MCP Sunucuları
Model Context Protocol sunucuları için açık kayıt. AI agent'larınız için doğru araçları, kaynakları ve prompt'ları kategori, taşıma yöntemi veya kullanım alanına göre bulun.
Sunucular
187
Araçlar
493
Kategoriler
11
Katkıda bulunanlar
164
Google's official MCP server for Google Analytics 4. Lets AI agents run reports against the GA4 Data API, discover dimensions and metrics, and explore account and property metadata with server-side aggregation and safe defaults. Runs locally (via pipx) and connects to MCP-compatible clients for conversational analysis of website traffic and user behavior.
MCP server for SQLite database interaction and business intelligence. Enables AI agents to query SQLite databases, create and modify tables, run analytical queries, and generate insights from data. Supports read-write operations with transaction safety and provides schema introspection for understanding database structure.
Provides AI agents with access to ClickHouse analytical databases through the Model Context Protocol. Enables running analytical queries, exploring table schemas, inspecting materialized views, and monitoring query performance. Designed for OLAP workloads with support for large result sets and query profiling.
MCP server for Google BigQuery that lets AI agents explore datasets, inspect table schemas, and run SQL analytics queries with dry-run cost estimation. Useful for natural-language data analysis, ad-hoc reporting, and pipeline debugging against large-scale BigQuery warehouses.
Provides AI agents with access to PostHog product analytics through the Model Context Protocol. Enables querying events, analyzing funnels, inspecting feature flags, and reviewing session recordings metadata. Supports HogQL queries for advanced analytics and cohort analysis for user segmentation.
Official Snowflake MCP server enabling AI agents to query and analyze data in the Snowflake AI Data Cloud. Supports running SQL against warehouses, exploring databases and schemas, describing tables, and invoking Cortex AI services for search and analytics, with role-based access control honored end to end.
MCP server for DuckDB, the fast in-process analytical database. Lets AI agents run analytical SQL over local files (CSV, Parquet, JSON), attach databases, inspect schemas, and profile queries. Ideal for ad-hoc data analysis, ETL prototyping, and querying large columnar files without a separate database server.
Official Elastic MCP server that connects AI agents to Elasticsearch data using the Model Context Protocol. Enables natural language interactions with Elasticsearch indices — querying, analyzing, and retrieving data without custom APIs. Supports both stdio and streamable-HTTP transports, and works with Elasticsearch 8.x/9.x clusters including Elasticsearch Serverless. Distributed as a Docker container image from the Elastic registry.
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.
Fivetran's MCP server helps agents inspect data connectors and sync health, diagnose broken connections, and answer operational questions about managed ELT pipelines.
Google's official MCP server for the Google Ads API, exposing resources and tools that let agents analyze advertising accounts and support campaign operations.
GrowthBook's official MCP server for working with feature flags, experiments, and metrics so agents can safely support product experimentation workflows.
Metabase's built-in MCP server that lets AI clients connect directly to a Metabase instance, scoped to the connecting user's permissions. Enables agents to discover databases and models, run queries, and retrieve results and dashboards so teams can ask questions of their business intelligence data in natural language.
Official MCP server for DuckDB and MotherDuck. Lets AI assistants run SQL analytics directly against local DuckDB files, in-memory databases, S3-hosted data, and MotherDuck cloud warehouses. Supports read and write queries, browsing database catalogs, and switching between connections on the fly, making it well suited for conversational data exploration and lightweight analytics.
OpenBB's MCP server connects agents to financial market data, research, and analytics for evidence-based investment and business workflows.
The official OpenSearch Model Context Protocol server, enabling AI assistants to interact with OpenSearch clusters. Lets agents list indices, inspect mappings, run search and aggregation queries, and read basic cluster health so they can explore and analyze data stored in OpenSearch through natural language.
MCP server for interacting with a Tinybird Workspace from any MCP client. Lets AI agents explore data sources, call published API endpoints, run SQL queries over real-time data, and push datafiles, making Tinybird's analytics readily available to LLM-driven workflows.
Official Cloudflare MCP server for managing Cloudflare services. Enables AI agents to interact with Workers, KV namespaces, R2 storage, D1 databases, and DNS records. Supports deploying Workers scripts, managing environment variables, querying analytics, and configuring security settings across Cloudflare's edge network.
Official dbt Labs MCP server for analytics engineering workflows. Lets AI agents run dbt commands (build, run, test), inspect models and lineage via the dbt project, and query the Semantic Layer and Discovery API in dbt Cloud. Useful for transforming data, validating models, and answering metric questions grounded in governed definitions.
MCP server for Intercom. Lets AI agents search and read conversations and contacts, retrieve message history, and query help-center articles via the Intercom API. Useful for support analytics, conversation summarization, and building assistants that reason over customer communications.
Skills ve MCP sunucuları
aralarındaki fark nedir?Skills“ne yapılacağı”
Bir Skill; talimatları, örnek prompt'u ve önerilen modelleri paketleyerek agent'ın görevi tutarlı şekilde yapmasını sağlar. Skills yeni bağlantılar değil, bilgi ekler.
MCP sunucuları“nasıl bağlanılacağı”
Bir MCP sunucusu, gerçek sistemlere (veritabanları, API'ler ve dosyalar) bir taşıma yöntemi üzerinden bağlanarak agent'a yeni yetenekler kazandırır. MCP görev talimatları değil, bağlantılar ve eylemler ekler.
Kısa kural: modelin bir görevi iyi yapması gerekiyorsa Skill, bir araca veya sisteme erişmesi gerekiyorsa MCP sunucusu kullanın. Birlikte çalışabilirler; Skill, MCP sunucusunun sunduğu araçlardan yararlanabilir.
Bir MCP sunucusu mu geliştirdiniz?
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