# Golddigger MCP Server > B2B Lead Intelligence API — search, enrich & score 10M+ global companies from any MCP-compatible client. [![MCP Server](https://img.shields.io/badge/MCP-Server-green)](https://modelcontextprotocol.io) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) [![Data Sovereignty](https://img.shields.io/badge/Data-Local%20Only-blue)](https://golddigger.gold) ## What is this? A Model Context Protocol (MCP) server that wraps the [Golddigger API](https://golddigger.gold) — giving AI assistants (Claude, Cline, Cursor, etc.) the ability to search, enrich, and score B2B leads in real time. **4 tools exposed:** | Tool | Description | Data Flow | |------|-------------|-----------| | `health_check` | Service health + **real** account quota (`/api/health` + `/api/quota`) | External API call | | `check_quota` | 挖客前预检:服务端剩余 + 本地每日预算账本 | External API call | | `search_leads` | Search by buyer-intent keyword + country (`POST /api/search`) | External API call, **1 quota each** | | `score_lead` | Six-dimension quality scoring | **Local only** | | `generate_report` | Full radar chart + Word report | **Local only** | | `draft_outreach` | Role-aware outreach draft + local queue CSV | **Local only**, 0 quota | ## Data Sovereignty - ✅ **Report generation**: 100% local (matplotlib + python-docx). No data leaves the user's machine. - ✅ **Scoring**: Pure local computation — six-dimension model runs on-device. - ⚠️ **Search**: Calls Golddigger API. Customer provides their own API key — costs borne by customer. ## Installation ```bash git clone https://github.com/SassumiX/golddigger-mcp.git cd golddigger-mcp pip install -r requirements.txt ``` ## Configuration ```bash # Set your Golddigger API key (customer provides their own) export GOLDDIGGER_API_KEY="gd_your_key_here" export GOLDDIGGER_HOST="https://golddigger.gold" # 可选 export GOLDDIGGER_DAILY_BUDGET=20 # 可选:本地软预算,默认 20 export GOLDDIGGER_QUOTA_RESERVE=2 # 可选:剩余低于此值不再自动搜 ``` > **Token billing**: The `search_leads` tool uses the customer's API key. Report generation is free (no external API calls). ## Usage ### Claude Desktop (macOS) Add to `~/Library/Application Support/Claude/claude_desktop_config.json`: ```json { "mcpServers": { "golddigger": { "command": "python3", "args": ["/FULL/PATH/TO/golddigger-mcp/server.py", "--transport", "stdio"] } } } ``` Restart Claude Desktop. ### Cline / Other MCP Clients ```json { "mcpServers": { "golddigger": { "command": "python3", "args": ["/FULL/PATH/TO/golddigger-mcp/server.py", "--transport", "stdio"], "env": { "GOLDDIGGER_API_KEY": "gd_your_key_here" } } } } ``` ### HTTP Endpoint ```bash python3 server.py --transport streamable-http --port 8080 ``` ## MCP Tools ### generate_report(商业核心工具) ``` 用户说:"出客户画像报告" Agent 自动调用 → 生成本地 .docx 文件 ``` ```python # Agent 调用示例 result = golddigger.generate_report( company_name="cnpulk.com", product_desc="DTH drill bits, rock drilling tools", buyers=[ { "name": "Afrimat Limited", "country": "南非", "industry": "Mining", "has_contact": True, "scale": "上市矿业集团", "buyer_role": "Contract Mining总监", "purchase_needs": "DTH钻头,持续消耗", "contacts": ["pierre@afrimat.co.za · +27 82 411 7475"], "outreach": "We offer 20-30% cost savings on DTH bits." }, # ... 2 more buyers ], api_key="gd_customer_own_key" # 客户自己的Key,费用自担 ) # result["output_path"] → 本地 .docx 文件路径 ``` ### score_lead ```python result = golddigger.score_lead( company="Afrimat Limited", country="南非", industry="Mining", has_contact=True, scale="上市矿业集团", note="并购整合期" ) # result["total"] = 91, result["tier"] = "HOT" ``` ## Pricing | Plan | 每日配额 | |------|---------| | Free | **20 次/天**(2026-10-06 由 `GET /api/quota` 实测得出,00:00 UTC 重置) | | Paid | 见 [https://golddigger.gold](https://golddigger.gold) | > ⚠️ 别信任何写死的配额数字,**以 `check_quota` 的实时返回为准**。 > Get your key at [https://golddigger.gold](https://golddigger.gold) ## outreach 是主线(不是 search) `search` 每天只有 20 次,`draft_outreach` **不限次数、不耗配额** —— 因为找人的成本高, 开口的成本为零。所以工作流必须是: ``` check_quota → search_leads(dry_run) → search_leads → 对每条 lead 跑 draft_outreach → 进 outreach_queue.csv → 按 D0/D3/D7/D14 跟进 ``` `draft_outreach` 会按公司描述自动识别角色(进口商 / 地产开发商 / 酒店 / 民宿)并切换话术, 支持 `email` / `linkedin` / `whatsapp` / `wechat` 与中英双语,队列按 company+channel 去重。 ```python r = golddigger.draft_outreach( lead={"company": "Bin Harkil Group", "contact": "Procurement", "country": "SA", "industry": "real estate developer"}, my_profile="smart lock factory, OEM/ODM, CE, MOQ 200, 7-day samples", channel="email", language="en", ) # r["subject"], r["body"], r["followup_plan"], r["quota_cost"] == 0 ``` ## 已知问题 / 端点实测(2026-10-06) | 端点 | 状态 | |---|---| | `GET /api/health` | ✅ | | `GET /api/quota` | ✅ 真实配额端点(旧代码用的 `/api/tenants/me` 从未上线) | | `GET /api/leads` | ✅ | | `POST /api/search` | ⚠️ **当前 500**,站点侧故障,重试无用(5xx 不扣配额) | | `GET /api/leads/search` | ❌ 从未部署(旧 `search_leads` 打的就是这个,恒 404) | ## 配额纪律(Agent 必读) 1. **批量挖客前先调 `check_quota`**,别让 Agent 自由发挥地循环搜索。 2. `search_leads(dry_run=True)` 可以预演请求,不烧配额 —— 先批量预演,再挑着真跑。 3. 本地预算账本写在 `~/.golddigger/search_budget.json`,默认上限 20/天,按天重置。 4. 剩余 ≤ 2 次(`GOLDDIGGER_QUOTA_RESERVE`)时 `search_leads` 直接拒绝发起,留额度给人工决策。 5. 优先级:**采购角色词 > 产品细分词 > 泛需求词**。泛需求词最费额度、命中率最低。 ## License MIT — SassumiX 2026