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Landed MCP Server

Search AI-native jobs, prepare applications, and study for interviews — from any MCP client.

A public Model Context Protocol server that gives Claude, Cursor, VS Code, and any other MCP-capable agent live access to Landed's ranked, fit-scored job corpus.

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What is this?

Landed MCP connects your AI assistant to a curated, continuously-updated corpus of AI-native roles (AI Engineer, ML Engineer, RAG Engineer, AI PM, GTM Engineer, and more). Instead of copy-pasting job boards into a chat, your agent can:

• 🔎 Search jobs — ranked and fit-scored against a structured brief (role, skills, seniority, remote, compensation, industries…), or from a plain-English description.
• 📝 Prepare applications — pull a job's real application form, grouped into standard / screening / EEO fields, so the agent can auto-fill and draft answers before you apply.
• 🎓 Study for interviews — fetch free, curated interview-prep, portfolio, and roadmap resources.

It speaks Streamable HTTP and works with any MCP client. Use the hosted server in seconds, or self-host this repo against your own Landed API.

Free to start. Anonymous callers get a shared free budget — no signup, no key. Add an API token for unlimited, personalized results.

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Quick start (hosted)

The hosted server lives at:

https://mcp.landed.jobs/mcp

Pick your client below. Everything works anonymously out of the box — just omit the Authorization header. Add Authorization: Bearer lnd_live_… (mint one at Landed → Settings → API tokens) for unlimited, brief-personalized search.

Claude Code

The one-liner (CLI):

# Anonymous (free tier)
claude mcp add --transport http landed-jobs https://mcp.landed.jobs/mcp

# Authenticated (unlimited, personalized)
claude mcp add --transport http landed-jobs https://mcp.landed.jobs/mcp \
  --header "Authorization: Bearer lnd_live_your_token_here"

Then in a session: /mcp to confirm it's connected, and try the find_jobs prompt.

Claude Desktop

Open Settings → Developer → Edit Config (this opens claude_desktop_config.json), then add:

{
  "mcpServers": {
    "landed-jobs": {
      "command": "npx",
      "args": [
        "-y", "mcp-remote", "https://mcp.landed.jobs/mcp",
        "--header", "Authorization: Bearer lnd_live_your_token_here"
      ]
    }
  }
}

Restart Claude Desktop. Drop the --header line for the free anonymous tier.

Claude Desktop bridges remote HTTP servers through mcp-remote. If your build has native Custom Connectors (Settings → Connectors → Add custom connector), you can instead paste https://mcp.landed.jobs/mcp directly.

Cursor

Create .cursor/mcp.json in your project (or ~/.cursor/mcp.json globally):

{
  "mcpServers": {
    "landed-jobs": {
      "url": "https://mcp.landed.jobs/mcp",
      "headers": { "Authorization": "Bearer lnd_live_your_token_here" }
    }
  }
}

Then enable landed-jobs under Settings → MCP. Omit headers for the free tier.

VS Code (GitHub Copilot / Agent Mode)

Create .vscode/mcp.json:

{
  "servers": {
    "landed-jobs": {
      "type": "http",
      "url": "https://mcp.landed.jobs/mcp",
      "headers": { "Authorization": "Bearer lnd_live_your_token_here" }
    }
  }
}

Open the Chat view → Agent mode → the tools appear under the 🔧 picker.

Windsurf

Edit ~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "landed-jobs": {
      "serverUrl": "https://mcp.landed.jobs/mcp",
      "headers": { "Authorization": "Bearer lnd_live_your_token_here" }
    }
  }
}

Cline (VS Code extension)

Open Cline → MCP Servers → Configure, or edit cline_mcp_settings.json:

{
  "mcpServers": {
    "landed-jobs": {
      "type": "streamableHttp",
      "url": "https://mcp.landed.jobs/mcp",
      "headers": { "Authorization": "Bearer lnd_live_your_token_here" }
    }
  }
}

Any other MCP client

Point it at https://mcp.landed.jobs/mcp using the Streamable HTTP transport. Pass Authorization: Bearer <token> if you have one. Quick sanity check from a terminal:

curl -s -X POST https://mcp.landed.jobs/mcp \
  -H 'content-type: application/json' \
  -H 'accept: application/json, text/event-stream' \
  -d '{"jsonrpc":"2.0","id":1,"method":"tools/list"}'

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Tools

Tool	What it does	Anonymous cost
search_jobs	Ranked, fit-scored jobs. Fill structured fields (role, skills, remote, seniority, comp, industries…) or a free-text query (parsed into filters server-side).	1 unit / job returned
get_job_form	Application form for a jobId, grouped standard / screening / eeo for answer prep.	free
get_learning_content	Curated interview-prep, portfolio, and roadmap resources.	free

Prompts (guided workflows)

MCP prompts are reusable, user-invocable skills that teach the agent how to chain the tools and present results as a clean shortlist — never raw JSON. In most clients they show up as slash-commands.

Prompt	Args	What it guides
find_jobs	describe?	Search, then present a ranked, fit-scored shortlist + next steps.
prepare_application	jobId	Fetch the form; auto-fill standard, draft screening, leave EEO to the user.
prep_for_role	role?	Pull learning resources for a role and suggest a study order.

The server also ships always-on instructions (tool overview, presentation rules, freemium behavior) that compliant clients load automatically.

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Auth & pricing

Tier	How	What you get
Anonymous	No header	A shared free budget of job-units. Metered by a hybrid of your IP and an issued X-Landed-Anon token (echoed on every response — resend it to keep your budget across sessions).
Authenticated	Authorization: Bearer lnd_live_…	Unlimited search, personalized to your saved brief + profile. Mint a token at Landed → Settings → API tokens.

Every result carries a freemium block so your agent can see how much budget is left and how to lift the cap.

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Architecture

This repository is a thin, self-hostable proxy. It speaks MCP and forwards to the hosted Landed API — it holds no database, no ranking engine, and no job data.

   MCP client                 landed-mcp (this repo)              Landed API
 ┌─────────────┐   HTTP    ┌────────────────────────┐  HTTPS   ┌────────────────────────┐
 │ Claude /    │ ───────▶  │ • MCP protocol + tools │ ──────▶  │ • search engine        │
 │ Cursor /    │  /mcp     │ • forwards caller creds│          │ • job corpus + forms   │
 │ VS Code …   │ ◀───────  │ • local learning list  │ ◀──────  │ • auth · freemium meter│
 └─────────────┘           └────────────────────────┘          └────────────────────────┘

The proxy resolves nothing itself: it forwards the caller's API token (or an anonymous id) to the Landed API, which validates it, runs the search, meters usage, and returns results plus a freemium block the proxy relays verbatim. The get_learning_content catalog is static and lives in this repo (src/mcp/catalog/learning.ts) — that tool works with no backend at all.

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Self-host

Run your own proxy against the Landed API (or your own deployment of it).

Prerequisites

• Node.js ≥ 20
• pnpm (npm i -g pnpm)
• A Landed API base URL and its shared internal secret

Run

git clone git@github.com:landedjobs/landed-mcp.git
cd landed-mcp
pnpm install
cp .env.example .env       # then fill in the values below
pnpm dev                   # hot-reload dev server
# → [mcp] listening on :8090 — POST /mcp → https://api.landed.jobs/api/v1

For production: pnpm start.

Environment variables

Variable	Required	Default	Description
LANDED_API_BASE	✓	http://localhost:8000/api/v1	Hosted Landed API base, including the /api/v1 prefix.
LANDED_INTERNAL_SECRET	✓	—	Shared secret authenticating this proxy to the API (must match the server's INTERNAL_SERVICE_SECRET).
PORT		8090	HTTP port to listen on.
CORS_ORIGINS		*	Comma-separated allowlist of origins, or *.
RATE_LIMIT_PER_MIN		60	Per-IP first-line request cap. The API's freemium meter is the real economic cap.

Endpoints

Method	Path	Purpose
POST	/mcp	MCP Streamable HTTP endpoint (stateless).
GET	/healthz	Liveness probe ({ "ok": true }).

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Development

pnpm dev           # watch + reload
pnpm check-types   # tsc --noEmit
pnpm start         # run once

Project layout

src/
├── index.ts                 # bootstrap: start the HTTP server
├── config/                  # env → typed config
├── http/                    # express shell + per-IP rate limiter
├── services/api-client.ts   # typed fetch client → Landed API
├── types.ts                 # the API response contract (owned here)
└── mcp/
    ├── server.ts            # instructions + tool/prompt registration
    ├── prompts.ts           # find_jobs / prepare_application / prep_for_role
    ├── catalog/learning.ts  # static, public learning resources
    └── tools/               # search_jobs · get_job_form · get_learning_content

Stack: TypeScript · Express · @modelcontextprotocol/sdk · Zod. No database, no build step (runs on tsx).

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Contributing

Issues and PRs welcome — bug fixes, new client setup guides, and learning-catalog additions especially. Please run pnpm check-types before opening a PR.

License

MIT © Landed