Context7 MCP alternatives

1

Unichat MCP Server

Universal MCP server providing context-aware AI chat and code tools across major model vendors.

Unichat MCP Server enables sending standardized requests to leading AI model vendors, including OpenAI, MistralAI, Anthropic, xAI, Google AI, DeepSeek, Alibaba, and Inception, utilizing the Model Context Protocol. It features unified endpoints for chat interactions and provides specialized tools for code review, documentation generation, code explanation, and programmatic code reworking. The server is designed for seamless integration with platforms like Claude Desktop and installation via Smithery. Vendor API keys are required for secure access to supported providers.

37 10 MCP

2

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

3

Lucidity MCP

Intelligent prompt-based code quality analysis for AI coding assistants.

Lucidity MCP is a Model Context Protocol (MCP) server that empowers AI coding assistants to deliver high-quality code through intelligent, prompt-driven analysis. It offers comprehensive detection of code issues across multiple quality dimensions, providing structured and actionable feedback. With language-agnostic capabilities, extensible framework, and flexible transport options, Lucidity MCP seamlessly integrates into developer workflows and AI systems.

72 20 MCP

4

godoc-mcp

Token-efficient Go documentation server for LLMs using Model Context Protocol.

godoc-mcp is a Model Context Protocol (MCP) server that provides efficient, structured access to Go package documentation for large language models. It enables LLMs to understand Go projects without reading entire source files by supplying essential documentation and source code at varying levels of granularity. The tool supports project navigation, automatic module setup, caching, and works offline for both standard and third-party Go packages.

88 11 MCP

5

NyxDocs

MCP server for real-time cryptocurrency project documentation and insights.

NyxDocs is a Model Context Protocol (MCP) compatible server built in Python for managing and serving up-to-date documentation for cryptocurrency projects. It aggregates information from multiple sources such as CoinGecko, GitHub, GitBook, Notion, and official websites, providing real-time data and updates on blockchain ecosystems. Featuring tools for searching projects, retrieving detailed info, extracting documentation, and monitoring changes, it is tailored for developers and AI contexts needing access to accurate crypto documentation. The architecture leverages a FastMCP-based server core, automated document scrapers, and supports multi-blockchain environments.

3 3 MCP

6

kibitz

The coding agent for professionals with MCP integration.

kibitz is a coding agent that supports advanced AI collaboration by enabling seamless integration with Model Context Protocol (MCP) servers via WebSockets. It allows users to configure Anthropic API keys, system prompts, and custom context providers for each project, enhancing contextual understanding for coding tasks. The platform is designed for developers and professionals seeking tailored AI-driven coding workflows and provides flexible project-specific configuration.

104 14 MCP

7

Driflyte MCP Server

Bridging AI assistants with deep, topic-aware knowledge from web and code sources.

Driflyte MCP Server acts as a bridge between AI-powered assistants and diverse, topic-aware content sources by exposing a Model Context Protocol (MCP) server. It enables retrieval-augmented generation workflows by crawling, indexing, and serving topic-specific documents from web pages and GitHub repositories. The system is extensible, with planned support for additional knowledge sources, and is designed for easy integration with popular AI tools such as ChatGPT, Claude, and VS Code.

9 2 MCP

8

Coda MCP Server

A Model Context Protocol server enabling seamless interaction with Coda documents and pages.

Coda MCP Server implements a Model Context Protocol (MCP) server that bridges AI assistants or MCP clients with the Coda API. It provides standardized tools for listing, creating, reading, updating, duplicating, and renaming Coda pages, as well as handling document context. The server communicates over standard input/output, supporting integration with platforms like Cursor and Claude Desktop, and can be deployed via Node.js or Docker.

36 22 MCP

9

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

10

interactive-mcp

Enable interactive, local communication between LLMs and users via MCP.

interactive-mcp implements a Model Context Protocol (MCP) server in Node.js/TypeScript, allowing Large Language Models (LLMs) to interact directly with users on their local machine. It exposes tools for requesting user input, sending notifications, and managing persistent command-line chat sessions, facilitating real-time communication. Designed for integration with clients like Claude Desktop and VS Code, it operates locally to access OS-level notifications and command prompts. The project is suited for interactive workflows where LLMs require user involvement or confirmation.

313 25 MCP

11

BoldSign MCP Server

Bridge Large Language Models with BoldSign's e-signature API via the Model Context Protocol.

BoldSign MCP Server enables interaction between Large Language Models (LLMs) and the BoldSign API using the Model Context Protocol (MCP). It allows LLMs to manage templates and documents for e-signature workflows as autonomous agents connected to external systems. The server can be seamlessly integrated with various MCP-compatible clients such as Cursor, VS Code, Windsurf, and Claude Desktop. Configuration is made easy through standard environment variables and client-specific setup instructions.

3 6 MCP

12

MCP Weather Server

Provides weather forecasts to LLMs via the Model Context Protocol.

MCP Weather Server enables large language models to access real-time, accurate weather forecasts by interfacing with the AccuWeather API. It offers both hourly and daily weather data, supporting metric and imperial units, and can be seamlessly integrated with MCP-compatible clients like Claude Desktop or supergateway. The server provides tools for retrieving weather based on location and settings, with robust configuration options. It is designed for straightforward deployment using Node.js and environment-configured API keys.

27 9 MCP

13

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

14

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

15

Linked API MCP

Connect LinkedIn to AI assistants for automated engagement and research.

Linked API MCP enables AI assistants like Claude, Cursor, and VS Code to interact with LinkedIn through a secure cloud browser. It allows automated searching for leads, profile analysis, messaging, and market research on LinkedIn. The solution is designed for sales, recruitment, and market research professionals who want to automate LinkedIn workflows. Integration is streamlined, offering a set of tools accessible to popular AI-powered platforms.

23 5 MCP

16

Enrichr MCP Server

Gene set enrichment analysis server for LLMs via the Model Context Protocol

Enrichr MCP Server provides gene set enrichment analysis using the Enrichr API, supporting all available gene set libraries. It is designed to integrate with LLM tools through the Model Context Protocol and returns only statistically significant results. The tool allows queries across multiple biological, disease, tissue, drug, and pathway gene set libraries, with customizable configuration for popular or specific libraries. Installation and integration is streamlined for platforms like Claude Desktop, Cursor, and VS Code.

7 3 MCP

17

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

18

Content Core

AI-powered content extraction and processing platform with seamless model context integration.

Content Core is an AI-driven platform for extracting, formatting, transcribing, and summarizing content from a wide variety of sources including documents, media files, web pages, images, and archives. It offers intelligent auto-detection and engine selection to optimize processing, and provides integrations via CLI, Python library, Raycast extension, macOS Services, and the Model Context Protocol (MCP). The platform supports context-aware AI summaries and direct integration with Claude through MCP for enhanced user workflows. Users can access zero-install options and benefit from enhanced processing capabilities such as advanced PDF parsing, OCR, and smart summarization.

85 20 MCP

19

Typst MCP Server

Facilitates AI-driven Typst interactions with LaTeX conversion, validation, and image generation tools.

Typst MCP Server implements the Model Context Protocol, enabling AI models to interface seamlessly with Typst, a markup-based typesetting system. It provides tools for tasks such as converting LaTeX to Typst, validating Typst syntax, listing and retrieving Typst documentation chapters, and rendering Typst code as images. The server is compatible with MCP agent clients, such as Claude Desktop and VS Code’s agent mode. All functionalities are exposed as tools for ease of LLM integration.

79 7 MCP

20

Memory MCP

A Model Context Protocol server for managing LLM conversation memories with intelligent context window caching.

Memory MCP provides a Model Context Protocol (MCP) server for logging, retrieving, and managing memories from large language model (LLM) conversations. It offers features such as context window caching, relevance scoring, and tag-based context retrieval, leveraging MongoDB for persistent storage. The system is designed to efficiently archive, score, and summarize conversational context, supporting external orchestration and advanced memory management tools. This enables seamless handling of conversation history and dynamic context for enhanced LLM applications.

10 6 MCP

21

IPLocate MCP Server

Comprehensive IP address geolocation and network intelligence via MCP.

Provides an MCP server interface to IPLocate.io, delivering detailed IP address intelligence including geolocation, network details, privacy detection, and abuse contact information. Easily integrates with popular MCP clients like Cursor and Claude Desktop for seamless IP lookups. Enables users to retrieve geographic, organizational, and security-related data associated with IPv4 and IPv6 addresses by connecting to the IPLocate.io API.

11 5 MCP

22

OpenTK Model Context Protocol Server

A standardized interface for LLMs to access Dutch parliamentary data.

OpenTK Model Context Protocol Server provides a bridge between large language models and Dutch parliamentary data using the Model Context Protocol (MCP). It enables AI systems to access, search, and analyze parliamentary documents, debates, and member information from the Tweede Kamer through a unified and structured interface. By leveraging the @modelcontextprotocol/sdk, it ensures consistent context management for model interactions. Built atop the OpenTK project, it delivers streamlined access to extensive open government datasets.

16 3 MCP

23

Stadia Maps MCP Server (TypeScript)

Bringing location services, geocoding, and mapping to AI assistants via Stadia Maps APIs.

Stadia Maps MCP Server (TypeScript) implements the Model Context Protocol to provide LLM-based assistants with structured access to Stadia Maps APIs. It enables AI tools to query for geocoding, routing, time zones, map generation, and isochrone calculations. Designed for integration with agentic tools and LLMs, the server enhances spatial intelligence and location-based features in AI workflows.

18 5 MCP

24

Pearch.ai MCP

Natural Language People Search and Candidate Sourcing API for Seamless ATS Integration

Pearch.ai MCP provides a high-precision people search API that interprets natural language queries to deliver top-quality candidate results. Designed for easy integration with Applicant Tracking Systems and hiring platforms, it leverages scientific methods and is trusted by recruiters. The tool is implemented as a Model Context Protocol (MCP), facilitating standardized model context handling and deployment via packages like FastMCP or through Smithery. The solution prioritizes ease of use, reliability, and high candidate match accuracy.

5 4 MCP

25

Beelzebub

AI-driven honeypot framework with advanced threat detection and context protocol support.

Beelzebub is an advanced honeypot framework that utilizes AI and large language models (LLMs) to realistically simulate system interactions, enabling the detection and analysis of sophisticated cyber attacks. The platform supports modular service definitions via YAML, integrates with observability stacks, and supports multiple protocols including MCP, which is used to detect prompt injection against LLM agents. Designed for security researchers and professionals, it enables the creation of distributed honeypot networks for collaborative global threat intelligence.

1,680 155 MCP

26

OSP Marketing Tools for LLMs

Comprehensive marketing content creation and optimization tools for LLMs using MCP.

OSP Marketing Tools for LLMs offers a suite of marketing content creation and optimization utilities designed to operate with Large Language Models that support the Model Context Protocol (MCP). Built on Open Strategy Partners’ proprietary methodologies, it provides structured workflows for product value mapping, metadata generation, content editing, technical writing, and SEO guidance. The suite includes features for persona development, value case documentation, semantic editing, and technical writing best practices, enabling consistent and high-quality marketing outputs. Designed to integrate seamlessly with MCP-compatible LLM clients, it streamlines complex marketing processes and empowers efficient collaboration across technical and non-technical teams.

252 40 MCP

27

Jotdown

MCP Server for Notion Page Creation and mdBook Generation

Jotdown is an MCP server enabling large language models to interact seamlessly with Notion and generate markdown books (mdBooks). It allows LLMs to create or update Notion pages and manage the entire process of markdown book creation, including structure and navigation. Leveraging the Model Context Protocol, it provides tools for consistent and intelligent context handling between LLMs and external content platforms.

19 4 MCP

28

MCP-Geo

Geocoding and reverse geocoding MCP server for LLMs.

MCP-Geo provides geocoding and reverse geocoding capabilities to AI models using the Model Context Protocol, powered by the GeoPY library. It offers various tools such as address lookup, reverse lookup from coordinates, distance calculations, and batch processing of locations, all accessible via standard MCP tool interfaces. Safety features like rate limiting and robust error handling ensure reliable and compliant usage of geocoding services. The server is compatible with environments like Claude Desktop and can be easily configured elsewhere.

28 4 MCP

29

mcp-paperswithcode

Discover and analyze research papers and code repositories through the PapersWithCode API.

mcp-paperswithcode provides a Model Context Protocol (MCP) interface for AI assistants to discover, search, and analyze research papers, related code repositories, datasets, authors, conferences, and research areas. The tool enables seamless integration with the PapersWithCode API, offering powerful methods for context-aware research exploration. It supports searching, retrieving metadata, extracting content, and listing relationships between academic resources, enhancing an AI model's ability to access and utilize scientific content.

14 7 MCP

30

Trieve

All-in-one solution for search, recommendations, and RAG.

Trieve offers a platform for semantic search, recommendations, and retrieval-augmented generation (RAG). It supports dense vector search, typo-tolerant neural search, sub-sentence highlighting, and integrates with a variety of embedding models. Trieve can be self-hosted and features APIs for context management with LLMs, including Bring Your Own Model and managed RAG endpoints. Full documentation and SDKs are available for streamlined integration.

2,555 229 MCP

31

Ethics Check MCP

Turn any AI into a philosophical sparring partner that challenges assumptions and biases.

Ethics Check MCP transforms AI assistants by making them actively identify and question ethical concerns, confirmation bias, and unexamined assumptions in conversations. The MCP server modifies models like Claude to interrupt comfortable exchanges and provoke critical thinking through counterarguments and alternative perspectives. By tracking ethical dimensions and user patterns, it delivers tailored challenges to encourage transparent and fair discussion. The tool is designed to keep AI-driven conversations rigorously self-critical and ethically aware.

3 2 MCP

32

melrose-mcp

An MCP server for generating and playing programmable music via Melrōse.

melrose-mcp is a Model Context Protocol (MCP) server that enables users to compose and perform music using the Melrōse programming language. It facilitates communication between AI models and the Melrōse tool, allowing for dynamic manipulation of tempo, playback, and MIDI configuration. The project supports various tools for controlling musical expression and can be integrated into client applications such as Claude Desktop.

7 3 MCP

33

GitMCP

Instantly turn any GitHub repository into an AI-ready documentation hub.

GitMCP is a free, open-source, remote Model Context Protocol (MCP) server that gives AI assistants real-time access to the latest documentation and code from any GitHub repository. It transforms any GitHub project into an accessible documentation hub, enabling AI tools to deliver accurate results, reduce hallucinations, and improve code correctness. Supporting both specific and generic server modes, it allows seamless integration into developer workflows with zero setup. GitMCP emphasizes privacy, flexibility, and up-to-date information retrieval.

6,916 571 MCP

34

Maven Tools MCP Server

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

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

14 2 MCP

35

dev.augments/mcp

Real-time framework documentation provider and context enhancer for Claude Code via MCP.

Augments MCP Server delivers comprehensive, real-time framework documentation and context-aware assistance for developers, integrating seamlessly with Claude Code through the Model Context Protocol. It aggregates and prioritizes multi-source documentation, employs advanced caching and hot-reloading, and enhances context with compatibility analysis and task-specific insights. It offers structured, validated JSON outputs and robust error handling for a modern, resilient developer experience.

79 10 MCP

36

awslabs/mcp

Specialized MCP servers for seamless AWS integration in AI and development environments.

AWS MCP Servers is a suite of specialized servers implementing the open Model Context Protocol (MCP) to bridge large language model (LLM) applications with AWS services, tools, and data sources. It provides a standardized way for AI assistants, IDEs, and developer tools to access up-to-date AWS documentation, perform cloud operations, and automate workflows with context-aware intelligence. Featuring a broad catalog of domain-specific servers, quick installation for popular platforms, and both local and remote deployment options, it enhances cloud-native development, infrastructure management, and workflow automation for AI-driven tools. The project includes Docker, Lambda, and direct integration instructions for environments such as Amazon Q CLI, Cursor, Windsurf, Kiro, and VS Code.

6,220 829 MCP

37

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

38

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

39

LLM Context

Reduce friction when providing context to LLMs with smart file selection and rule-based filtering.

LLM Context streamlines the process of sharing relevant project files and context with large language models. It employs smart file selection and customizable rule-based filtering to ensure only the most pertinent information is provided. The tool supports Model Context Protocol (MCP), allowing AI models to access additional files seamlessly through standardized commands. Integration with MCP enables instant project context sharing during AI conversations, enhancing productivity and collaboration.

283 26 MCP

40

RAG Documentation MCP Server

Vector-based documentation search and context augmentation for AI assistants

RAG Documentation MCP Server provides vector-based search and retrieval tools for documentation, enabling large language models to reference relevant context in their responses. It supports managing multiple documentation sources, semantic search, and real-time context delivery. Documentation can be indexed, searched, and managed with queueing and processing features, making it highly suitable for AI-driven assistants. Integration with Claude Desktop and support for Qdrant vector databases is also available.

238 29 MCP

41

In Memoria

Persistent memory and instant context for AI coding assistants, integrated via MCP.

In Memoria is an MCP server that enables AI coding assistants such as Claude or Copilot to retain, recall, and provide context about codebases across sessions. It learns patterns, architecture, and conventions from user code, offering persistent intelligence that eliminates repetitive explanations and generic suggestions. Through the Model Context Protocol, it allows AI tools to perform semantic search, smart file routing, and track project-specific decisions efficiently.

94 17 MCP

42

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

43

VideoDB Agent Toolkit

AI Agent toolkit that exposes VideoDB context to LLMs with MCP support

VideoDB Agent Toolkit provides tools for exposing VideoDB context to large language models (LLMs) and agents, enabling integration with AI-driven IDEs and chat agents. It automates context generation, metadata management, and discoverability by offering structured context files like llms.txt and llms-full.txt, and standardized access via the Model Context Protocol (MCP). The toolkit ensures synchronization of SDK versions, comprehensive documentation, and best practices for seamless AI-powered workflows.

43 8 MCP

44

Octocode MCP

Enterprise-grade AI context server for codebase research and analysis.

Octocode MCP is a Model Context Protocol (MCP) server designed to enable AI assistants to search, analyze, and extract insights from millions of GitHub repositories with high security and token efficiency. It offers intelligent orchestration for deep code research, planning, and agentic workflows, streamlining the process of building and understanding complex software projects. The platform features robust tools and commands, such as /research for expert code research, designed to support developers and AI systems with context-rich information.

577 45 MCP

45

Biel.ai MCP Server

Seamlessly connect IDEs to your company’s product documentation using an MCP server.

Biel.ai MCP Server enables AI tools such as Cursor, VS Code, and Claude Desktop to access and utilize a company’s product documentation and knowledge base through the Model Context Protocol. It provides a hosted RAG layer that makes documentation searchable and usable, supporting real-time, context-rich completion and answers for developers. The server can be used as a hosted solution or self-hosted locally or via Docker for advanced customization.

2 2 MCP

46

MCP Claude Code

Claude Code-like functionality via the Model Context Protocol.

Implements a server utilizing the Model Context Protocol to enable Claude Code functionality, allowing AI agents to perform advanced codebase analysis, modification, and command execution. Supports code understanding, file management, and integration with various LLM providers. Offers specialized tools for searching, editing, and delegating tasks, with robust support for Jupyter notebooks. Designed for seamless collaboration with MCP clients including Claude Desktop.

281 33 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

Vercel AI SDK Documentation MCP Agent

AI-powered documentation agent for Vercel AI SDK with Model Context Protocol support.

The Vercel AI SDK Documentation MCP Agent is a server implementing the Model Context Protocol to enable AI-powered search and conversational querying of the Vercel AI SDK documentation. It features natural language understanding, semantic search using FAISS, and session-based context management for in-depth assistance. Integration with popular MCP clients like Claude Desktop and Cursor ensures seamless use in developer workflows. Automated documentation indexing and a Gemini-powered agent enhance accuracy and contextuality of responses.

41 8 MCP

49

codemirror-mcp

CodeMirror extension for Model Context Protocol resource mentions and prompt commands

codemirror-mcp provides a CodeMirror extension that implements the Model Context Protocol (MCP) to enable resource mention handling and prompt command integration within code editors. It offers autocomplete, visual decorations, and interaction support for '@resource' mentions, as well as command triggers using the '/prompt' syntax. The extension integrates with model context servers using a defined transport and enhances the editor experience with resource click handling and customizable theming.

78 3 MCP

50

mcp-server-templates

Deploy Model Context Protocol servers instantly with zero configuration.

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

5 1 MCP

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