B2B 연락처를 실시간으로 찾고 검증합니다. 회사 웹사이트, Discord, Telegram을 스크래핑한 후 모든 이메일을 SMTP로 검증합니다. 네이티브 MCP 서버로 구축되어 Claude, ChatGPT, Cursor 및 모든 AI 에이전트가 직접 호출할 수 있습니다.
한 줄 명령어로 설치:
uvx --from git+https://github.com/axelfreeman/tapac-mcp tapac-mcp그런 다음 에이전트에게 물어보세요: "직원 50~500명의 미국 SaaS 회사에서 VP Sales 20명을 찾아줘."
데이터베이스는 썩습니다. 매년 연락처의 23%가 직장을 바꾸고(ZoomInfo 2025), 2년 안에 이메일의 40%가 사라집니다(NeverBounce). 연락처 목록을 구매하면 이메일 한 통 보내기도 전에 4분의 1이 낡은 데이터가 됩니다.
TAPAC은 데이터베이스를 판매하지 않습니다. 실시간으로 스크래핑하고 요청 시점에 검증합니다:
TAPAC | 정적 DB (Apollo, ZoomInfo, Hunter) | |
데이터 소스 | 실시간 스크래핑 | 고정된 스냅샷 |
반송률 | 2–5% | 10–35% |
검증 | SMTP, 즉시 | 없음 / 사후 |
MCP / AI 에이전트 | ✅ 네이티브 | ❌ |
Discord / Telegram | ✅ | ❌ |
가격 | 사용량 기반, 연락처당 $0.10–0.50 | $34–$15,000+/월 또는 /년 |
Related MCP server: Bytemine MCP Server - Contact Search & Enrich
uvx --from git+https://github.com/axelfreeman/tapac-mcp tapac-mcp필요 사항: uv (한 줄 설치: curl -LsSf https://astral.sh/uv/install.sh | sh).
동일한 command + args가 모든 곳에서 작동합니다. 에이전트를 선택하세요:
Claude Desktop — claude_desktop_config.json:
{
"mcpServers": {
"tapac": {
"command": "uvx",
"args": ["--from", "git+https://github.com/axelfreeman/tapac-mcp", "tapac-mcp"]
}
}
}Claude Code (터미널):
claude mcp add tapac -- uvx --from git+https://github.com/axelfreeman/tapac-mcp tapac-mcpCodex (OpenAI) — ~/.codex/config.toml:
[mcp_servers.tapac]
command = "uvx"
args = ["--from", "git+https://github.com/axelfreeman/tapac-mcp", "tapac-mcp"]Cursor — .cursor/mcp.json:
{
"mcpServers": {
"tapac": {
"command": "uvx",
"args": ["--from", "git+https://github.com/axelfreeman/tapac-mcp", "tapac-mcp"]
}
}
}Windsurf — ~/.codeium/windsurf/mcp_config.json (Cursor와 동일한 JSON).
DeepSeek — 채팅 앱은 로컬 MCP 서버를 기본적으로 등록하지 않습니다. MCP 지원 클라이언트(DeepSeek API를 사용하는 Claude Code / Cursor)를 통해 DeepSeek을 사용하거나 호스팅된 엔드포인트 https://tapacapi.com/mcp/sse에 연결하세요 (출시 예정).
첫 실행 시 https://tapacapi.com/get-key로 안내합니다. 한 번 설정하세요:
export TAPAC_API_KEY=your_key_here"직원 50~500명의 미국 SaaS 회사에서 VP Sales 20명을 찾고 이메일을 검증해줘."
에이전트가 필요한 기준을 묻고, tapac_find_contacts를 호출한 후 검증된 연락처(이름, 직함, 회사, 이메일, 출처, 검증 상태)를 반환합니다.
100회 무료 검색, 신용카드 불필요.
tapac_find_contactsB2B 연락처를 찾고 검증합니다.
매개변수 | 유형 | 설명 |
| 문자열 | 업종, 예: "SaaS", "헬스케어", "핀테크" |
| 문자열 배열 | 직책, 예: |
| 문자열 | "50-500명", "스타트업", "엔터프라이즈" |
| 문자열 | "미국", "유럽", "DACH", "원격" |
| 문자열 |
|
| 정수 | 연락처 수 (기본값 10) |
tapac_status서버 버전 + API 키 상태.
베타. 설치 + 도구 인터페이스 + API 키 온보딩이 라이브입니다. 전체 스크래핑 → SMTP 검증 엔진이 연결 중이며 다음에 출시됩니다. 그때까지 tapac_find_contacts는 대상을 캡처하고 명확한 베타 응답을 반환하므로 오늘 설치하고 제품 내부를 살펴볼 수 있습니다.
웹사이트: https://tapacapi.com
무료 툴킷 (자체 호스팅): https://github.com/axelfreeman/b2b-contact-mining-kit
저자: Axel Freeman
MIT.
Find and verify B2B business contacts in real time.
Ask the user for these criteria before calling:
industry: vertical, e.g. "SaaS", "healthcare", "fintech"
job_titles: roles, e.g. ["VP Sales", "CTO", "Head of Growth"]
company_size: e.g. "50-500 employees", "startup", "enterprise"
location: geography, e.g. "US", "Europe", "DACH", "remote"
source: where to search — "website", "telegram", or "discord"
limit: how many contacts to return (default 10)
Returns verified contacts (name, title, company, email, source, verification status) as structured data.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| source | No | website | |
| industry | No | ||
| location | No | ||
| job_titles | No | ||
| company_size | No |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
While no annotations are provided, the description adds significant context by specifying that contacts are returned as structured data with fields like name, title, company, email, source, and verification status. It also discloses that contacts are verified, which is a behavioral trait. However, it does not mention authentication needs, rate limits, or what happens when no contacts are found—minor gaps that prevent a top score.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is succinct and well-structured, with a concise opening sentence followed by a bulleted list of criteria to ask for. Every sentence provides essential information without repetition or fluff. The structure is front-loaded with the main purpose, then details, making it easy for an AI agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity with 6 parameters, no required fields, and no annotations, the description covers the critical aspects: purpose, required user input, parameter semantics, and return structure. The presence of an output schema partially reduces the need to describe return values further. However, a note on error handling or empty results would enhance completeness for the agent, preventing it from being a 5.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds substantial meaning beyond the input schema by defining each parameter with concrete examples (e.g., industry 'SaaS', location 'US'), which compensates for the 0% schema description coverage. For the limit parameter with default 10, it clarifies the purpose. This goes well beyond the bare schema definitions, making the parameters actionable for the agent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Find and verify B2B business contacts in real time.' The verb 'find and verify' combined with the resource 'B2B business contacts' and modifier 'in real time' makes the action explicit. It also distinguishes itself from the sibling tool 'tapac_status' by focusing on contact discovery rather than status checking.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidelines by instructing the user to ask for specific criteria before calling the tool, listing each parameter with examples (e.g., industry 'SaaS', job_titles '[VP Sales, CTO, ...]'). This guidance clearly tells the agent when to use the tool—when it needs to collect these details from the user—and implicitly distinguishes it from the sibling tool 'tapac_status' which likely handles status queries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Check TAPAC server status, version, and API-key state.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description indicates the tool performs a read-only check of status, version, and API-key state. While this implies safe, non-destructive behavior, there are no annotations to confirm. The description does not elaborate on potential latency, network dependencies, or error states, which would improve transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, using a single sentence that effectively communicates the three aspects the tool checks: server status, version, and API-key state. There is no extraneous text, making it easy for an AI agent to quickly interpret its purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters and the sibling tool is clearly for contact lookup, the description is largely sufficient for a status-check tool. However, the description does not explain the format or structure of the output, which could be important for an agent to interpret results, even though an output schema exists separately.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has zero parameters and has 100% coverage. Since no parameters exist, there is no need for the description to add parameter-level details, and a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks TAPAC server status, version, and API-key state. It uses specific nouns and verbs to describe the function, differentiating it from sibling tools that likely interact with contacts rather than checking server status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for health-check or diagnostic purposes, but does not explicitly state when to use this tool versus the sibling tapac_find_contacts. It lacks guidance on prerequisites or conditions under which a status check is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v0.1.0tapac_find_contactstapac_statusScored across 2 tools
The two tools serve completely distinct purposes: one checks server status, the other finds contacts. There is no overlap or ambiguity.
Both tools follow a consistent snake_case pattern with the prefix 'tapac_', one describing a state (status) and the other an action (find_contacts). The naming is uniform.
With only two tools, the server feels thin for a contact-finding service, but each tool is clearly defined and serves a necessary function. It is borderline but not excessive.
The server covers the core operation of finding and verifying contacts with extensive filtering, plus a status check. Minor gaps like retrieving a specific contact by ID are absent, but the main workflow is complete.
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