MCP Sunucuları

MCP server for the Railway deployment platform. Lets AI agents create projects and services, deploy from repositories, manage environment variables, view deployment logs, and inspect service status. Useful for provisioning backends, databases, and cron jobs and for debugging deploys directly from an AI assistant.

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.

Official Linear MCP server for project management integration. Enables AI agents to find, create, and update issues, projects, and comments in Linear. Supports searching issues by status, assignee, or label, creating new issues with full metadata, and managing project workflows directly from AI-powered development environments.

MCP server for the Wolfram Alpha computational knowledge engine. Gives AI agents access to step-by-step math, symbolic computation, unit conversions, scientific data, and curated facts across physics, chemistry, finance, and more. Useful for grounding quantitative answers and offloading precise computation from the model.

Official DigitalOcean MCP server for managing cloud infrastructure. Lets AI agents deploy and manage App Platform apps, Droplets, databases, and Spaces object storage, and read logs and metrics. Useful for provisioning and operating cloud resources and debugging deployments through an AI assistant.

Model Context Protocol üzerinden PostgreSQL veritabanlarına salt okunur erişim sağlar. AI agent'ların veritabanı şemalarını incelemesine, SELECT sorguları çalıştırmasına ve tablo yapılarını keşfetmesine olanak tanır. Verilerin yanlışlıkla değiştirilmesini önlemek için salt okunur transaction isolation kullanır. Daha önce referans sunucu paketinin parçasıydı; artık arşivlenmiştir ve servers-archived altında bulunur.

Official Plaid MCP server for financial data connectivity. Lets AI agents work with Plaid's APIs to retrieve accounts, balances, and transactions, and to build and debug integrations for banking, payments, and identity. Useful for fintech development, personal finance tooling, and automating account data workflows.

Official Box MCP server for enterprise content management. Lets AI agents search files, read documents, extract text and metadata, ask questions with Box AI, and manage folders via the Box API. Useful for document analysis, knowledge retrieval, and automating content workflows over files stored in Box.

Algolia's MCP server for interacting with the Algolia search platform through AI tools. Lets agents run searches against indices, inspect and manage index settings and records, and review analytics and monitoring data using natural language. Useful for building, tuning, and debugging search experiences powered by Algolia.

Apache Doris' MCP server provides agents with governed access to Doris analytics databases for schema discovery, query assistance, and operational investigation.

Apache IoTDB's MCP server connects agents to time-series data and metadata for operational analysis, industrial telemetry exploration, and query assistance.

Apache SkyWalking's MCP server gives agents access to observability data for tracing, service topology, metrics, logs, and production incident investigation.

DataStax's official MCP server for Astra DB, a serverless database built on Apache Cassandra with native vector search. Lets AI agents create and manage collections, insert and update records, and run similarity and metadata queries, making it a convenient backend for retrieval-augmented generation and agent memory workloads.

Cloudinary's official MCP servers for managing media through conversational AI. Cover the full media workflow: uploading and transforming images and videos, organizing assets with structured metadata, configuring processing pipelines, and running AI-powered content analysis. Available as remote OAuth endpoints or local npx processes across several focused servers (asset management, environment config, structured metadata, and analysis).

A Model Context Protocol server that provides a natural-language interface for LLMs and agents to manage, monitor, and query data in CockroachDB. Supports schema exploration, query plan inspection, and running SQL, with a read-only-by-default posture so agents can investigate a distributed SQL cluster safely.

Confluent's open-source MCP server that connects AI assistants to Confluent Cloud, Confluent Platform, and standalone Apache Kafka deployments. Provides tools to manage Kafka topics and connectors, work with Schema Registry, and run Flink SQL statements through natural language, helping teams operate streaming data platforms from an MCP client.

Community-supported MCP server from the Couchbase ecosystem that lets AI assistants interact with data in Couchbase clusters and Capella. Exposes tools to browse scopes and collections, run SQL++ (N1QL) queries, and read or modify documents, with authentication and safety controls enforced by the server. Useful for conversational data exploration and operational queries against Couchbase.

Dagster's MCP integration enables agents to inspect and operate data assets, jobs, schedules, and runs in modern data platforms.

Dynatrace's official MCP server that brings the Dynatrace observability platform into AI workflows. Lets assistants query problems and vulnerabilities, run DQL against logs, metrics, and traces, inspect entities, and pull real-time monitoring data directly into a developer's coding environment for faster troubleshooting and root-cause analysis.

E2B's MCP server gives AI agents the ability to run arbitrary code in secure, isolated cloud sandboxes. Each sandbox is a fast-booting micro-VM where models can execute Python and shell commands, install packages, read and write files, and capture stdout/stderr — ideal for code interpretation, data analysis, and agentic workflows that need real execution.

Fivetran's MCP server helps agents inspect data connectors and sync health, diagnose broken connections, and answer operational questions about managed ELT pipelines.