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WonderCV

ClawHire MCP

by WonderCV

ClawHire MCP

Employer-facing MCP for China's first agent-native hiring marketplace.

ClawHire lets hiring managers post jobs, search candidates, and receive applications — all through natural language conversation with Claude or any MCP-compatible AI assistant. Backed by WonderCV's resume database and existing HR infrastructure.

What This Is

ClawHire is one half of a two-sided marketplace:

Candidates                              Employers
    │                                       │
resume-agent-mcp                    clawhire-mcp (this repo)
    │                                       │
    └──────── WonderCV Backend ─────────────┘
                    │
              PostgreSQL (existing WonderCV DB)
  • resume-agent-mcp — Candidate-facing. Resume analysis, profile publishing, job applications.

  • clawhire-mcp (this repo) — Employer-facing. Job posting, candidate search, application management.

Both share WonderCV's existing Django backend, company database, and profession taxonomy. This is NOT a standalone product — it's an MCP layer on top of WonderCV's existing hiring infrastructure.

Why It Exists

The thesis: China is in an AI-agent boom. Companies hiring for white-collar roles increasingly want people who can work with AI agents. But no hiring platform treats AI-agent fluency as a first-class hiring signal.

ClawHire does. Candidates who use MCP tools are automatically tagged with AI fluency badges. Employers can filter for agent-fluent talent. This signal is impossible to replicate on traditional job boards.

Three Categories of Candidates

Not all candidates are equal. The system handles three distinct pools:

Category

How They Enter

AI Fluency

Employer Can...

1. MCP Native

Install resume-agent-mcp, publish profile

Auto-badged verified_mcp_user

Search, view profile, receive applications

2. GUI Opt-In

Click button on wondercv.com or WeChat

No badge (not demonstrated)

Same as above

3. Database

They don't — existing WonderCV users

None

View anonymized/coarsened data, send outreach invite only

Category conversions:

  • 3 → 2: Candidate responds to outreach email or opts in via GUI

  • 2 → 1: Candidate links MCP session to their WonderCV account (automatic upgrade)

  • Conversions are one-way (upward only)

Company blocklist: Candidates can block specific companies (e.g. current employer) from seeing their profile. Enforced at query time.

Architecture

Existing WonderCV Models We Reuse (DO NOT DUPLICATE)

Model

Table

What It Has

Companies

api/companies/

Company names (cn/en), scale, industry, Tianyancha verification

HrAccounts

api/account/

HR manager accounts, WeChat auth, phone login, quotas

Jobs

api/jobs/

Job postings with profession taxonomy, salary, experience (in days)

JobApplications

api/data_operations/

Application tracking with state machine

JobOrders

api/job_orders/

Payment/promotion with Alipay + WeChat Pay

New Models We Add (only 2)

Model

Purpose

CandidateProfile

Opt-in marketplace profile (Cat 1 + 2). Links to WonderCV user. Contains visibility, AI fluency data, company blocklist, preferences.

McpEmployerSession

Bridges MCP session → HrAccount. Tracks daily usage quotas.

Data Unit Conventions

These MUST match existing WonderCV conventions:

Field

Unit

Notes

salary_min/max

CNY/month (integer)

NOT thousands

experience_min/max

Days (in DB)

MCP accepts years, converts with × 365

status (Jobs)

Integer 0-4

0=draft, 1=publish, 2=expired, 3=offline, 4=remove

IDs

token (CharField)

NOT UUIDs — WonderCV uses string tokens

Available Tools (7)

Tool

Purpose

Quota

register_company

Create employer account, get session_id

post_job

Publish job to marketplace

jobs_posted

list_jobs

View own posted jobs with stats

search_candidates

Search marketplace + database pools

searches

view_candidate

View candidate profile (visibility-enforced)

candidate_views

list_applications

View inbound applications

request_outreach

Send invite to Category 3 database candidate

outreach_sent

Quota Tiers (daily limits)

Tier

Views

Searches

Outreach

Jobs

Alpha (current)

50

30

10

5

Free

20

10

5

2

Paid

200

100

20

20

All alpha users get the Alpha tier for free.

Quick Start

Install & Build

git clone https://github.com/WonderCV/clawhire-mcp.git
cd clawhire-mcp
npm install
npm run build

Configure

cp .env.example .env

Edit .env:

CLAWHIRE_API_BASE_URL=https://api.wondercv.cn/cv/v1/mcp/hiring
CLAWHIRE_API_KEY=your_api_key_here    # Leave as-is for mock mode
LOG_LEVEL=info

Mock mode: If CLAWHIRE_API_KEY is missing or your_api_key_here, the server returns realistic mock data for all endpoints. Useful for development without the backend.

Add to Claude

In your MCP config (e.g. ~/.claude.json or Claude Desktop settings):

{
  "mcpServers": {
    "clawhire": {
      "command": "node",
      "args": ["/absolute/path/to/clawhire-mcp/dist/server.js"],
      "env": {
        "CLAWHIRE_API_KEY": "your_api_key_here"
      }
    }
  }
}

Try It

After connecting, tell Claude:

  • "Register my company — we're TechCorp in Shanghai, email hr@techcorp.com"

  • "Post a job for Senior Product Manager, remote OK, 30-50k/month"

  • "Search for AI-fluent product managers in Shanghai with 3+ years experience"

  • "Show me candidate details for [candidate_id]"

  • "Send an outreach invite to [candidate_ref] for the PM role"

Development

npm run dev          # Watch mode (auto-recompile on changes)
npm run build        # Single build
npm run typecheck    # Type check without emitting
npm start            # Run compiled server

Project Structure

src/
├── server.ts           # MCP server entry, tool registration, JSON schema conversion
├── types.ts            # All TypeScript types (aligned with WonderCV models)
├── session.ts          # In-memory session management + quota tracking
├── backend-api.ts      # WonderCV backend API client (with mock fallback)
└── tools/
    ├── index.ts                # Tool registry
    ├── register_company.ts     # Creates HrAccount + Company
    ├── post_job.ts             # Wraps Jobs model (years→days conversion)
    ├── list_jobs.ts            # Paginated job list with stats
    ├── search_candidates.ts    # Marketplace + database pools, AI fluency filter
    ├── view_candidate.ts       # Visibility-enforced profile view + anonymization
    ├── list_applications.ts    # Application list with match scores
    └── request_outreach.ts     # Database candidate invitation (rate-limited)

Adding a New Tool

  1. Create src/tools/your_tool.ts implementing the Tool<Input> interface

  2. Define input schema with Zod

  3. Implement execute(input) returning ToolResult

  4. Export from src/tools/index.ts and add to allTools array

  5. The server auto-registers it via the tool registry

Backend API Pattern

All tools follow the same pattern:

// 1. Validate session
const session = getSession(input.session_id);
if (!session) return errorResult('INVALID_SESSION', '...');

// 2. Check quota (for metered tools)
const remaining = getRemainingQuota(session, 'searches');
if (remaining <= 0) return errorResult('QUOTA_EXCEEDED', '...');

// 3. Call backend
const result = await backendApi.searchCandidates(input);

// 4. Consume quota AFTER success (not before)
checkAndIncrementUsage(session, 'searches');

// 5. Format and return
return { content: [{ type: 'text', text: JSON.stringify(formatted) }], isError: false };

Known Issues (v0.1.0)

See KnownIssues.md for full details.

Issue

Severity

Impact

In-memory session storage

High (for prod)

Server restart = re-register

Quota race condition

Medium

Concurrent requests can exceed limits

Brittle JSON schema conversion

Medium

Works for flat inputs, fragile for complex

No test coverage

Low

Needs tests before v0.2

Alpha verdict: Ship to alpha (<50 employers), not to GA.

Roadmap

v0.1 (current) — Alpha Foundation

  • 7 employer tools (register, post, search, view, applications, outreach, list)

  • Three-category candidate model

  • AI fluency badges

  • Anonymization for privacy

  • Daily quota system

v0.2 — Marketplace Core

  • Persistent session storage (Redis or backend rehydration)

  • Backend authoritative quota metering

  • Replace zodToJsonSchema with zod-to-json-schema library

  • Candidate-side tools in resume-agent-mcp (publish, apply, browse jobs)

  • LLM-based match scoring

  • Test suite

v0.3 — Growth

  • Company verification automation (Tianyancha API)

  • Application status management (shortlist, reject)

  • Paid tier billing (via existing JobOrders + Alipay/WeChat Pay)

  • Global aggregate stats

License

MIT

Install Server
A
security – no known vulnerabilities
F
license - not found
A
quality - confirmed to work

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