drives PhD eligibility gating)
  • target_term, target_degree
  • research_areas: [nlp, ai4health, ...]
  • target_regions: [US, Canada] — only draft for profs in these regions (empty = anywhere)
  • seed_projects: 3 to 10 flagship projects with name, pitch, link, tags

Profile edits apply immediately, even while a long-running MCP session is open.

Then:

grad-agent sync        # scan projects (GitHub + HF + local)

grad-agent run # one batch, drafts land in your inbox

Register with Claude Code

Three commands, in order:

pipx install grad-agent

pipx ensurepath # macOS/Linux: opens ~/.local/bin on PATH

Windows: opens %USERPROFILE%\.local\bin on PATH

claude mcp add grad-agent grad-agent server

On Windows you may need to open a new PowerShell or Terminal window after pipx ensurepath for the PATH change to take effect.

Prefer a zero-install one-liner? Skip pipx and use uvx:

claude mcp add grad-agent uvx grad-agent server

Then in a new Claude Code session:

/mcp

You should see grad-agent connected with ~36 tools. Before it does anything useful, run grad-agent init (or uvx grad-agent init) and fill in ~/.grad-agent/.env and ~/.grad-agent/profile.yaml as described in the setup section above.

If you skipped pipx ensurepath, grad-agent register-claude prints an absolute-path variant of the command that works without PATH changes.

Register with Claude Desktop

Edit ~/Library/Application Support/Claude/claude_desktop_config.json:

{

"mcpServers": { "grad-agent": { "command": "uvx", "args": ["grad-agent", "server"] } } }

The uvx command needs no prior install. If you already ran pipx install grad-agent, you can use "command": "grad-agent", "args": ["server"] instead.

Any other MCP client (Cursor, Zed, Windsurf) uses the same manifest shape; just point them at uvx grad-agent server.

Daily autonomous run

The package ships scheduler templates for all three OSes. grad-agent schedule emits the right one for your platform:

grad-agent schedule --dest .

Then follow the install instructions the command prints. In case you want them up front:

macOS (launchd):

cp com.gradagent.daily.plist ~/Library/LaunchAgents/

launchctl load ~/Library/LaunchAgents/com.gradagent.daily.plist

Linux (systemd user timer, fires at 08:00 local):

mkdir -p ~/.config/systemd/user

cp grad-agent-daily.service grad-agent-daily.timer ~/.config/systemd/user/ systemctl --user daemon-reload systemctl --user enable --now grad-agent-daily.timer

Windows (Task Scheduler):

# In an elevated PowerShell prompt:

schtasks /Create /TN "grad-agent-daily" /XML .\grad-agent-daily.xml

Or import the XML via the Task Scheduler GUI (Action → Import Task).

Every morning: replies auto-detected via IMAP, follow-up nudges drafted for silent profs, 3 identity-verified faculty leads with fit scores (best fit first), hooks fact-checked against paper abstracts, freshness warnings when a prof's S2 record and live homepage disagree, plus program and scholarship deadline warnings — all in one review email. Skipped leads are persisted with the specific mismatch reason (view with skipped_log_view or open the skipped sheet).

What each MCP tool does

ToolPurpose
run_daily_batch(n, area)Full pipeline: verify → recruiting → hook + verify → draft → log
outreach_log_view(limit)Show last N rows of the outreach xlsx
outreach_mark_sent(prof, uni)Flag a row as actually sent to the prof
sync_catalog(source)Pull projects from github, hf, or local
list_projects_in_catalog()Show every project the matcher can see
list_programs()Your target programs
upcoming_deadlines(days)Any program deadline in the next N days
lor_add / lor_outstanding / lor_markRecommendation-letter tracker
run_program_batch(program_id, n)Deadline-driven batch: draft for one program's faculty
skipped_log_view(limit)Audit trail of skipped leads with the specific stage + mismatch reason
s2_cache_invalidate(query, all)Selectively purge Semantic Scholar cache entries by author name or id
followups_due(days)Drafted nudges for profs silent 10+ days
outreach_mark_followup(prof)Record a sent nudge (never nudged twice)
outreach_mark_response(prof, outcome)Tag replies; feeds the matcher's learning loop
outcome_report()Response rates by area and project
ingest_replies()Read-only IMAP scan; auto-tags replies in the log
interview_prep(prof)One-page brief: their papers, likely questions, your talking points
list_scholarships(region)External scholarships filtered by eligibility region
upcoming_scholarship_deadlines(days)Scholarship deadlines approaching
draft_cold_email(...)Manual per-prof draft
draft_sop(...)Compile a Columbia-style SOP PDF (versioned: sop_v1, v2, ...)
send_draft_to_me(path)Ship any draft file to your review inbox
discover_profs(area)arXiv + OpenReview scan (raw candidates, no verification)

Blog publishing tools (publish_article, update_article, ...) are gated behind blog.enabled: true in profile.yaml and are specific to the author's Turso-backed Next.js portfolio. Most users can ignore them.

What the agent will not do

  • Send any email to a professor. Every send is manual, from your Gmail, after you read the draft.
  • Touch your inbox beyond reading. IMAP access is read-only: it never sends, deletes, or marks messages.
  • Fabricate a paper claim. The hook goes through a second Claude call that rejects any claim not present in the abstracts, and rewrites.
  • Email the same professor twice. Deduplication is keyed on the Semantic Scholar authorId, with a name fallback for legacy rows, and follow-ups are marked so no prof is nudged more than once.
  • Draft for the wrong person when two profs share a name. Identity is resolved from the trigger paper's authorId, not the name string; ambiguous cases are refused and logged.
  • Hide why a lead was reject

只显示了开头部分;其余内容请在仓库中阅读

问 PopNx