AI 어시스턴트를 Leadloadz B2B 리드 생성 플랫폼에 연결하는 Model Context Protocol (MCP) 서버입니다.
리드 검색 — 자연어 쿼리를 사용하여 검증된 B2B 리드 찾기
이메일 검증 — 전달 가능성 점수를 포함한 실시간 이메일 검증
통계 확인 — 사용량 및 남은 할당량 확인
Related MCP server: LeadClaw
별도의 설치가 필요하지 않습니다. AI 클라이언트에서 서버를 직접 실행할 수 있습니다:
npx -y @leadloadz/mcp-servernpm install -g @leadloadz/mcp-server
leadloadz-mcp이 서버를 사용하려면 Leadloadz API 키가 필요합니다.
leadloadz.com에서 가입하세요
대시보드 → API 토큰으로 이동하세요
새 토큰을 생성하세요
토큰 값을 복사하세요
claude_desktop_config.json에 추가하세요:
{
"mcpServers": {
"leadloadz": {
"command": "npx",
"args": ["-y", "@leadloadz/mcp-server"],
"env": {
"LEADLOADZ_API_KEY": "your-api-key-here"
}
}
}
}Cline MCP 설정에 추가하세요:
{
"mcpServers": {
"leadloadz": {
"command": "npx",
"args": ["-y", "@leadloadz/mcp-server"],
"env": {
"LEADLOADZ_API_KEY": "your-api-key-here"
}
}
}
}stdio 전송을 지원하는 모든 MCP 클라이언트는 다음을 사용할 수 있습니다:
{
"command": "npx",
"args": ["-y", "@leadloadz/mcp-server"],
"env": {
"LEADLOADZ_API_KEY": "your-api-key-here"
}
}변수 | 필수 | 기본값 | 설명 |
| 예 | — | Leadloadz API 토큰 |
| 아니요 |
| API 기본 URL |
| 아니요 |
| 요청 시간 제한 (밀리초) |
# 의존성 설치
npm install
# 빌드
npm run build
# 타입 체크
npm run typecheck
# 로컬 테스트
node dist/index.js다음과 같은 경우 새 버전을 게시하세요:
새 도구 추가 또는 기존 도구 스키마 변경
MCP 응답에 영향을 주는 API 엔드포인트 동작 변경
MCP 서버 코드의 버그 수정
의존성 업데이트 (특히 @modelcontextprotocol/sdk)
환경 변수 또는 구성 옵션 변경
다음 변경 사항에 대해서는 게시하지 마세요:
메인 Leadloadz 웹 앱 (별도의 코드베이스임)
Next.js 앱의 API 경로 (MCP 서버가 해당 경로로 프록시함)
데이터베이스 스키마 (메인 앱에서 처리)
UI 컴포넌트 또는 마케팅 페이지
필요에 따라 src/의 파일을 수정하세요. 로컬에서 테스트하세요:
npm run build
npm testnpm version patch # 버그 수정 시
npm version minor # 새 기능 추가 시
npm version major # 주요 변경 사항 시버전을 변경했다면 server.json도 일치하도록 업데이트하세요:
{
"version": "1.0.X",
"packages": [
{
"version": "1.0.X"
}
]
}git add .
git commit -m "변경 사항 설명"
git push origin masterecho "//registry.npmjs.org/:_authToken=YOUR_NPM_TOKEN" > .npmrc
npm publish --access public
rm -f .npmrc참고: npm 토큰은 npm_으로 시작합니다. 안전하게 보관하고 절대 커밋하지 마세요.
새 npm 버전을 게시할 때마다 Anthropic MCP 레지스트리를 업데이트해야 합니다:
# 로그인 (토큰이 만료되므로 매번 수행해야 할 수 있음)
./mcp-publisher login github
# 기기 인증 흐름을 따르세요:
# 1. https://github.com/login/device 로 이동
# 2. 표시된 코드 입력
# 3. 애플리케이션 승인
# 게시
./mcp-publisher publish중요: package.json의 mcpName은 server.json의 name과 정확히 일치해야 합니다(대소문자 구분). 현재 둘 다 io.github.Ali1041/leadloadz를 사용합니다.
플랫폼 | URL | 목적 |
npm | 패키지 배포 | |
GitHub | 소스 코드 | |
Anthropic MCP 레지스트리 | 공식 Anthropic 디렉토리 | |
Glama.ai | 커뮤니티 디렉토리 | |
PulseMCP | 커뮤니티 디렉토리 | |
Smithery.ai | 커뮤니티 디렉토리 | |
MCP.Directory | 커뮤니티 디렉토리 |
"Token expired" 오류:
./mcp-publisher login github를 다시 실행하세요
"You do not have permission" 오류:
server.json 이름이 GitHub 사용자 이름과 대소문자까지 일치하는지 확인하세요: io.github.Ali1041/leadloadz
package.json의 mcpName이 정확히 일치하는지 확인하세요
"Validation failed" 오류:
설명은 100자 이내여야 합니다
server.json의 모든 필수 필드가 있어야 합니다
npm 패키지가 일치하는 버전으로 이미 게시되어 있어야 합니다
API 키는 절대 로그에 기록되거나 오류 메시지에 노출되지 않습니다
모든 오류는 정보 유출을 방지하기 위해 정제됩니다
서버는 HTTPS를 통해 Leadloadz API와 직접 통신합니다
속도 제한은 Leadloadz API에 의해 강제됩니다
웹사이트: leadloadz.com
이슈: GitHub Issues
MIT
Read current usage counters: searches performed, emails verified, and remaining quota. Read-only. Requires API key. Rate limit: 30/min per user. Use before batch operations to check available allowance.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses read-only nature, API key requirement, and rate limit (30/min per user). No annotations exist, so the description carries full burden; it adequately covers behavioral traits for a safe read operation.
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?
Three concise sentences front-load the purpose and add necessary behavioral info without redundancy. Every sentence adds value.
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?
Provides enough context for a parameterless tool: what it reads, when to use it, and constraints. Lacks details on return format, but acceptable for simple stats retrieval.
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?
No parameters in input schema, so baseline score is 4. Description does not need to add parameter information.
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 it reads usage counters (searches, emails, quota). It distinguishes itself from siblings 'search_leads' and 'verify_email' by specifying a different resource and action.
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?
Explicitly advises to use before batch operations to check allowance. While it doesn't discuss when not to use or alternatives, the provided context is sufficient for a simple read tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search indexed B2B contacts by role, company, location, or technology. Read-only; returns verified leads with deliverability scores. Requires API key. Rate limit: 30/min per user. Use verify_email after discovery to confirm deliverability before outreach.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Specific natural-language search query. Narrow criteria yield better precision (e.g., 'CTOs at Series A B2B SaaS in London') | |
| limit | No | Maximum results to return. Default: 10. Cap: 50. Higher values consume more quota. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully covers behavioral traits: read-only, returns verified leads with deliverability scores, requires API key, and rate limit of 30/min per user.
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?
Three sentences, front-loaded with purpose, no wasted words. Each sentence adds value.
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?
For a 2-param search tool with no output schema, the description adequately explains input (search criteria), behavior (read-only, deliverability scores), constraints (rate limit, API key), and follow-up action (verify_email). Complete.
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?
Schema coverage is 100% and schema descriptions already detail both parameters. The tool description adds no new parameter information beyond what's in the schema.
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?
Clearly states it searches indexed B2B contacts by role, company, location, or technology. Distinct from siblings get_user_stats and verify_email.
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?
Provides guidance on when to use (searching leads) and recommends verify_email for further action. Lacks explicit when-not-to-use but implies context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Check email deliverability in real-time: MX records, SMTP, disposable/role detection. Read-only. Requires API key. Rate limit: 30/min per user. Use after search_leads or before sending campaigns. Returns deliverability score and risk assessment.
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | Single email address to verify. Must be a valid RFC-like address format. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses read-only nature, API key requirement, and rate limit (30/min per user) without any annotations. Also describes return value (deliverability score and risk assessment).
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?
Concise, packing core purpose, behavior, guidelines, and return info into a few sentences. No wasted words, well front-loaded.
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?
Covers all essential aspects for a simple tool: purpose, behavior, auth, rate limit, usage context, and return summary. No gaps.
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?
Input schema already provides 100% coverage with description for 'email' parameter. Description does not add additional semantic detail beyond the schema, so baseline 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?
Description clearly states 'Check email deliverability in real-time' with specific checks (MX records, SMTP, disposable/role detection). Differentiates from siblings like get_user_stats and search_leads by focusing on email verification.
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?
Explicitly says 'Use after search_leads or before sending campaigns', providing clear context. Lacks explicit exclusions or alternatives, but sufficiently guides usage.
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.
v1.0.6get_user_statssearch_leadsverify_emailv1.0.5get_user_statssearch_leadsverify_emailv0.1.0get_user_statssearch_leadsverify_emailScored across 3 tools
Each tool serves a distinct purpose: usage stats, lead searching, and email verification. No functional overlap.
All tool names follow a consistent verb_noun pattern (get_user_stats, search_leads, verify_email).
Three tools is well-scoped for a lead generation and verification service, covering essential operations without redundancy.
The set covers the full workflow: check quota, search leads, and verify email deliverability. No missing critical operations given the read-only nature.
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