Oura MCP Server - Alternatives & Competitors
Enables language models to access Oura sleep, readiness, and resilience data via MCP.
Oura MCP Server implements the Model Context Protocol to provide language models with access to Oura API data. It allows querying of sleep, readiness, and resilience metrics for specified date ranges or for the current day. The server supports integration with tools like Claude for Desktop and handles API authentication and error scenarios gracefully. Designed for seamless access to personal health metrics through standardized protocol endpoints.
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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 -
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OpenAI MCP Server
Bridge between Claude and OpenAI models using the MCP protocol.
OpenAI MCP Server enables direct querying of OpenAI language models from Claude via the Model Context Protocol (MCP). It provides a configurable Python server that exposes OpenAI APIs as MCP endpoints. The server is designed for seamless integration, requiring simple configuration updates and environment variable setup. Automated testing is supported to verify connectivity and response from the OpenAI API.
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mcp
Universal remote MCP server connecting AI clients to productivity tools.
WayStation MCP acts as a remote Model Context Protocol (MCP) server, enabling seamless integration between AI clients like Claude or Cursor and a wide range of productivity applications, such as Notion, Monday, Airtable, Jira, and more. It supports multiple secure connection transports and offers both general and user-specific preauthenticated endpoints. The platform emphasizes ease of integration, OAuth2-based authentication, and broad app compatibility. Users can manage their integrations through a user dashboard, simplifying complex workflow automations for AI-powered productivity.
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MCP Server for Milvus
Bridge Milvus vector database with AI apps using Model Context Protocol (MCP).
MCP Server for Milvus enables seamless integration between the Milvus vector database and large language model (LLM) applications via the Model Context Protocol. It exposes Milvus functionality to external LLM-powered tools through both stdio and Server-Sent Events communication modes. The solution is compatible with MCP-enabled clients such as Claude Desktop and Cursor, supporting easy access to relevant vector data for enhanced AI workflows. Configuration is flexible through environment variables or command-line arguments.
196 57 MCP -
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OpsLevel MCP Server
Read-only MCP server for integrating OpsLevel data with AI tools.
OpsLevel MCP Server implements the Model Context Protocol to provide AI tools with a secure way to access and interact with OpsLevel account data. It supports read-only operations for a wide range of OpsLevel resources such as actions, campaigns, checks, components, documentation, domains, and more. The tool is compatible with popular environments including Claude Desktop and VS Code, enabling easy integration via configuration and API tokens. Installation options include Homebrew, Docker, and standalone binaries.
8 7 MCP -
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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 -
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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 -
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TeslaMate MCP Server
Query your TeslaMate data using the Model Context Protocol
TeslaMate MCP Server implements the Model Context Protocol to enable AI assistants and clients to securely access and query Tesla vehicle data, statistics, and analytics from a TeslaMate PostgreSQL database. The server exposes a suite of tools for retrieving vehicle status, driving history, charging sessions, battery health, and more using standardized MCP endpoints. It supports local and Docker deployments, includes bearer token authentication, and is intended for integration with MCP-compatible AI systems like Claude Desktop.
106 14 MCP -
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ShopSavvy Data API MCP Server
MCP server providing AI assistants with live product data, pricing, and price tracking from ShopSavvy.
ShopSavvy Data API MCP Server implements the Model Context Protocol to enable AI assistants to access and interact with ShopSavvy's extensive product database. It supports product lookup, retrieves current and historical pricing from multiple retailers, and allows scheduled monitoring of product prices. The server also manages API usage analytics and credit consumption, offering robust error handling and developer tools for integration.
5 3 MCP -
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RAE Model Context Protocol (MCP) Server
An MCP server enabling LLMs to access RAE’s dictionary and linguistic resources.
Provides a Model Context Protocol (MCP) server implementation for the Royal Spanish Academy API, facilitating integration with language models. Offers tools such as search and word information retrieval, exposing RAE’s dictionary and linguistic data to LLMs. Supports multiple transports including stdio and SSE, making it suitable for both direct and server-based LLM interactions.
3 3 MCP -
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MCP Server for Iaptic
A Model Context Protocol server for accessing and managing Iaptic data with AI agents.
MCP Server for Iaptic implements the Model Context Protocol to enable AI models, such as Claude, to securely and efficiently interact with Iaptic's customer, purchase, transaction, and statistics data. The server provides a standardized interface and command set for querying and managing information related to customers, purchases, transactions, events, and application management. Designed for integration with Claude Desktop and similar AI clients, it offers both automated and manual installation options.
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Aiven MCP Server
Model Context Protocol server enabling LLMs to access and manage Aiven cloud data services.
Aiven MCP Server implements the Model Context Protocol (MCP) to provide secure access to Aiven's PostgreSQL, Kafka, ClickHouse, Valkey, and OpenSearch services. It enables Large Language Models (LLMs) to seamlessly integrate and interact with these cloud data platforms, supporting full stack solution development. The server offers streamlined tools for project and service management via standardized APIs and supports integration with platforms like Claude Desktop and Cursor. Environment variable configuration and explicit permission controls are used to ensure secure and flexible operations.
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Snowflake MCP Server
MCP server enabling secure and structured Snowflake database interaction with AI tools.
Snowflake MCP Server provides a Model Context Protocol-conformant interface to interact programmatically with Snowflake databases. It exposes SQL execution, schema exploration, and insight aggregation as standardized resources and tools accessible by AI assistants. The server offers read/write capabilities, structured resource summaries, and insight memoization suitable for contextual AI workflows. Integration is supported with popular AI platforms such as Claude Desktop via Smithery or UVX configurations.
170 75 MCP -
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Perplexity MCP Server
MCP Server integration for accessing the Perplexity API with context-aware chat completion.
Perplexity MCP Server provides a Model Context Protocol (MCP) compliant server that interfaces with the Perplexity API, enabling chat completion with citations. Designed for seamless integration with clients such as Claude Desktop, it allows users to send queries and receive context-rich responses from Perplexity. Environment configuration for API key management is supported, and limitations with long-running requests are noted. Future updates are planned to enhance support for client progress reporting.
85 35 MCP -
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mcp-server-home-assistant
A Model Context Protocol Server integration for Home Assistant.
Provides an MCP server interface for Home Assistant, enabling context sharing between Home Assistant and AI models through the Model Context Protocol. Allows users to connect Claude Desktop and similar tools to Home Assistant via a WebSocket API and secure API token. Facilitates seamless integration by leveraging a custom Home Assistant component that is migrating into Home Assistant Core. Enables access and manipulation of smart home context data in standardized ways.
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Model Context Protocol Server for Home Assistant
Seamlessly connect Home Assistant to LLMs for natural language smart home control via MCP.
Enables integration between a local Home Assistant instance and language models using the Model Context Protocol (MCP). Facilitates natural language monitoring and control of smart home devices, with robust API support for state management, automation, real-time updates, and system administration. Features secure, token-based access, and supports mobile and HTTP clients. Designed to bridge Home Assistant environments with modern AI-driven automation.
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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.
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MCP Server for Odoo
Connect AI assistants to Odoo ERP systems using the Model Context Protocol.
MCP Server for Odoo enables AI assistants such as Claude to interact seamlessly with Odoo ERP systems via the Model Context Protocol (MCP). It provides endpoints for searching, creating, updating, and deleting Odoo records using natural language while respecting access controls and security. The server supports integration with any Odoo instance, includes smart features like pagination and LLM-optimized output, and offers both demo and production-ready modes.
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FHIR MCP Server
A Model Context Protocol server for seamless interaction with FHIR resources and AI tools.
FHIR MCP Server implements a full Model Context Protocol server, enabling large language model agents to perform comprehensive CRUD operations on FHIR-compliant healthcare data. It offers standardized integration with various clinical data sources, natural-language query capabilities, and supports secure authentication via OAuth2. The server includes semantic search, AI-powered document processing, terminology resolution, Docker deployment, and is optimized for use with MCP-compatible clients like Claude Desktop.
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HarmonyOS MCP Server
Enables HarmonyOS device manipulation via the Model Context Protocol.
HarmonyOS MCP Server provides an MCP-compatible server that allows programmatic control of HarmonyOS devices. It integrates with tools and frameworks such as OpenAI's openai-agents SDK and LangGraph to facilitate LLM-powered automation workflows. The server supports execution through standard interfaces and can be used with agent platforms to process natural language instructions for device actions. Its design allows for seamless interaction with HarmonyOS systems using the Model Context Protocol.
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AllTrails MCP Server
MCP server for seamless AllTrails data access and integration
AllTrails MCP Server provides Model Context Protocol (MCP) compliant access to AllTrails hiking trail data, enabling AI tools to search for trails and retrieve detailed trail information. It supports searching by national park and fetching comprehensive details such as difficulty, length, elevation, ratings, and route types. The server communicates via standard input/output and is designed for easy integration with MCP-compatible clients like Claude Desktop. Installation is flexible, supporting both virtual environments and system Python setups.
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Lara Translate MCP Server
Context-aware translation server implementing the Model Context Protocol.
Lara Translate MCP Server enables AI applications to seamlessly access professional translation services via the standardized Model Context Protocol. It supports features such as language detection, context-aware translations, and translation memory integration. The server acts as a secure bridge between AI models and Lara Translate, managing credentials and facilitating structured translation requests and responses.
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Apple Health MCP Server
Connect Apple Health data with any LLM using the Model Context Protocol.
Apple Health MCP Server enables users to import, parse, and analyze Apple Health data exports, seamlessly connecting them to large language models (LLMs) that support the Model Context Protocol. Built on the high-performance FastMCP framework, it supports natural language querying, trend analysis, and integration with databases like Elasticsearch, ClickHouse, and DuckDB. The project offers modular tools for data exploration, structure analysis, and automated statistics generation. Designed for flexibility and scalability, it is container-ready and provides extensive configuration options.
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Product Hunt MCP Server
Plug-and-play MCP server for accessing Product Hunt data with LLMs and agents.
Product Hunt MCP Server acts as a bridge between Product Hunt’s API and any agent or LLM that supports the Model Context Protocol (MCP). It enables fast and standardized access to posts, collections, topics, users, comments, and votes on Product Hunt. Built on FastMCP, it ensures seamless compatibility with popular AI tooling like Claude Desktop and Cursor. Integration is straightforward, requiring only a Product Hunt API token and simple configuration.
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Open Data Model Context Protocol
Easily connect open data providers to LLMs using a Model Context Protocol server and CLI.
Open Data Model Context Protocol enables seamless integration of open public datasets into Large Language Model (LLM) applications, starting with support for Claude. Through a CLI tool and server, users can access and query public data providers within their LLM clients. It also offers tools and templates for contributors to publish and distribute new open datasets, making data discoverable and actionable for LLM queries.
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MXCP
Enterprise-Grade Model Context Protocol Framework for AI Applications
MXCP is an enterprise-ready framework that implements the Model Context Protocol (MCP) for building secure, production-grade AI application servers. It introduces a structured methodology focused on data modeling, robust service design, policy enforcement, and comprehensive testing, integrated with strong security and audit capabilities. The framework enables rapid development and deployment of AI tools, supporting both SQL and Python environments, with built-in telemetry and drift detection for reliability and compliance.
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OpenMCP
A standard and registry for converting web APIs into MCP servers.
OpenMCP defines a standard for converting various web APIs into servers compatible with the Model Context Protocol (MCP), enabling efficient, token-aware communication with client LLMs. It also provides an open-source registry of compliant servers, allowing clients to access a wide array of external services. The platform supports integration with local and remote hosting environments and offers tools for configuring supported clients, such as Claude desktop and Cursor. Comprehensive guidance is offered for adapting different API formats including REST, gRPC, GraphQL, and more into MCP endpoints.
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MCP Obsidian Server
Integrate Obsidian note management with AI models via the Model Context Protocol.
MCP Obsidian Server acts as a bridge between Obsidian and AI models by providing an MCP-compatible server interface. It enables programmatic access to Obsidian vaults through a local REST API, allowing operations like listing files, searching, reading, editing, and deleting notes. Designed to work with Claude Desktop and other MCP-enabled clients, it exposes a set of tools for efficient note and content management within Obsidian.
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Thales CDSP CRDP MCP Server
MCP server enabling secure data protection and revelation with Thales CipherTrust CRDP
Thales CDSP CRDP MCP Server implements the Model Context Protocol (MCP) to allow AI applications and LLMs to securely protect and reveal sensitive data via Thales CipherTrust RestFul Data Protection (CRDP) service. The server supports both stdio and HTTP transports, individual and bulk data operations, and robust versioning support. Features include health checks, metrics collection, and integration with protection policies and JWT-based authorization.
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MCP Server for Cortex
Bridge Cortex threat analysis capabilities to MCP-compatible clients like Claude.
MCP Server for Cortex exposes the analysis capabilities of a Cortex instance as tools consumable by Model Context Protocol (MCP) clients, such as large language models. It enables these clients to request threat intelligence analyses via Cortex and receive structured results. The server supports easy configuration, secure authentication, and flexible analyzer selection for integrating threat intelligence tasks into automated AI workflows.
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Modbus MCP Server
Standardizes Modbus data for seamless AI integration via the Model Context Protocol.
Modbus MCP Server provides an MCP-compliant interface that standardizes and contextualizes Modbus device data for use with AI agents and industrial IoT systems. It supports flexible Modbus connections over TCP, UDP, or serial interfaces and offers a range of Modbus tools for reading and writing registers and coils. With customizable prompts and structured tool definitions, it enables natural language-driven interactions and analysis of Modbus data within AI workflows. The solution is designed to ensure interoperability and easy configuration within MCP-compatible environments.
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Hydrolix MCP Server
MCP server for secure, efficient SQL access to Hydrolix clusters.
Hydrolix MCP Server provides a Model Context Protocol (MCP) interface for executing SQL queries, listing databases, and listing tables on Hydrolix clusters. It ensures safe, read-only data access and includes a standardized health-check endpoint. The server integrates easily with various MCP-compatible clients, supporting multiple authentication methods using either credentials or service account tokens.
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OpenStreetMap MCP Server
Enhancing LLMs with geospatial and location-based capabilities via the Model Context Protocol.
OpenStreetMap MCP Server enables large language models to interact with rich geospatial data and location-based services through a standardized protocol. It provides APIs and tools for address geocoding, reverse geocoding, points of interest search, route directions, and neighborhood analysis. The server exposes location-related resources and tools, making it compatible with MCP hosts for seamless LLM integration.
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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 -
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cloudflare/mcp-server-cloudflare
Connect Cloudflare services to Model Context Protocol (MCP) clients for AI-powered management.
Cloudflare MCP Server enables integration between Cloudflare's suite of services and clients using the Model Context Protocol (MCP). It provides multiple specialized servers that allow AI models to access, analyze, and manage configurations, logs, analytics, and other features across Cloudflare's platform. Users can leverage natural language interfaces in compatible MCP clients to read data, gain insights, and perform automated actions on their Cloudflare accounts. This project aims to streamline the orchestration of security, development, monitoring, and infrastructure tasks through standardized MCP connections.
2,919 251 MCP -
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Coinmarket MCP server
Access CoinMarketCap data through MCP for AI models and tools
Coinmarket MCP Server provides an interface for accessing CoinMarketCap cryptocurrency data via the Model Context Protocol. It supports retrieving the latest currency listings and token quotes using custom URI schemes. The server is compatible with environments like Claude Desktop and Docker, and requires a CoinMarketCap API key for operation.
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CipherTrust Manager MCP Server
Enables AI assistants to access CipherTrust Manager securely via the Model Context Protocol.
CipherTrust Manager MCP Server provides an implementation of the Model Context Protocol (MCP), offering AI assistants such as Claude and Cursor a unified interface to interact with CipherTrust Manager resources. Communication is facilitated through JSON-RPC over stdin/stdout, enabling key management, CTE client management, user management, and connection management functionalities. The tool is configurable via environment variables and integrates with existing CipherTrust Manager instances using the ksctl CLI for secure resource access.
7 4 MCP -
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quran-mcp-server
MCP server to access Quran.com API with AI tool compatibility.
quran-mcp-server exposes the Quran.com corpus and associated data through a Model Context Protocol (MCP) server generated from an OpenAPI specification. It provides tool endpoints for chapters, verses, translations, tafsirs, audio, languages, and more. The server is designed for seamless integration with large language models (LLMs) and AI tools, supporting both Docker and Node.js environments. Advanced logging features and flexible deployment options are included for debugging and development.
49 10 MCP -
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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 -
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CVE-Search MCP Server
MCP server for querying and managing CVE-Search vulnerability data.
CVE-Search MCP Server implements the Model Context Protocol to provide structured access to the CVE-Search API. It enables querying vendors, products, and vulnerabilities, as well as retrieving detailed information for specific CVEs. The server facilitates model context integration via MCP client tools, supporting seamless interactions for vulnerability data management.
67 11 MCP -
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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 -
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GitHub Enterprise MCP Server
Expose GitHub Enterprise data through a Model Context Protocol server.
GitHub Enterprise MCP Server provides an MCP (Model Context Protocol) interface to integrate with GitHub Enterprise APIs, enabling standardized access to repository data, issues, pull requests, workflows, and user management. It is compatible with both GitHub Enterprise Server and GitHub.com environments and supports features like repository management, file browsing, and enterprise statistics. The platform is designed for seamless integration with tools such as Cursor, making it simple to interact with GitHub data programmatically or via MCP-compliant clients.
25 7 MCP -
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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.
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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 -
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Insforge MCP Server
A Model Context Protocol server for seamless integration with Insforge and compatible AI clients.
Insforge MCP Server implements the Model Context Protocol (MCP), enabling smooth integration with various AI tools and clients. It allows users to configure and manage connections to the Insforge platform, providing automated and manual installation methods. The server supports multiple AI clients such as Claude Code, Cursor, Windsurf, Cline, Roo Code, and Trae via standardized context management. Documentation and configuration guidelines are available for further customization and usage.
3 2 MCP -
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Postmancer
A standalone MCP server for API testing and management via AI assistants.
Postmancer is a Model Context Protocol (MCP) server designed to facilitate API testing and management through natural language interactions with AI assistants. It enables HTTP requests, organizes API endpoints into collections, and provides tools for managing environment variables, authentication, and request history. Postmancer is particularly aimed at integrating with AI platforms like Claude for seamless, automated API workflows.
28 4 MCP -
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Shopify Storefront MCP Server
Seamless Shopify Storefront API access for AI assistants via Model Context Protocol
Enables AI assistants to interact with Shopify store data through standardized MCP tools. Offers endpoints for product discovery, inventory management, GraphQL queries, cart operations, and comprehensive customer data manipulation. Designed for easy integration with MCP-compatible AI and automated token handling. Simplifies secure connection to Shopify's Storefront API with minimal configuration.
5 5 MCP -
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Flowcore Platform MCP Server
A standardized MCP server for managing and interacting with Flowcore Platform resources.
Flowcore Platform MCP Server provides an implementation of the Model Context Protocol (MCP) for seamless interaction and management of Flowcore resources. It enables AI assistants to query and control the Flowcore Platform using a structured API, allowing for enhanced context handling and data access. The server supports easy deployment with npx, npm, or Bun and requires user authentication using Flowcore credentials.
9 5 MCP -
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Vectara MCP Server
Secure RAG server enabling seamless AI integration via Model Context Protocol.
Vectara MCP Server implements the open Model Context Protocol to enable AI systems and agentic applications to connect securely with Vectara's Trusted RAG platform. It supports multiple transport modes, including secure HTTP, Server-Sent Events (SSE), and local STDIO for development. The server provides fast, reliable retrieval-augmented generation (RAG) operations with built-in authentication, rate limiting, and optional CORS configuration. Integration is compatible with Claude Desktop and any other MCP client.
25 8 MCP -
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MCP Link
Convert Any OpenAPI V3 API to an MCP Server for seamless AI Agent integration.
MCP Link enables automatic conversion of any OpenAPI v3-compliant RESTful API into a Model Context Protocol (MCP) server, allowing instant compatibility with AI-driven agent frameworks. It eliminates the need for manual interface creation and code modification by translating OpenAPI schemas into MCP endpoints. MCP Link supports robust feature mapping and authentication, making it easy to expose existing APIs to AI ecosystems using a standardized protocol. The tool is designed for both developers and organizations seeking to streamline API integration with AI agents.
572 68 MCP
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