Servidores MCP

El registro abierto de servidores Model Context Protocol. Encuentra herramientas, recursos y prompts para tus agentes de IA, filtrados por categoría, transporte o caso de uso.

Servidores

177

Herramientas

471

Categorías

11

Colaboradores

155

11 servidores

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MarkItDown MCPMicrosoft

Microsoft's MarkItDown MCP integration converts documents from HTTP, file, and data URIs into Markdown for agent-ready analysis and retrieval.

0
MCP Toolbox for DatabasesGoogle APIs

Google's MCP Toolbox provides secure, ready-made and custom tools for database queries, schema operations, and semantic search in agent workflows.

0
Excel MCP ServerHaris Musa

MCP server for reading and writing Excel workbooks without needing Microsoft Excel installed. Lets AI agents create workbooks and worksheets, read and write cell ranges, apply formulas and formatting, and build charts and pivot tables programmatically. Useful for automating spreadsheet generation, reporting, and data entry from an assistant.

0
Pulumi MCP ServerPulumi

Pulumi's official MCP server for AI-assisted Infrastructure as Code. Wraps the Pulumi Automation and Cloud APIs so agents can preview and deploy stacks, read stack outputs, inspect resources, and look up provider/resource schemas from the Pulumi Registry. Helps developers codify cloud architectures and review infrastructure diffs from within an AI coding assistant.

0
Jenkins MCP ServerJenkins Community

MCP server for Jenkins CI/CD. Enables AI agents to trigger builds, inspect job and build status, stream console logs, and diagnose failing pipelines, bringing continuous integration workflows into AI-powered development environments.

198
Milvus MCP ServerZilliz

Official MCP server for the Milvus vector database. Lets AI agents create collections, insert vectors, and run similarity and scalar-filtered searches over large-scale embedding data, enabling retrieval and long-term memory for AI applications.

356
Semgrep MCP ServerSemgrep

Official Semgrep MCP server for static application security testing. Lets AI agents scan code for security vulnerabilities and bugs, run custom rules, and return findings with severity and remediation guidance, embedding SAST into AI-powered development workflows.

512
Asana MCP ServerAsana

Official Asana MCP server that connects AI tools to the Asana Work Graph. Enables agents to create and update tasks, manage projects and sections, add comments, search work, and summarize project status via a remote OAuth-secured endpoint.

760
Zapier MCP ServerZapier

Official Zapier MCP server that exposes thousands of app integrations and Zap actions to AI agents through a single remote endpoint. Lets agents trigger automations and perform actions across apps like Gmail, Slack, Google Sheets, and Salesforce without building custom integrations, with per-action scoping configured in the Zapier dashboard.

1.2k
Grafana MCP ServerGrafana Labs

MCP server for Grafana's observability platform. Enables AI agents to query metrics from Prometheus, search and analyze logs from Loki, query traces, list and manage dashboards, and investigate incidents. Useful for debugging production issues, building monitoring dashboards, and performing root cause analysis with AI assistance across the full Grafana LGTM stack.

2.1k
Qdrant MCP ServerQdrant

Official MCP server for Qdrant vector search engine. Acts as a semantic memory layer enabling AI agents to store and retrieve information using vector similarity search. Supports storing text with metadata, semantic querying, configurable embedding models via FastEmbed, and both cloud-hosted and local Qdrant instances. Useful for building RAG pipelines, code search, knowledge bases, and long-term agent memory.

1.4k

Skills frente a servidores MCP

¿cuál es la diferencia?

Skillsel «qué hacer»

Una Skill reúne conocimientos prácticos —instrucciones, un prompt de ejemplo y modelos recomendados— para que un agente realice una tarea de forma consistente. Las Skills aportan conocimiento, no nuevas conexiones.

Servidores MCPel «cómo conectarse»

Un servidor MCP proporciona nuevas capacidades a un agente conectándolo con sistemas reales —bases de datos, API o archivos— mediante un transporte. MCP añade conexiones y acciones, no instrucciones de tarea.

Regla práctica: usa una Skill cuando necesites que el modelo realice bien una tarea y un servidor MCP cuando necesites conectarlo con una herramienta o sistema. Se complementan: una Skill puede utilizar las herramientas que proporciona un servidor MCP.

¿Has creado un servidor MCP?

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