Tilt MCP Server - Alternatives & Competitors

Ranked by Relevance

• 1
  

  MKP

  A Model Context Protocol server enabling LLM-powered applications to interact with Kubernetes clusters.

  MKP is a Model Context Protocol (MCP) server designed for Kubernetes environments, allowing large language model (LLM) powered applications to list, retrieve, and apply Kubernetes resources through a standardized protocol interface. Built natively in Go, it utilizes Kubernetes API machinery to provide direct, type-safe, and reliable operations without dependencies on CLI tools. MKP offers a minimalist, pluggable design enabling universal resource support, including custom resource definitions, and includes built-in rate limiting for production readiness.

  54 5 MCP
• 2
  

  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
• 3
  

  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
• 4
  

  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.

  76 13 MCP
• 5
  

  CircleCI MCP Server

  Enable LLM-driven automation for CircleCI with the Model Context Protocol.

  CircleCI MCP Server is an implementation of the Model Context Protocol (MCP) designed to bridge CircleCI with large language models and AI assistants. It supports integration with tools like Cursor IDE, Windsurf, Copilot, and VS Code, allowing users to interact with CircleCI using natural language. The server can be deployed locally via NPX or Docker and remotely, making CircleCI workflows accessible and manageable through standardized protocol operations.

  69 38 MCP
• 6
  

  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
• 7
  

  Weblate MCP Server

  Seamlessly connect AI assistants to Weblate for translation management via the Model Context Protocol.

  Weblate MCP Server enables AI assistants and clients to directly manage Weblate translation projects through the Model Context Protocol (MCP). It integrates with the Weblate REST API, allowing natural language interaction for project and translation management. The tool offers multiple transport options including HTTP, SSE, and STDIO, and is optimized for large language model workflows. Full support for project, component, and translation operations is provided, with a focus on type safety and flexible environment configuration.

  9 5 MCP
• 8
  

  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
• 9
  

  mcp-k8s

  A Kubernetes MCP server enabling resource management via Model Control Protocol.

  mcp-k8s is a Kubernetes server that implements the Model Control Protocol (MCP), allowing users to interact with Kubernetes clusters through MCP-compatible tools. It supports querying and managing all Kubernetes resources, including custom resources, with fine-grained control over read and write operations. The server utilizes stdio communication and integrates with both Kubernetes and Helm, facilitating resource and Helm release management. It is designed to support natural language interactions with large language models for managing, diagnosing, and learning Kubernetes operations.

  129 25 MCP
• 10
  

  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
• 11
  

  APISIX Model Context Protocol Server

  Bridge LLMs with APISIX for natural language API management.

  APISIX Model Context Protocol (MCP) Server enables large language models to interact with and manage APISIX resources via natural language commands. It provides a standardized protocol for connecting AI clients like Claude, Cursor, and Copilot to the APISIX Admin API. The server supports a range of operations including CRUD for routes, services, upstreams, plugins, security configurations, and more. Installation is streamlined via Smithery, npm, or direct source setup with customizable environment variables.

  29 9 MCP
• 12
  

  MaxMSP-MCP Server

  Bridge LLMs with Max patches via Model Context Protocol

  MaxMSP-MCP Server enables large language models to understand, explain, and generate Max patches by leveraging the Model Context Protocol. It connects LLM agents with MaxMSP environments, providing access to documentation and patch objects for detailed interaction. Installation includes both a Python server and Max environment integration, facilitating seamless Python-Max communication. The tool supports explaining patches, debugging, and synthesizer creation directly through LLM interfaces.

  106 12 MCP
• 13
  

  tfmcp

  A CLI tool for managing Terraform via the Model Context Protocol (MCP).

  tfmcp is a command-line tool that enables interaction with Terraform using the Model Context Protocol (MCP). It allows language models and AI assistants to analyze, manage, and operate Terraform environments programmatically, supporting operations such as configuration analysis, state management, and secure application of changes. The tool offers enterprise-grade security, audit logging, and flexible deployment options including Docker support. Designed for efficiency and seamless integration, tfmcp simplifies infrastructure automation workflows for both developers and AI systems.

  345 23 MCP
• 14
  

  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
• 15
  

  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
• 16
  

  mcp-server-docker

  Natural language management of Docker containers via Model Context Protocol.

  mcp-server-docker enables users to manage Docker containers using natural language instructions through the Model Context Protocol. It allows composing, introspecting, and debugging containers, as well as managing persistent Docker volumes. The tool is suitable for server administrators, tinkerers, and AI enthusiasts looking to leverage LLM capabilities for Docker management. Integration with tools like Claude Desktop and Docker ensures flexible deployment and easy connectivity to Docker engines.

  648 86 MCP
• 17
  

  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
• 18
  

  mcp-graphql

  Enables LLMs to interact dynamically with GraphQL APIs via Model Context Protocol.

  mcp-graphql provides a Model Context Protocol (MCP) server that allows large language models to discover and interact with GraphQL APIs. The implementation facilitates schema introspection, exposes the GraphQL schema as a resource, and enables secure query and mutation execution based on configuration. It supports configuration through environment variables, automated or manual installation options, and offers flexibility in using local or remote schema files. By default, mutation operations are disabled for security, but can be enabled if required.

  319 54 MCP
• 19
  

  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
• 20
  

  TickTick MCP

  MCP server for AI-powered TickTick task management integration

  TickTick MCP is a Model Context Protocol (MCP) server that enables standardized integration of TickTick's task management features with AI assistants and developer applications. It allows programmatic access to create, update, retrieve, complete, or delete tasks and projects in TickTick via Python. Using this MCP server, AI systems can leverage TickTick's API to help automate and manage user's to-do lists and projects through natural language or other interfaces.

  6 6 MCP
• 21
  

  MCP-Typescribe

  An MCP server for serving TypeScript API context to language models.

  MCP-Typescribe is an open-source implementation of the Model Context Protocol (MCP) focused on providing LLMs with contextual, real-time access to TypeScript API documentation. It parses TypeScript (and other) definitions using TypeDoc-generated JSON and serves this information via a queryable server that supports tools used by AI coding assistants. The solution enables AI agents to dynamically explore, search, and understand unknown APIs, accelerating onboarding and supporting agentic behaviors in code generation.

  45 6 MCP
• 22
  

  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
• 23
  

  PiloTY

  AI Pilot for PTY Operations via the Model Context Protocol

  PiloTY is an MCP server that enables AI agents to control interactive terminals as if they were human users. It provides stateful, context-preserving terminal sessions that support interactive programs, SSH connections, and background process management. The system allows secure integration with AI platforms like Claude Code or Claude Desktop to translate natural language instructions into complex terminal workflows. Designed for extensibility and real-world development scenarios, PiloTY empowers agents to manage remote environments, debug interactively, and automate multi-step operations.

  12 3 MCP
• 24
  

  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
• 25
  

  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
• 26
  

  Portainer MCP

  Connect AI assistants securely to Portainer environments using the Model Context Protocol.

  Portainer MCP is an implementation of the Model Context Protocol (MCP) designed for seamless integration between AI assistants and Portainer-managed container environments. It enables management of Portainer resources and allows execution of Docker and Kubernetes commands through AI interfaces in a secure, standardized manner. The tool provides direct protocol-based access to environment data, facilitating automation and operational insights for container infrastructures.

  81 16 MCP
• 27
  

  MCP K8S Go

  Golang-based MCP server that enables AI-driven interactions with Kubernetes clusters.

  MCP K8S Go provides a server implementation of the Model Context Protocol for managing and interacting with Kubernetes clusters. It offers functionality to list, retrieve, create, and modify Kubernetes resources such as contexts, namespaces, pods, and nodes using standardized context-aware approaches. Designed for integration with AI assistants like Claude Desktop, it enables prompting and tool execution to manage cluster state, monitor events, fetch pod logs, and run in-pod commands. The solution supports deployment via various installation methods including Docker, Node.js, and Go binaries.

  356 50 MCP
• 28
  

  TickTick MCP Server

  Enable powerful AI-driven task management for TickTick via the Model Context Protocol.

  TickTick MCP Server provides comprehensive programmatic access to TickTick task management features using the Model Context Protocol. Built on the ticktick-py library, it enables AI assistants and MCP-compatible applications to create, update, retrieve, and filter tasks with improved precision and flexibility. The server supports advanced filtering, project and tag management, subtask handling, and robust context management for seamless AI integration.

  35 9 MCP
• 29
  

  Firefly MCP Server

  Seamless resource discovery and codification for Cloud and SaaS with Model Context Protocol integration.

  Firefly MCP Server is a TypeScript-based server implementing the Model Context Protocol to enable integration with the Firefly platform for discovering and managing resources across Cloud and SaaS accounts. It supports secure authentication, resource codification into infrastructure as code, and easy integration with tools such as Claude and Cursor. The server can be configured via environment variables or command line and communicates using standardized MCP interfaces. Its features facilitate automation and codification workflows for cloud resource management.

  15 6 MCP
• 30
  

  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
• 31
  

  Flipt MCP Server

  MCP server for Flipt, enabling AI assistants to manage and evaluate feature flags.

  Flipt MCP Server is an implementation of the Model Context Protocol (MCP) that provides AI assistants with the ability to interact with Flipt feature flags. It enables listing, creating, updating, and deleting various flag-related entities, as well as flag evaluation and management. The server supports multiple transports, is configurable via environment variables, and can be deployed via npm or Docker. Designed for seamless integration with MCP-compatible AI clients.

  2 7 MCP
• 32
  

  MCP Nutanix

  An MCP server enabling LLM access to Nutanix Prism Central APIs.

  MCP Nutanix is an experimental Model Context Protocol (MCP) server that allows large language models to interact with Nutanix Prism Central APIs. It facilitates listing and accessing resources such as VMs, clusters, and hosts via standardized MCP client-server integration, using the Prism Go Client for backend communication. The implementation supports both interactive and static credential methods, making it compatible with various MCP clients including Claude and Cursor.

  11 5 MCP
• 33
  

  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
• 34
  

  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
• 35
  

  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.

  11 11 MCP
• 36
  

  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
• 37
  

  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.

  12 4 MCP
• 38
  

  CyberChef API MCP Server

  MCP server enabling LLMs to access CyberChef's powerful data analysis and processing tools.

  CyberChef API MCP Server implements the Model Context Protocol (MCP), interfacing with the CyberChef Server API to provide structured tools and resources for LLM/MCP clients. It exposes key CyberChef operations such as executing recipes, batch processing, retrieving operation categories, and utilizing the magic operation for automated data decoding. The server can be configured and managed via standard MCP client workflows and supports context-driven tool invocation for large language models.

  29 5 MCP
• 39
  

  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
• 40
  

  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
• 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
  

  Mattermost MCP Host

  Connects Mattermost to MCP servers, enabling AI agent-powered tool orchestration within chat.

  Mattermost MCP Host integrates the Model Context Protocol (MCP) with Mattermost, utilizing a LangGraph-based AI agent to facilitate seamless user interaction and dynamic tool execution directly in chat. It supports integration with multiple MCP servers, automatically discovers available tools, and allows users to issue commands or natural language requests. Conversational context is maintained in threads, and users can interact directly with MCP servers to manage resources and capabilities.

  27 16 MCP
• 43
  

  Databricks MCP Server

  Expose Databricks data and jobs securely with Model Context Protocol for LLMs.

  Databricks MCP Server implements the Model Context Protocol (MCP) to provide a bridge between Databricks APIs and large language models. It enables LLMs to run SQL queries, list Databricks jobs, retrieve job statuses, and fetch detailed job information via a standardized MCP interface. The server handles authentication, secure environment configuration, and provides accessible endpoints for interaction with Databricks workspaces.

  42 24 MCP
• 44
  

  GIS MCP Server

  Empower AI with advanced geospatial operations via Model Context Protocol.

  GIS MCP Server provides a Model Context Protocol (MCP) server implementation that enables Large Language Models to access and perform sophisticated GIS operations. It bridges AI assistants with Python geospatial libraries such as Shapely, GeoPandas, PyProj, Rasterio, and PySAL. The server supports a wide range of spatial analysis, coordinate transformations, raster and vector data processing, and geospatial intelligence tasks. By integrating with MCP-compatible clients, it enhances AI tools with precise and extensible spatial capabilities.

  70 21 MCP
• 45
  

  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.

  140 21 MCP
• 46
  

  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
• 47
  

  @reapi/mcp-openapi

  Serve multiple OpenAPI specs for LLM-powered IDE integrations via the Model Context Protocol.

  @reapi/mcp-openapi is a Model Context Protocol (MCP) server that loads and serves multiple OpenAPI specifications, making APIs available to LLM-powered IDEs and development tools. It enables Large Language Models to access, interpret, and work directly with OpenAPI docs within code editors such as Cursor. The server supports dereferenced schemas, maintains an API catalog, and offers project-specific or global configuration. Sponsored by ReAPI, it bridges the gap between API specifications and AI-powered developer environments.

  71 13 MCP
• 48
  

  Docker Hub MCP Server

  Expose Docker Hub APIs to LLMs via the Model Context Protocol.

  The Docker Hub MCP Server implements the Model Context Protocol (MCP) to make Docker Hub APIs accessible to large language models, enabling AI-powered discovery and management of container images and repositories. It provides an interface for LLMs to access real-time Docker Hub data, recommend images, and streamline developer workflows. The server supports both public and private repositories through configurable authentication, and can be integrated with AI assistants like Gordon and clients such as Claude Desktop.

  83 61 MCP
• 49
  

  Cross-LLM MCP Server

  Unified MCP server for accessing and combining multiple LLM APIs.

  Cross-LLM MCP Server is a Model Context Protocol (MCP) server enabling seamless access to a range of Large Language Model APIs including ChatGPT, Claude, DeepSeek, Gemini, Grok, Kimi, Perplexity, and Mistral. It provides a unified interface for invoking different LLMs from any MCP-compatible client, allowing users to call and aggregate responses across providers. The server implements eight specialized tools for interacting with these LLMs, each offering configurable options like model selection, temperature, and token limits. Output includes model context details as well as token usage statistics for each response.

  9 5 MCP
• 50
  

  Telegram MCP Server

  A bridge connecting AI assistants to the Telegram API via the Model Context Protocol.

  Telegram MCP Server facilitates secure and structured interaction between AI assistants and the Telegram API by implementing the Model Context Protocol. It enables AI-powered tools to access, organize, and manage Telegram messages, chats, and user data while maintaining user control and privacy. The server offers capabilities for retrieving messages, managing conversations, sending drafts, and organizing chats, making it a versatile tool for AI integrations with Telegram.

  237 26 MCP