JMeter MCP Server - Alternatives & Competitors

Ranked by Relevance

• 1
  

  locust-mcp-server

  Run Locust load tests via Model Context Protocol integration.

  locust-mcp-server provides a Model Context Protocol (MCP) server for executing Locust load tests, allowing seamless connection between Locust and AI-powered development environments. It offers easy configuration, real-time test output, and both headless and UI testing modes. The project features a simple API for customizable load testing scenarios and supports various runtime and user parameters.

  9 6 MCP
• 2
  

  VictoriaMetrics MCP Server

  Model Context Protocol server enabling advanced monitoring and observability for VictoriaMetrics.

  VictoriaMetrics MCP Server implements the Model Context Protocol (MCP) to provide seamless integration with VictoriaMetrics, allowing advanced monitoring, data exploration, and observability. It offers access to almost all read-only APIs, as well as embedded documentation for offline usage. The server facilitates comprehensive metric querying, cardinality analysis, alert and rule testing, and automation capabilities for engineers and tools.

  87 11 MCP
• 3
  

  k6-mcp-server

  A Model Context Protocol server for orchestrating k6 load tests via MCP-enabled clients.

  k6-mcp-server implements the Model Context Protocol, allowing users to execute and manage k6 load testing scripts through standardized MCP clients. It provides a simple API, supports custom test durations and virtual users, and offers real-time execution output. The system is configurable via environment variables and can be easily integrated into existing MCP-compatible tooling.

  17 8 MCP
• 4
  

  Optuna MCP Server

  Automated model optimization and analysis via the Model Context Protocol using Optuna.

  Optuna MCP Server is an implementation of the Model Context Protocol (MCP) that enables automated hyperparameter optimization and analysis workflows through Optuna. It acts as a server providing standardized tools and endpoints for creating studies, managing trials, and visualizing optimization results. The server facilitates integration with MCP clients and supports deployment via both Python environments and Docker. It streamlines study creation, metric management, and result handling using Optuna’s capabilities.

  65 21 MCP
• 5
  

  Maven Tools MCP Server

  Universal Maven Central dependency intelligence server for JVM build tools via the Model Context Protocol.

  Maven Tools MCP Server provides an MCP-compliant API delivering rich Maven Central dependency intelligence for JVM build tools like Maven, Gradle, SBT, and Mill. It enables AI assistants to instantly analyze, interpret, and recommend updates, health checks, and maintenance insights by reading maven-metadata.xml directly from Maven Central. With Context7 integration, it supports orchestration and documentation, enabling bulk analysis, stable version filtering, risk assessment, and rapid cached responses. Designed for seamless integration into AI workflows via the Model Context Protocol.

  14 2 MCP
• 6
  

  Jupyter MCP Server

  Real-time, context-aware MCP server for managing and interacting with Jupyter Notebooks.

  Jupyter MCP Server is an implementation of the Model Context Protocol (MCP) designed to enable AI-driven, real-time management and interaction with Jupyter Notebooks. It offers context-aware capabilities, smart execution features, and multimodal output handling, seamlessly integrating with JupyterLab and supporting multiple notebooks simultaneously. The server is compatible with any MCP client and can work with local or hosted Jupyter deployments.

  765 127 MCP
• 7
  

  MCP Server for ZenML

  Expose ZenML data and pipeline operations via the Model Context Protocol.

  Implements a Model Context Protocol (MCP) server for interfacing with the ZenML API, enabling standardized access to ZenML resources for AI applications. Provides tools for reading data about users, stacks, pipelines, runs, and artifacts, as well as triggering new pipeline runs if templates are available. Includes robust testing, automated quality checks, and supports secure connection from compatible MCP clients. Designed for easy integration with ZenML instances, supporting both local and remote ZenML deployments.

  32 10 MCP
• 8
  

  JVM MCP Server

  Lightweight multi-agent protocol server for JVM monitoring and diagnostics.

  JVM MCP Server provides a lightweight, zero-dependency server that implements the Multi-Agent Communication Protocol for monitoring and diagnosing Java applications. It leverages native JDK tools to enable powerful AI agent interactions for gathering JVM metrics, analyzing memory and threads, and performing advanced diagnostics without relying on third-party software. The server supports both local and remote Java environments through SSH, ensuring cross-platform compatibility and secure operation.

  71 15 MCP
• 9
  

  MCP Server for Data Exploration

  Interactive Data Exploration and Analysis via Model Context Protocol

  MCP Server for Data Exploration enables users to interactively explore and analyze complex datasets using prompt templates and tools within the Model Context Protocol ecosystem. Designed as a personal Data Scientist assistant, it facilitates the conversion of raw data into actionable insights without manual intervention. Users can load CSV datasets, run Python scripts, and generate tailored reports and visualizations through an AI-powered interface. The server integrates directly with Claude Desktop, supporting rapid setup and seamless usage for both macOS and Windows.

  503 63 MCP
• 10
  

  ORKL MCP Server

  A Model Context Protocol server for threat intelligence queries via the ORKL API.

  ORKL MCP Server is an implementation of the Model Context Protocol (MCP) designed for seamless integration with MCP-compatible applications. It enables secure querying of the ORKL API, offering tools to fetch and analyze threat reports, threat actors, and intelligence sources. The server streamlines access to detailed cyber threat data for security operations and research.

  45 6 MCP
• 11
  

  mcp-server-apache-airflow

  A Model Context Protocol server for integrating Apache Airflow with MCP clients.

  mcp-server-apache-airflow provides a Model Context Protocol (MCP) server implementation that allows standardized interaction with Apache Airflow environments. By wrapping Airflow's REST API, it enables MCP clients to manage and orchestrate workflows, DAGs, and runs in a consistent and interoperable manner. This implementation leverages the official Apache Airflow client library to ensure robust compatibility and maintainability. It streamlines the management of Airflow resources by exposing comprehensive endpoint coverage for key workflow operations.

  109 28 MCP
• 12
  

  omniparser-autogui-mcp

  Automated GUI analysis and interaction via the Model Context Protocol.

  omniparser-autogui-mcp is an MCP server that leverages OmniParser to analyze on-screen content and perform automated GUI operations. It integrates with clients such as Claude Desktop and can be configured via a detailed environment setup. The tool supports Windows and can delegate OmniParser processing to external devices, offering flexibility for complex contexts. Multiple environment variables allow customization of backend processing, target window selection, and communication methods, including SSE.

  58 11 MCP
• 13
  

  AutoMobile

  Powerful tools for mobile automation, test authoring, and device management via MCP.

  AutoMobile provides a comprehensive set of tools for mobile automation, focusing on UI testing and development workflow automation. It operates as an MCP Server, enabling a robust interaction loop for model-driven actions and observations. The solution supports Android platforms with features like automated test authoring, multi-device management, and seamless CI test execution. AutoMobile also offers source mapping and deep view hierarchy analysis to enhance code rendering accuracy.

  63 8 MCP
• 14
  

  MCP Internet Speed Test

  Standardized internet speed and network performance testing for AI models via MCP.

  MCP Internet Speed Test implements the Model Context Protocol (MCP) to enable AI models and agents to measure, analyze, and report diverse network performance metrics through a standardized interface. It supports download, upload, latency, jitter, and cache analysis, along with multi-CDN and geographic location detection. By offering an MCP-compatible server with robust testing features, it allows seamless integration with LLMs and AI tools for real-time network assessment and diagnostics.

  11 7 MCP
• 15
  

  MCP System Monitor

  Real-time system metrics for LLMs via Model Context Protocol

  MCP System Monitor exposes real-time system metrics, such as CPU, memory, disk, network, host, and process information, through an interface compatible with the Model Context Protocol (MCP). The tool enables language models to retrieve detailed system data in a standardized way. It supports querying various hardware and OS statistics via structured tools and parameters. Designed with LLM integration in mind, it facilitates context-aware system monitoring for AI-driven applications.

  73 17 MCP
• 16
  

  ScreenMonitorMCP v2

  Real-time screen monitoring and visual analysis for AI assistants via MCP.

  ScreenMonitorMCP v2 is a Model Context Protocol (MCP) server enabling AI assistants to capture, analyze, and interact with screen content in real time. It supports instant screenshots, live streaming, advanced vision-based analysis, and provides performance monitoring across Windows, macOS, and Linux. Integration with clients like Claude Desktop is streamlined, offering easy configuration and broad compatibility. The tool leverages AI vision models to provide intelligent insights into screen content and system health.

  64 14 MCP
• 17
  

  Zaturn

  Your Co-Pilot For Data Analytics & Business Insights

  Zaturn enables AI models to interact with multiple data sources and generate analytics without requiring users to write SQL or Python code. It supports SQL databases and file formats, providing visual and tabular summaries and offering an interactive web interface similar to Jupyter Notebook. Zaturn can function both as a standalone platform or as a Model Context Protocol (MCP) compliant tool, allowing seamless context management for AI-driven data analysis.

  66 9 MCP
• 18
  

  SonarQube MCP Server

  Model Context Protocol server for AI access to SonarQube code quality metrics.

  SonarQube MCP Server offers a Model Context Protocol (MCP) server that integrates with SonarQube, enabling AI assistants to access code quality metrics, issues, and analysis results programmatically. It supports retrieving detailed quality metrics, filtering issues, reviewing security hotspots, analyzing branches and pull requests, and monitoring project health. The server facilitates multi-project analysis, contextual code review, and improved assistant workflows through a standardized protocol.

  101 16 MCP
• 19
  

  Markmap MCP Server

  Convert Markdown to interactive mind maps via the Model Context Protocol.

  Markmap MCP Server enables seamless conversion of Markdown content into interactive mind maps using the Model Context Protocol (MCP). It leverages the open-source markmap project and provides users with diverse export formats including PNG, JPG, and SVG. Designed for easy integration with MCP clients, it offers tools for automated browser previews, rich interactivity, and batch mind map generation. The server can be installed easily via npm or Smithery and supports configurable output directories.

  137 22 MCP
• 20
  

  VirusTotal MCP Server

  Security analysis server for VirusTotal with comprehensive relationship data, compatible with MCP-enabled applications.

  VirusTotal MCP Server is a Model Context Protocol server that interfaces with the VirusTotal API to deliver detailed security analysis of URLs, files, IPs, and domains. It provides comprehensive reports with automatically fetched relationship data, supporting rich security insights in a single request. Designed for seamless integration with MCP-compatible clients like Claude Desktop, it supports easy installation and flexible configuration options.

  88 12 MCP
• 21
  

  Data Visualization MCP Server

  MCP server for data visualization using Vega-Lite.

  Data Visualization MCP Server enables large language models to visualize data through a standardized interface using Vega-Lite specifications. The server provides tools for saving data tables and generating visualizations as text or PNG images. Integration with platforms like Claude Desktop allows seamless addition of data visualization capabilities to LLM workflows.

  92 25 MCP
• 22
  

  MCP Swagger Server (mss)

  Seamlessly convert OpenAPI/Swagger specs into Model Context Protocol tools for AI integration.

  MCP Swagger Server converts OpenAPI/Swagger API specifications into Model Context Protocol (MCP) compatible tools, enabling REST APIs to become directly callable by AI systems. It supports zero-configuration conversion, multiple transport protocols (SSE, Streamable, Stdio), and secure API access through Bearer Token authentication. The tool offers an interactive command-line interface and configuration options to filter operations, customize transports, and manage API security. Its modular structure includes OpenAPI parsing, web UI, and backend services.

  38 8 MCP
• 23
  

  Mindmap MCP Server

  Convert Markdown content into interactive mindmaps via an MCP-compliant server.

  Mindmap MCP Server provides a Model Context Protocol (MCP) compatible service that transforms Markdown input into interactive mindmap visualizations. It supports command-line, Python, and Docker installation methods for flexibility across platforms. Designed to integrate with MCP clients like Claude Desktop, it ensures seamless Markdown-to-mindmap conversion using markmap under the hood. The server is intended for easy plug-and-play use in model-powered workflows that require structured, visual context formatting.

  205 22 MCP
• 24
  

  Kaggle MCP Server

  Model Context Protocol server enabling Kaggle dataset search and download tools.

  Kaggle MCP Server implements the Model Context Protocol (MCP) using the fastmcp library and provides tools for searching and downloading datasets from Kaggle via a standardized MCP interface. It manages Kaggle API authentication, exposes search and download tools as MCP resources, and offers prompts for generating exploratory data analysis notebooks. The server can be run locally or via Docker, supporting easy integration with MCP clients and compliant applications.

  28 7 MCP
• 25
  

  Bugsnag MCP Server

  A Model Context Protocol server for AI-powered Bugsnag error monitoring and management.

  Bugsnag MCP Server provides a Model Context Protocol-compliant interface for AI tools to interact with Bugsnag, enabling advanced error monitoring, analysis, and management. It allows navigation of organizations and projects, filtering and investigation of errors and events, and detailed stacktrace and exception chain visualization. The server is designed for easy integration with LLM-powered agents like Cursor and Claude, supporting rich context retrieval and automated issue resolution workflows.

  18 5 MCP
• 26
  

  mcp-git-ingest

  MCP server for exploring GitHub repository structures and key files.

  mcp-git-ingest is a Model Context Protocol (MCP) server designed to programmatically read and visualize GitHub repository structures and retrieve important file contents. It leverages fastmcp for server functionality and gitpython for repository operations, ensuring robust error handling and cleanup. The tool offers commands to generate directory trees and fetch specified files, making it suitable for integrating repository context into AI workflows.

  286 38 MCP
• 27
  

  mcp-log-proxy

  Web-based proxy for inspecting Model Context Protocol traffic in real time.

  mcp-log-proxy enables users to observe and debug messages exchanged between MCP clients and servers through a user-friendly web interface. It supports the STDIO interface and can operate multiple proxy instances, each accessible via a web dashboard. The tool allows customization of ports, web page titles, and log file locations, making it suitable for managing and troubleshooting MCP-based model communication. Installation is straightforward via Homebrew or Go, and it supports real-time switching between different running proxies.

  26 3 MCP
• 28
  

  Webpage Screenshot MCP Server

  Capture web page screenshots programmatically for AI agent workflows.

  Webpage Screenshot MCP Server enables the capture of webpage and element screenshots using Puppeteer, providing a Model Context Protocol-compliant interface for AI agents. It supports various image formats, flexible authentication, and session persistence to facilitate integration with tools like Claude and Cursor. The server simplifies visual verification and monitoring of web applications by returning base64-encoded screenshots through customizable options. It also allows manual login workflows and multi-step web interactions with session continuity.

  44 4 MCP
• 29
  

  MCP Chess Server

  Play chess against any LLM via Model Context Protocol tools.

  MCP Chess Server enables interactive chess gameplay between users and any large language model (LLM) by exposing standardized model context protocol tools. Users can play chess, analyze games from PGN files, and visualize board states through a variety of programmatically accessible functions. The system supports move validation, game state visualization, turn detection, and position finding within PGN strings, making it suitable for both human and automated (AI/LLM-driven) play and analysis.

  14 6 MCP
• 30
  

  Calculator Server

  A high-precision Go server implementing 13 advanced mathematical and financial tools via the Model Context Protocol.

  Calculator Server is a Go-based implementation of the Model Context Protocol (MCP) designed to offer comprehensive mathematical computation services. It features 13 advanced tools including support for arithmetic, scientific, statistical, unit conversion, and financial calculations. The server provides high-precision operations, bulk processing for unit conversions, and sophisticated financial modeling capabilities, making it suitable for both scientific and financial applications.

  0 1 MCP
• 31
  

  @just-every/mcp-screenshot-website-fast

  Fast screenshot capture and tiling optimized for AI model workflows.

  Provides a fast and efficient command-line tool for capturing high-quality screenshots of webpages, specifically optimized for integration with AI vision workflows via the Model Context Protocol (MCP). Automates image tiling to 1072x1072 pixel chunks for optimal processing and compatibility with tools like Claude Vision API. Includes advanced features such as full-page capture, screencast recording, support for JavaScript injection, configurable viewports, and resource-efficient browser management.

  89 8 MCP
• 32
  

  MCP BaoStock Server

  Stock market data server with multiple APIs, powered by BaoStock.

  MCP BaoStock Server offers a stock data API service based on BaoStock, providing endpoints for retrieving diverse market information. It supports queries for stock basics, K-line historical data, industry classification, dividends, financial indicators, index data, and valuation metrics. Developed in Python, it is designed for easy integration and rapid access to comprehensive Chinese stock market data. The server enables detailed analysis and research with example test cases for each supported endpoint.

  56 19 MCP
• 33
  

  Currents MCP Server

  Connect AI agents to test results context via Currents MCP Server.

  Currents MCP Server provides a standardized Model Context Protocol (MCP) server for integrating test results and debugging data into AI agents. It enables seamless communication between CI test data in Currents and AI-powered tools, such as Cursor Editor and Claude Desktop, facilitating actions like test optimization and failure diagnosis. The server exposes a suite of tools for retrieving detailed project, run, and performance metrics and is easily configurable via command-line for development and integration. Secure handling of API keys and support for local development are included.

  14 6 MCP
• 34
  

  Prometheus MCP Server

  Access and analyze Prometheus metrics through standardized MCP interfaces.

  Prometheus MCP Server enables seamless access to Prometheus metrics by providing a standardized Model Context Protocol (MCP) interface. It allows AI assistants and compatible clients to execute PromQL queries, discover and explore metric data, and retrieve instant or range-based results. The server supports authentication via basic and bearer token mechanisms and can be easily deployed via Docker or integrated into multiple development environments.

  282 64 MCP
• 35
  

  VictoriaLogs MCP Server

  MCP server enabling advanced read-only access and observability for VictoriaLogs

  VictoriaLogs MCP Server implements the Model Context Protocol (MCP) to provide seamless, read-only integration with VictoriaLogs instances. It enables comprehensive access to VictoriaLogs APIs, allowing for log querying, exploration, and advanced observability tasks. The server includes embedded and searchable documentation and supports automation and interaction capabilities via standardized MCP tools. Designed to combine with other MCP servers, it enhances engineering workflows for log analysis and troubleshooting.

  30 7 MCP
• 36
  

  Druid MCP Server

  Comprehensive Model Context Protocol server for advanced Apache Druid management and analytics

  Druid MCP Server provides a fully MCP-compliant interface for managing, analyzing, and interacting with Apache Druid clusters. Leveraging tools, resources, and AI-assisted prompts, it enables LLM clients and AI agents to perform operations such as time series analysis, statistical exploration, and data management through standardized protocols. The server is built with a feature-based architecture, offers real-time communication via multiple transports, and includes automatic discovery and registration of MCP components.

  9 4 MCP
• 37
  

  Pica MCP Server

  A Model Context Protocol (MCP) server for seamless integration with 100+ platforms via Pica.

  Pica MCP Server provides a standardized Model Context Protocol (MCP) interface for interaction with a wide range of third-party services through Pica. It enables direct platform integrations, action execution, and intelligent intent detection while prioritizing secure environment variable management. The server also offers features such as code generation, form and data handling, and robust documentation for platform actions. It supports multiple deployment methods, including standalone, Docker, Vercel, and integration with tools like Claude Desktop and Cursor.

  8 5 MCP
• 38
  

  MCP-Twikit

  A Model Context Protocol server for Twitter search and interaction.

  MCP-Twikit is an MCP-compliant server that enables interaction with the Twitter platform via the Model Context Protocol. It supports functions such as searching tweets, analyzing sentiments across accounts, and retrieving a user's Twitter timeline. The tool is designed for integration with AI clients to facilitate structured, context-aware access to Twitter data.

  211 27 MCP
• 39
  

  QA Sphere MCP Server

  Model Context Protocol server enabling LLMs to interact with QA Sphere test cases

  QA Sphere MCP Server provides a Model Context Protocol (MCP) integration for QA Sphere, allowing Large Language Models to interact with, discover, and summarize test cases within the QA Sphere test management system. It enables AI-powered IDEs and MCP clients to reference and manipulate QA Sphere test case data within development workflows. The solution supports quick integration into clients like Claude, Cursor, and 5ire, facilitating seamless collaboration and context sharing for AI-assisted development.

  15 6 MCP
• 40
  

  VictoriaMetrics MCP Server

  Model Context Protocol server interface for VictoriaMetrics time-series database.

  VictoriaMetrics MCP Server provides a Model Context Protocol (MCP) compliant interface to interact with VictoriaMetrics. It enables structured data writing, Prometheus format imports, and advanced querying capabilities within the VictoriaMetrics platform. The tool supports installation via Smithery and CLI, facilitating flexible integration. It offers endpoints for writing metrics, querying time series, retrieving labels, and label values.

  7 5 MCP
• 41
  

  dicom-mcp

  A Model Context Protocol server for managing and querying DICOM medical imaging data.

  dicom-mcp enables AI assistants and tools to query, read, and transfer data on DICOM servers, such as PACS and VNA systems. It integrates with MCP-compatible clients, offering tooling for searching patient records, retrieving medical reports, and sending image data to analysis endpoints. Configurable via YAML, it streamlines operations on DICOM databases for research and development in medical imaging. It is explicitly designed for interoperability with LLM-based AI workflows.

  74 21 MCP
• 42
  

  Globalping MCP Server

  Enable AI models to run network tests globally via natural language.

  Globalping MCP Server implements the Model Context Protocol, enabling AI models to interface with a global network measurement platform through natural language. It allows AI clients to perform network diagnostic tests such as ping, traceroute, DNS, MTR, and HTTP from thousands of locations worldwide. The server offers AI-friendly context handling, detailed parameter descriptions, comparative analysis of network performance, and supports secure authentication using OAuth or API tokens.

  33 3 MCP
• 43
  

  mcp-code-runner

  A Docker-based code runner implementing the MCP protocol

  mcp-code-runner is a code execution service built on top of the Model Context Protocol (MCP). It enables users to execute code securely within Docker containers and retrieve the execution results. The tool is designed to support code execution use cases while adhering to the MCP standard for interoperability. A local Docker environment is required for operation.

  14 4 MCP
• 44
  

  mcp_mysql_server_pro

  Advanced MySQL server tool with Model Context Protocol support and database health analysis.

  mcp_mysql_server_pro enables seamless MySQL database operations and analysis, supporting all Model Context Protocol (MCP) transfer modes including STDIO, SSE, and Streamable HTTP. It provides flexible permission control, advanced anomaly detection, and health status monitoring, with easy extensibility via custom tools. OAuth2.0 authentication is supported, and users can execute multi-statement SQL queries, perform index and lock analysis, and leverage prompt template invocation.

  273 35 MCP
• 45
  

  Quarkus Model Context Protocol Servers

  Extensible Java-based servers implementing the Model Context Protocol for context-aware LLM integrations.

  Quarkus Model Context Protocol Servers offers a collection of Java-based servers implementing the Model Context Protocol (MCP) to extend the capabilities of language model applications. Built with the Quarkus MCP server framework, it enables integration with JDBC databases, JVM processes, file systems, JavaFX, Kubernetes, containers, and Wolfram Alpha. The project allows easy deployment and extension of context-aware services for AI applications via MCP. Its servers can be run across different environments using jbang and are easily extensible for new capabilities.

  176 46 MCP
• 46
  

  mcp-server-templates

  Deploy Model Context Protocol servers instantly with zero configuration.

  MCP Server Templates enables rapid, zero-configuration deployment of production-ready Model Context Protocol (MCP) servers using Docker containers and a comprehensive CLI tool. It provides a library of ready-made templates for common integrations—including filesystems, GitHub, GitLab, and Zendesk—and features intelligent caching, smart tool discovery, and flexible configuration options via JSON, YAML, environment variables, or CLI. Perfect for AI developers, data scientists, and DevOps teams, it streamlines the process of setting up and managing MCP servers and has evolved into the MCP Platform for enhanced capabilities.

  5 1 MCP
• 47
  

  MCP GitLab Jira Server

  MCP server for seamless GitLab and Jira integration

  MCP GitLab Jira Server acts as a bridge, enabling AI agents to interact programmatically with GitLab and Jira instances via the Model Context Protocol. It provides a standardized server interface for operations on projects, merge requests, pipelines, branches, issues, releases, and users in GitLab, as well as tickets and project management features in Jira. The server can be run as a CLI tool or in a Docker container, making it compatible with tools like gemini-cli. Configuration via environment variables allows secure authentication and flexible deployment.

  6 4 MCP
• 48
  

  Kestra Python MCP Server

  Run Kestra orchestrations with Model Context Protocol support via Docker.

  Kestra Python MCP Server enables integration of the Kestra workflow orchestration platform with environments that use the Model Context Protocol (MCP). It provides a Dockerized MCP server for managing workflows, executions, files, namespaces, and more, with support for both Open-Source (OSS) and Enterprise Edition (EE) setups. The server can be configured easily using environment variables and is compatible with tools like VS Code and Claude, making model-driven orchestration accessible and modular.

  16 3 MCP
• 49
  

  books-mcp-server

  A server implementation supporting Model Context Protocol integration with cherry-studio.

  books-mcp-server allows users to set up a Model Context Protocol (MCP) compliant server for managing and interacting with AI models. It enables integration with cherry-studio through STDIO commands and structured server configurations. The tool provides straightforward setup instructions and supports launching the server with customizable parameters, making it suitable for various AI context management tasks.

  5 2 MCP
• 50
  

  dbt MCP Server

  Bridge dbt projects and AI agents with rich project context.

  dbt MCP Server provides an implementation of the Model Context Protocol for dbt projects, enabling seamless integration between dbt and AI agents. It allows agents to access and understand the context of dbt Core, dbt Fusion, and dbt Platform projects. The tool supports connection to external AI products and offers resources for building custom agents. Documentation and examples are provided to facilitate adoption and integration.

  420 90 MCP