Un servidor del Model Context Protocol (MCP) que conecta asistentes de IA con la plataforma de generación de leads B2B Leadloadz.
Buscar leads — Encuentra leads B2B verificados usando consultas en lenguaje natural
Verificar correo electrónico — Verificación de correo electrónico en tiempo real con puntuación de entregabilidad
Obtener estadísticas — Consulta tu uso y las cuotas restantes
Related MCP server: LeadClaw
No requiere instalación. Los clientes de IA pueden ejecutar el servidor directamente:
npx -y @leadloadz/mcp-servernpm install -g @leadloadz/mcp-server
leadloadz-mcpNecesitas una clave de API de Leadloadz para usar este servidor.
Regístrate en leadloadz.com
Ve a Dashboard → API Tokens
Genera un nuevo token
Copia el valor del token
Añádelo a tu claude_desktop_config.json:
{
"mcpServers": {
"leadloadz": {
"command": "npx",
"args": ["-y", "@leadloadz/mcp-server"],
"env": {
"LEADLOADZ_API_KEY": "tu-clave-api-aqui"
}
}
}
}Añádelo a tus ajustes de MCP de Cline:
{
"mcpServers": {
"leadloadz": {
"command": "npx",
"args": ["-y", "@leadloadz/mcp-server"],
"env": {
"LEADLOADZ_API_KEY": "tu-clave-api-aqui"
}
}
}
}Cualquier cliente MCP que soporte transporte stdio puede usar:
{
"command": "npx",
"args": ["-y", "@leadloadz/mcp-server"],
"env": {
"LEADLOADZ_API_KEY": "tu-clave-api-aqui"
}
}Variable | Requerido | Predeterminado | Descripción |
| Sí | — | Tu token de API de Leadloadz |
| No |
| URL base de la API |
| No |
| Tiempo de espera de la solicitud en milisegundos |
# Instalar dependencias
npm install
# Construir
npm run build
# Comprobación de tipos
npm run typecheck
# Probar localmente
node dist/index.jsPublica una nueva versión siempre que:
Añadas nuevas herramientas o cambies esquemas de herramientas existentes
Cambies el comportamiento de un endpoint de la API que afecte a las respuestas de MCP
Corrijas errores en el código del servidor MCP
Actualices dependencias (especialmente @modelcontextprotocol/sdk)
Cambies variables de entorno u opciones de configuración
NO publiques por cambios en:
La aplicación web principal de Leadloadz (es una base de código separada)
Rutas de API en la aplicación Next.js (el servidor MCP actúa como proxy hacia ellas)
Esquemas de base de datos (gestionados por la aplicación principal)
Componentes de UI o páginas de marketing
Edita los archivos en src/ según sea necesario. Prueba localmente:
npm run build
npm testnpm version patch # para correcciones de errores
npm version minor # para nuevas funciones
npm version major # para cambios disruptivosSi cambiaste la versión, actualiza server.json para que coincida:
{
"version": "1.0.X",
"packages": [
{
"version": "1.0.X"
}
]
}git add .
git commit -m "Describe tus cambios"
git push origin masterecho "//registry.npmjs.org/:_authToken=TU_TOKEN_NPM" > .npmrc
npm publish --access public
rm -f .npmrcNota: El token de npm comienza con npm_. Mantenlo seguro y nunca lo confirmes en el repositorio.
El Registro MCP de Anthropic debe actualizarse siempre que publiques una nueva versión de npm:
# Iniciar sesión (el token caduca, por lo que es posible que debas hacerlo cada vez)
./mcp-publisher login github
# Sigue el flujo de autenticación del dispositivo:
# 1. Ve a https://github.com/login/device
# 2. Introduce el código mostrado
# 3. Autoriza la aplicación
# Publicar
./mcp-publisher publishCrítico: El mcpName en package.json DEBE coincidir exactamente con el name en server.json (distingue entre mayúsculas y minúsculas). Actualmente ambos usan io.github.Ali1041/leadloadz.
Plataforma | URL | Propósito |
npm | Distribución del paquete | |
GitHub | Código fuente | |
Registro MCP de Anthropic | Directorio oficial de Anthropic | |
Glama.ai | Directorio comunitario | |
PulseMCP | Directorio comunitario | |
Smithery.ai | Directorio comunitario | |
MCP.Directory | Directorio comunitario |
Error "Token expired":
Vuelve a ejecutar ./mcp-publisher login github
Error "You do not have permission":
Asegúrate de que el nombre en server.json coincida con tu nombre de usuario de GitHub: io.github.Ali1041/leadloadz
Asegúrate de que el mcpName en package.json coincida exactamente
Error "Validation failed":
La descripción debe ser ≤ 100 caracteres
Todos los campos requeridos en server.json deben estar presentes
El paquete npm ya debe estar publicado con la versión coincidente
Tu clave de API nunca se registra ni se expone en mensajes de error
Todos los errores se desinfectan para evitar fugas de información
El servidor se comunica directamente con las API de Leadloadz a través de HTTPS
Los límites de tasa son aplicados por la API de Leadloadz
Sitio web: leadloadz.com
Problemas: GitHub Issues
Correo electrónico: support@leadloadz.com
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.
MCP server for Tomba email finder, verification, and contact enrichment API
Managed LinkedIn MCP server for AI agents: search, connect, message and enrich on accounts you own.
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