mcp-log-proxy alternatives

1

ws-mcp

WebSocket bridge for MCP stdio servers.

ws-mcp wraps Model Context Protocol (MCP) stdio servers with a WebSocket interface, enabling seamless integration with web-based clients and tools. It allows users to configure and launch multiple MCP servers via a flexible configuration file or command-line arguments. The tool is designed to be compatible with services such as wcgw, fetch, and other MCP-compliant servers, providing standardized access to system operations, HTTP requests, and more. Integration with tools like Kibitz enables broader applications in model interaction workflows.

19 7 MCP

2

MyMCP Server (All-in-One Model Context Protocol)

Powerful and extensible Model Context Protocol server with developer and productivity integrations.

MyMCP Server is a robust Model Context Protocol (MCP) server implementation that integrates with services like GitLab, Jira, Confluence, YouTube, Google Workspace, and more. It provides AI-powered search, contextual tool execution, and workflow automation for development and productivity tasks. The system supports extensive configuration and enables selective activation of grouped toolsets for various environments. Installation and deployment are streamlined, with both automated and manual setup options available.

93 9 MCP

3

mcp-cli

A command-line inspector and client for the Model Context Protocol

mcp-cli is a command-line interface tool designed to interact with Model Context Protocol (MCP) servers. It allows users to run and connect to MCP servers from various sources, inspect available tools, resources, and prompts, and execute commands non-interactively or interactively. The tool supports OAuth for various server types, making integration and automation seamless for developers working with MCP-compliant servers.

391 31 MCP

4

Confluence Communication Server MCP Server

Seamlessly interact with Confluence using standardized MCP tools.

Confluence Communication Server MCP Server is a TypeScript-based implementation that enables seamless interaction with Confluence through the Model Context Protocol. It provides tools for running CQL queries, retrieving, and updating Confluence page content, thus showcasing and adhering to core MCP concepts. The server is compatible with Claude Desktop and supports installation via Smithery, emphasizing ease of integration and automation for Confluence management tasks.

13 6 MCP

5

Vibe Check MCP

Plug & play agent oversight tool to keep LLMs aligned, reflective, and safe.

Vibe Check MCP provides a mentor layer over large language model agents to prevent over-engineering and promote optimal, minimal pathways. Leveraging research-backed oversight, it integrates seamlessly as an MCP server with support for STDIO and streamable HTTP transport. The platform enhances agent reliability, improves task success rates, and significantly reduces harmful actions. Designed for easy plug-and-play with MCP-aware clients, it is trusted across multiple MCP platforms and registries.

315 36 MCP

6

mcp-miro

Model Context Protocol server for integrating MIRO Whiteboard with AI workflows.

mcp-miro is a Model Context Protocol (MCP) compliant server that connects the MIRO Whiteboard Application to AI-based systems, such as Claude Desktop. It enables board manipulation, sticky note creation, bulk operations, and more through standardized MCP interfaces. Users can authenticate via OAuth and interact with MIRO boards programmatically for collaborative whiteboarding and automation tasks. The server can be installed using Smithery or mcp-get and supports debugging with the MCP Inspector.

97 31 MCP

7

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

8

mcp-access-point

Bridge HTTP services with Model Context Protocol (MCP) clients seamlessly.

MCP Access Point acts as a lightweight gateway that enables direct communication between MCP-compatible clients and traditional HTTP services without requiring server-side modifications. Built on the high-performance Pingora proxy library, it supports protocol conversion between HTTP, SSE, and MCP, supporting multi-tenancy and customizable routing. It empowers various MCP clients, such as Cursor Desktop, MCP Inspector, and VS Code, to interact with existing APIs efficiently. Configuration is flexible via YAML, and deployment is possible both locally and through Docker.

118 21 MCP

9

pluggedin-mcp-proxy

Unified proxy server for Model Context Protocol data exchanges and AI integrations

Aggregates multiple Model Context Protocol (MCP) servers into a single, unified proxy interface, supporting real-time discovery, management, and orchestration of AI model resources, tools, and prompts. Enables seamless interaction between MCP clients such as Claude, Cline, and Cursor, while integrating advanced document search, AI document exchange, and workspace management. Provides flexible transport modes (STDIO and Streamable HTTP), robust authentication, and comprehensive security measures for safe and scalable AI data exchange.

87 15 MCP

10

MCP Router

A Unified MCP Server Management App

MCP Router is a cross-platform desktop application designed to simplify the management of Model Context Protocol (MCP) servers. It enables users to centrally manage, organize, and monitor multiple MCP servers, both locally and remotely, with support for various connection methods. The app offers advanced context organization through Projects and Workspaces, as well as tools toggling and comprehensive logging. With a focus on privacy, all data is stored locally, and integration capabilities allow seamless connection with popular AI tools.

1,078 95 MCP

11

Last9 MCP Server

Enables AI agents to access real-time production observability data for automated code fixes.

Last9 MCP Server is an implementation of the Model Context Protocol (MCP) designed to provide seamless integration between AI agents and production observability data. It allows tools and agents to fetch live logs, metrics, traces, events, and alerts from Last9 systems, supporting a range of development environments and IDEs. This enables faster debugging, automated code fixes, and insightful context directly within local development workflows.

46 8 MCP

12

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

13

1mcp-app/agent

A unified server that aggregates and manages multiple Model Context Protocol servers.

1MCP Agent provides a single, unified interface that aggregates multiple Model Context Protocol (MCP) servers, enabling seamless integration and management of external tools for AI assistants. It acts as a proxy, managing server configuration, authentication, health monitoring, and dynamic server control with features like asynchronous loading, tag-based filtering, and advanced security options. Compatible with popular AI development environments, it simplifies setup by reducing redundant server instances and resource usage. Users can configure, monitor, and scale model tool integrations across various AI clients through easy CLI commands or Docker deployment.

96 14 MCP

14

Kubernetes MCP Server

A standardized MCP interface for Kubernetes cluster management and introspection.

Kubernetes MCP Server enables interaction with Kubernetes clusters via the Model Context Protocol, providing a consistent and standardized interface across various tools and environments. It features resource discovery, detailed inspection, metrics retrieval, resource manipulation, and supports multiple communication modes such as stdio, SSE, and streamable HTTP. Designed for flexibility and security, it allows both read-only and full-access modes and works with different Kubernetes contexts.

117 21 MCP

15

sentry-mcp

Remote MCP middleware for developer workflow and debugging tools.

sentry-mcp provides a remote Model Context Protocol server designed as middleware for Sentry's API, specifically optimized for human-in-the-loop coding agents and developer-oriented workflows. It enables integration with coding assistants like Cursor and Claude Code, offering both remote and stdio transports for varied environments, including self-hosted instances. The project also supports AI-powered search tools for querying events and issues, leveraging OpenAI API for natural language processing. Additionally, an Inspector tool is included for service testing and integration validation.

424 51 MCP

16

mcp-k8s-eye

Kubernetes management and diagnostics tool with MCP protocol support.

mcp-k8s-eye enables users to manage and analyze Kubernetes clusters using standardized Model Context Protocol (MCP) interfaces. It offers comprehensive resource operations, diagnostics, and resource usage monitoring through both stdio and SSE transports. Supporting generic and custom resource management along with advanced diagnostic tooling, it is geared for integration with AI clients and other MCP consumers.

26 9 MCP

17

Teamwork MCP Server

Seamless Teamwork.com integration for Large Language Models via the Model Context Protocol

Teamwork MCP Server is an implementation of the Model Context Protocol (MCP) that enables Large Language Models to interact securely and programmatically with Teamwork.com. It offers standardized interfaces, including HTTP and STDIO, allowing AI agents to perform various project management operations. The server supports multiple authentication methods, an extensible toolset architecture, and is designed for production deployments. It provides read-only capability for safe integrations and robust observability features.

11 9 MCP

18

PMCP

Golang Model Context Protocol server for natural language Prometheus queries

PMCP implements a Model Context Protocol (MCP) server in Go, enabling natural language access and manipulation of Prometheus metrics. It maintains full consistency with the Prometheus HTTP API and supports a robust, type-safe interface for seamless integration with MCP-compatible clients. The server offers complete Prometheus API coverage and supports multiple transport methods, including HTTP and Server-Sent Events. Its modular architecture is designed for performance, extensibility, and effective error handling.

3 1 MCP

19

YAMCP

Unified management and orchestration of Model Context Protocol servers via a local gateway workspace.

YAMCP is a command-line tool that enables organizing and managing multiple MCP (Model Context Protocol) servers as unified workspaces. It allows users to connect to various local or remote MCP servers, group them by functionality or application, and expose them as a single MCP server gateway for AI applications. The tool simplifies monitoring and debugging by centralizing server communication logs and provides workspace management and runtime control. YAMCP facilitates seamless integration with AI applications by providing a consolidated configuration and context management interface.

57 9 MCP

20

metoro-mcp-server

Bridge Kubernetes observability data to LLMs via the Model Context Protocol.

Metoro MCP Server is an implementation of the Model Context Protocol (MCP) that enables seamless integration between Kubernetes observability data and large language models. It connects Metoro’s eBPF-based telemetry APIs to LLM applications such as the Claude Desktop App, allowing AI systems to query and analyze Kubernetes clusters. This solution supports both authenticated and demo modes for accessing real-time cluster insights.

45 12 MCP

21

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

22

Opik MCP Server

A unified Model Context Protocol server for Opik with multi-transport IDE integration.

Opik MCP Server is an open-source implementation of the Model Context Protocol (MCP) designed for the Opik platform. It enables seamless integration with compatible IDEs and provides a unified interface to manage Opik's features such as prompts, projects, traces, and metrics. Supporting multiple transport mechanisms like stdio and experimental SSE, it simplifies workflow integration and platform management for LLM applications. The tool aims to streamline development and monitoring by offering standardized access and control over Opik's capabilities.

182 27 MCP

23

McGravity

Unified load balancer and proxy for multiple MCP servers

McGravity acts as a scalable unified proxy and load balancer for multiple MCP (Model Context Protocol) servers. It allows clients to connect through a single endpoint to access and manage multiple MCP servers efficiently. The tool offers load balancing, configuration via YAML, CLI and Docker support, and plans to evolve with features such as health checks and a web interface. Designed for modern GenAI infrastructure, it simplifies connection, balancing, and scalability of MCP server deployments.

68 3 MCP

24

MCP Server for TheHive

Connect AI-powered automation tools to TheHive incident response platform via MCP.

MCP Server for TheHive enables AI models and automation clients to interact with TheHive incident response platform using the Model Context Protocol. It provides tools to retrieve and analyze security alerts, manage cases, and automate incident response operations. The server facilitates seamless integration by exposing these functionalities over the standardized MCP protocol through stdio communication. It offers both pre-compiled binaries and a source build option with flexible configuration for connecting to TheHive instances.

11 3 MCP

25

Parallel Search MCP

Integrate Parallel Search API with any MCP-compatible LLM client.

Parallel Search MCP provides an interface to use the Parallel Search API seamlessly from any Model Context Protocol (MCP)-compatible language model client. It serves as a proxy server that connects requests to the search API, adding the necessary support for authentication and MCP compatibility. The tool is designed for everyday web search tasks and facilitates easy web integration for LLMs via standardized MCP infrastructure.

3 2 MCP

26

PostHog MCP

Easily deploy and manage Model Context Protocol servers across multiple platforms.

PostHog MCP provides a server implementation for the Model Context Protocol, now maintained within the PostHog monorepo. It enables quick deployment for enhanced model context management across editors like Cursor, Claude, Claude Code, VS Code, and Zed. Users can install the MCP server with a single command, streamlining integration for large language model workflows. Documentation and further details are provided through official PostHog resources.

138 23 MCP

27

MCP CLI

A powerful CLI for seamless interaction with Model Context Protocol servers and advanced LLMs.

MCP CLI is a modular command-line interface designed for interacting with Model Context Protocol (MCP) servers and managing conversations with large language models. It integrates with the CHUK Tool Processor and CHUK-LLM to provide real-time chat, interactive command shells, and automation capabilities. The system supports a wide array of AI providers and models, advanced tool usage, context management, and performance metrics. Rich output formatting, concurrent tool execution, and flexible configuration make it suitable for both end-users and developers.

1,755 299 MCP

28

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

29

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

30

MCP Status Observer

Monitor and query real-time operational status of digital platforms using Model Context Protocol.

MCP Status Observer enables real-time monitoring and querying of service status for major digital platforms and AI providers through the Model Context Protocol (MCP). It supports integration with tools like Claude Desktop for streamlined status checks, incident tracking, and impact analysis across a range of platforms including GitHub, Slack, OpenAI, and Cloudflare. The tool provides detailed component-level insights, incident histories, and resolution statuses, empowering rapid awareness of operational issues and outages.

5 7 MCP

31

Binary Ninja MCP

Seamlessly integrate Binary Ninja with Model Context Protocol clients for enhanced reverse engineering.

Binary Ninja MCP enables real-time integration of Binary Ninja's reverse engineering environment with various Model Context Protocol (MCP) clients. It acts as a server exposing Binary Ninja's capabilities via HTTP endpoints and includes a bridge to connect to MCP clients. The extension supports auto-setup with popular clients such as Cline, Claude Desktop, Roo Code, and others, streamlining the use of AI-assisted workflows. This enhances tasks such as analyzing binaries, switching targets, and leveraging LLM-driven automation in reverse engineering.

112 35 MCP

32

mcpmcp-server

Seamlessly discover, set up, and integrate MCP servers with AI clients.

mcpmcp-server enables users to discover, configure, and connect MCP servers with preferred clients, optimizing AI integration into daily workflows. It supports streamlined setup via JSON configuration, ensuring compatibility with various platforms such as Claude Desktop on macOS. The project simplifies the connection process between AI clients and remote Model Context Protocol servers. Users are directed to an associated homepage for further platform-specific guidance.

17 6 MCP

33

Dexscreener MCP server

MCP-compliant server for accessing the Dexscreener API.

Dexscreener MCP server provides a basic Model Context Protocol (MCP) interface to the Dexscreener API, allowing integration with tools like Claude Desktop. It supports both STDIO and server-sent events (SSE) modes and facilitates contextual API access based on the latest Dexscreener documentation. Configuration is straightforward for users on both MacOS and Windows, and the server can be tested using Inspector or other MCP-compatible clients.

16 4 MCP

34

WebSearch-MCP

Real-time web search for AI assistants via Model Context Protocol.

WebSearch-MCP is a Model Context Protocol (MCP) server that enables real-time web search capabilities for AI assistants through the stdio transport. It connects with a web crawler API to retrieve up-to-date search results and serves these results to AI models like Claude. The solution offers straightforward configuration and seamless integration with various MCP clients, enhancing AI model access to current and relevant external information.

19 7 MCP

35

mcp-stockfish

A Model Context Protocol server that connects AI systems to the Stockfish chess engine.

mcp-stockfish provides a server implementing the Model Context Protocol (MCP) to enable seamless integration between AI models and the Stockfish chess engine. It supports multiple concurrent sessions, full UCI command support, and offers both stdio and HTTP server modes. Built for robust, concurrent usage, it handles session and command management, exposes a JSON-based API response, and offers Docker support for easy deployment.

4 5 MCP

36

MCP Language Server

Bridge codebase navigation tools to AI models using MCP-enabled language servers.

MCP Language Server implements the Model Context Protocol, allowing MCP-enabled clients, such as LLMs, to interact with language servers for codebase navigation. It exposes standard language server features—like go to definition, references, rename, and diagnostics—over MCP for seamless integration with AI tooling. The server supports multiple languages by serving as a proxy to underlying language servers, including gopls, rust-analyzer, and pyright.

1,256 94 MCP

37

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

38

Tilt MCP Server

Programmatic Access to Tilt via Model Context Protocol for LLMs

Tilt MCP Server provides Model Context Protocol (MCP) capabilities to enable seamless integration between Tilt—an environment for managing Docker/Kubernetes workloads—and large language model (LLM) applications. It allows LLMs and AI assistants to interact programmatically with Tilt resources, retrieve logs, monitor status, trigger actions, and utilize guided workflows. The server exposes standardized resources, tools, and prompts for intelligent management and automation of Tilt-based development environments.

2 1 MCP

39

Neovim MCP Server

Connect AI assistants to Neovim via the Model Context Protocol.

Neovim MCP Server enables seamless integration between Neovim instances and AI assistants by implementing the Model Context Protocol (MCP). It allows for multi-connection management, supports both stdio and HTTP server transport modes, and provides access to structured diagnostic information via URI schemes. With LSP integration, plugin support, and an extensible tool system, it facilitates advanced interaction with Neovim for context-aware AI workflows.

20 3 MCP

40

MCP Rubber Duck

A bridge server for querying multiple OpenAI-compatible LLMs through the Model Context Protocol.

MCP Rubber Duck acts as an MCP (Model Context Protocol) server that enables users to query and manage multiple OpenAI-compatible large language models from a unified API. It supports parallel querying of various providers, context management across sessions, failover between providers, and response caching. This tool is designed for debugging and experimentation by allowing users to receive diverse AI-driven perspectives from different model endpoints.

56 7 MCP

41

Inspektor Gadget MCP Server

AI-powered Kubernetes troubleshooting via Model Context Protocol.

Inspektor Gadget MCP Server provides an AI-powered debugging and inspection interface for Kubernetes clusters. Leveraging the Model Context Protocol, it enables intelligent output summarization, one-click deployment of Inspektor Gadget, and automated discovery of debugging tools from Artifact Hub. The server integrates seamlessly with VS Code for interactive AI commands, simplifying Kubernetes troubleshooting and monitoring workflows.

16 1 MCP

42

mcp-get

A command-line tool for discovering, installing, and managing Model Context Protocol servers.

mcp-get is a CLI tool designed to help users discover, install, and manage Model Context Protocol (MCP) servers. It enables seamless integration of Large Language Models (LLMs) with various external data sources and tools by utilizing a standardized protocol. The tool provides access to a curated registry of MCP servers and supports installation and management across multiple programming languages and environments. Although now archived, mcp-get simplifies environment variable management, package versioning, and server updates to enhance the LLM ecosystem.

497 103 MCP

43

Signoz MCP Server

Connect SigNoz observability data to AI assistants via the Model Context Protocol.

Signoz MCP Server acts as a bridge between SigNoz observability platforms and AI assistants by implementing the Model Context Protocol (MCP). It exposes a suite of tools for querying dashboard information, fetching panel and metrics data, executing custom queries, and retrieving traces or logs from SigNoz. The tool supports integration with popular AI assistants, flexible deployment options (Docker, local virtual environments), and secure configuration via environment variables or YAML files. The server is designed to enable standardized programmatic context retrieval for enhancing AI/LLM workflows.

11 1 MCP

44

Edge Delta MCP Server

Seamlessly integrate Edge Delta APIs into the Model Context Protocol ecosystem.

Edge Delta MCP Server is a Model Context Protocol server enabling advanced integration with Edge Delta APIs. It allows developers and tools to extract, analyze, and automate observability data from Edge Delta through standardized MCP interfaces. The server supports AI-powered applications and automations, and can be deployed via Docker for straightforward operation. The Go API is available for experimental programmatic access.

5 4 MCP

45

mcp-memgraph

Expose Memgraph database features via the Model Context Protocol.

mcp-memgraph provides an MCP (Model Context Protocol) server implementation, enabling Memgraph tools to be accessed over a lightweight STDIO protocol. It supports seamless integration with AI frameworks by standardizing context and communication for data-driven AI workflows. The toolkit is part of a larger suite for extending Memgraph with AI-powered capabilities, including tools for LangChain integration and automated database migration. Tested packages and usage examples are provided for quick adoption.

52 5 MCP

46

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

47

LlamaCloud MCP Server

Connect multiple LlamaCloud indexes as tools for your MCP client.

LlamaCloud MCP Server is a TypeScript-based implementation of a Model Context Protocol server that allows users to connect multiple managed indexes from LlamaCloud as separate tools in MCP-compatible clients. Each tool is defined via command-line parameters, enabling flexible and dynamic access to different document indexes. The server automatically generates tool interfaces, each capable of querying its respective LlamaCloud index, with customizable parameters such as index name, description, and result limits. Designed for seamless integration, it works with clients like Claude Desktop, Windsurf, and Cursor.

82 17 MCP

48

Dappier MCP Server

Real-time web search and premium data access for AI agents via Model Context Protocol.

Dappier MCP Server enables fast, real-time web search and access to premium data sources, including news, financial markets, sports, and weather, for AI agents using the Model Context Protocol (MCP). It integrates seamlessly with tools like Claude Desktop and Cursor, allowing users to enhance their AI workflows with up-to-date, trusted information. Simple installation and configuration are provided for multiple platforms, leveraging API keys for secure access. The solution supports deployment via Smithery and direct installation with 'uv', facilitating rapid setup for developers.

35 11 MCP

49

Apache APISIX

Dynamic, high-performance API Gateway with AI and Model Context Protocol support

Apache APISIX is a real-time, high-performance API gateway that offers advanced traffic management features such as load balancing, dynamic routing, and authentication. It serves as both a traditional API gateway and an AI Gateway, supporting seamless proxying for AI workloads and managing LLM traffic. Notably, it includes the 'mcp-bridge' plugin, which allows for integration and conversion of stdio-based Model Context Protocol (MCP) servers to scalable HTTP SSE services, enabling robust context management for AI applications.

15,837 2,707 MCP

50

Webvizio MCP Server

Bridge between Webvizio feedback and AI coding agents via the Model Context Protocol

Webvizio MCP Server is a TypeScript-based server implementing the Model Context Protocol to securely and efficiently interface with the Webvizio API. It transforms web page feedback and bug reports into structured, actionable developer tasks, providing AI coding agents with comprehensive task context and data. It offers methods to fetch project and task details, retrieve logs and screenshots, and manage task statuses. The server standardizes communication between Webvizio and AI agent clients, facilitating automated issue resolution.

4 4 MCP

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