Chroma MCP Server - Alternatives & Competitors

Ranked by Relevance

• 1
  

  Weaviate MCP Server

  A server implementation for the Model Context Protocol (MCP) built on Weaviate.

  Weaviate MCP Server provides a backend implementation of the Model Context Protocol, enabling interaction with Weaviate for managing, inserting, and querying context objects. The server facilitates object insertion and hybrid search retrieval, supporting context-driven workflows required for LLM orchestration and memory management. It includes tools for building and running a client application, showcasing integration with Weaviate's vector database.

  157 38 MCP
• 2
  

  mcp-server-qdrant

  Official Model Context Protocol server for seamless integration with Qdrant vector search engine.

  mcp-server-qdrant provides an official implementation of the Model Context Protocol for interfacing with the Qdrant vector search engine. It enables storing and retrieving contextual information, acting as a semantic memory layer for LLM-driven applications. Designed for easy integration, it supports environment-based configuration and extensibility via FastMCP. The server standardizes tool interfaces for managing and querying contextual data using Qdrant.

  1,054 187 MCP
• 3
  

  VikingDB MCP Server

  MCP server for managing and searching VikingDB vector databases.

  VikingDB MCP Server is an implementation of the Model Context Protocol (MCP) that acts as a bridge between VikingDB, a high-performance vector database by ByteDance, and AI model context management frameworks. It allows users to store, upsert, and search vectorized information efficiently using standardized MCP commands. The server supports various operations on VikingDB collections and indexes, making it suitable for integrating advanced vector search in AI workflows.

  3 5 MCP
• 4
  

  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
• 5
  

  mcp-pinecone

  A Pinecone-backed Model Context Protocol server for semantic search and document management.

  mcp-pinecone implements a Model Context Protocol (MCP) server that integrates with Pinecone indexes for use with clients such as Claude Desktop. It provides powerful tools for semantic search, document reading, listing, and processing within a Pinecone vector database. The server supports operations like embedding, chunking, and upserting records, enabling contextual management of large document sets. Designed for ease of installation and interoperability via the MCP standard.

  150 35 MCP
• 6
  

  MCP Local RAG

  Privacy-first local semantic document search server for MCP clients.

  MCP Local RAG is a privacy-preserving, local document search server designed for use with Model Context Protocol (MCP) clients such as Cursor, Codex, and Claude Code. It enables users to ingest and semantically search local documents without using external APIs or cloud services. All processing, including embedding generation and vector storage, is performed on the user's machine. The tool supports document ingestion, semantic search, file management, file deletion, and system status reporting through MCP.

  10 3 MCP
• 7
  

  Couchbase MCP Server

  Enable LLMs to interact directly with Couchbase clusters via the Model Context Protocol.

  Couchbase MCP Server provides an MCP-compliant server for connecting Large Language Models to Couchbase clusters. It supports various database operations such as bucket and collection listing, document retrieval, upsert, and deletion, as well as running SQL++ queries and retrieving index information. Designed for easy integration with MCP clients like Claude Desktop, it includes features for secure authentication and query mode configuration. The server can be deployed using a prebuilt PyPI package or directly from source.

  24 28 MCP
• 8
  

  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
• 9
  

  Vectorize MCP Server

  MCP server for advanced vector retrieval and text extraction with Vectorize integration.

  Vectorize MCP Server is an implementation of the Model Context Protocol (MCP) that integrates with the Vectorize platform to enable advanced vector retrieval and text extraction. It supports seamless installation and integration within development environments such as VS Code. The server is configurable through environment variables or JSON configuration files and is suitable for use in collaborative and individual workflows requiring vector-based context management for models.

  97 21 MCP
• 10
  

  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
• 11
  

  Raindrop.io MCP Server

  Enable LLMs to manage and search Raindrop.io bookmarks via the Model Context Protocol.

  Raindrop.io MCP Server is an integration that allows large language models to interact with Raindrop.io bookmarks using the Model Context Protocol. It provides tools to create and search bookmarks, including filtering by tags, and is designed for interoperability with environments like Claude for Desktop. Installation can be done via Smithery or manually, and configuration is managed through environment variables. The project is open source and optimized for secure, tokenized access to Raindrop.io.

  63 15 MCP
• 12
  

  YDB MCP

  MCP server for AI-powered natural language database operations on YDB.

  YDB MCP acts as a Model Context Protocol server enabling YDB databases to be accessed via any LLM supporting MCP. It allows AI-driven and natural language interaction with YDB instances by bridging database operations with language model interfaces. Flexible deployment through uvx, pipx, or pip is supported, along with multiple authentication methods. The integration empowers users to manage YDB databases conversationally through standardized protocols.

  24 7 MCP
• 13
  

  memvid-mcp-server

  A Streamable HTTP MCP Server for encoding and semantically searching video-based memory.

  memvid-mcp-server provides a Model Context Protocol (MCP) compatible HTTP server that leverages memvid to encode text data into videos. It supports adding text chunks as video and performing semantic search over them using standardized MCP actions such as add_chunks and search. The server can be integrated with MCP clients via streamable HTTP and enables fast context retrieval for AI applications.

  8 3 MCP
• 14
  

  Multi-Database MCP Server (by Legion AI)

  Unified multi-database access and AI interaction server with MCP integration.

  Multi-Database MCP Server enables seamless access and querying of diverse databases via a unified API, with native support for the Model Context Protocol (MCP). It supports popular databases such as PostgreSQL, MySQL, SQL Server, and more, and is built for integration with AI assistants and agents. Leveraging the MCP Python SDK, it exposes databases as resources, tools, and prompts for intelligent, context-aware interactions, while delivering zero-configuration schema discovery and secure credential management.

  76 19 MCP
• 15
  

  MCP MongoDB Server

  A Model Context Protocol server for LLM interaction with MongoDB databases.

  MCP MongoDB Server enables large language models to interact with MongoDB databases through the standardized Model Context Protocol interface. It provides schema inspection, document querying, aggregation, and write operations with intelligent ObjectId handling and flexible read-only configurations. Designed for seamless integration with tools like Claude Desktop, it offers collection completions, schema inference, and robust support for both development and production environments.

  267 50 MCP
• 16
  

  Optuna MCP Server

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

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

  65 21 MCP
• 17
  

  MongoDB MCP Server

  A Model Context Protocol server for enabling LLM interaction with MongoDB databases.

  MongoDB MCP Server empowers language models to interface directly with MongoDB databases using the Model Context Protocol (MCP). It enables natural language querying and management of collections, documents, and indexes. Users can inspect database schemas, execute document operations, and manage indexes seamlessly. The tool integrates with clients like Claude Desktop for conversational database management.

  172 33 MCP
• 18
  

  Unsplash MCP Server

  Seamless Unsplash image integration via the Model Context Protocol.

  Unsplash MCP Server provides a simple and robust interface to search and integrate high-quality Unsplash images through the Model Context Protocol (MCP). It offers advanced photo search capabilities with filters for keywords, color schemes, orientation, and sorting. Designed for easy integration with development environments such as Cursor and Smithery, it simplifies embedding Unsplash image search into AI and automation workflows.

  186 20 MCP
• 19
  

  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
• 20
  

  Quarkus Model Context Protocol Servers

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

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

  176 46 MCP
• 21
  

  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
• 22
  

  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
• 23
  

  Parallel Search MCP

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

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

  3 2 MCP
• 24
  

  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
• 25
  

  NCBI Literature Search MCP Server

  Seamless PubMed literature search via Model Context Protocol server.

  NCBI Literature Search MCP Server provides a Model Context Protocol (MCP) interface to search the vast PubMed database using natural language queries. It enables AI assistants to conduct comprehensive and advanced literature searches across biological and biomedical disciplines, returning metadata such as abstracts, author lists, MeSH terms, and DOIs. Designed for integration with AI tools, it supports advanced query capabilities and streamlines literature review and research discovery processes.

  6 1 MCP
• 26
  

  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
• 27
  

  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
• 28
  

  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.

  134 30 MCP
• 29
  

  QA Sphere MCP Server

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

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

  15 6 MCP
• 30
  

  Snowflake Cortex AI Model Context Protocol (MCP) Server

  Tooling and orchestration for Snowflake Cortex AI via Model Context Protocol.

  Provides an MCP server that brings Snowflake Cortex AI, object management, and SQL orchestration to the MCP ecosystem. Enables Cortex Search, Analyst, and Agent services for structured and unstructured data querying, along with automated SQL execution and object management. Designed for integration with MCP clients to streamline AI-powered data workflows and context-sensitive operations within Snowflake environments.

  176 60 MCP
• 31
  

  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
• 32
  

  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
• 33
  

  CrateDocs MCP

  MCP server for Rust crate documentation lookup and search

  CrateDocs MCP is an MCP (Model Context Protocol) server designed to provide AI models with access to Rust crate documentation. It enables lookup of crate-level and item-level documentation, as well as efficient searching of Rust crates on crates.io. The system supports various server modes, offers multiple output formats, and includes features for both developers and large language models.

  9 2 MCP
• 34
  

  Search1API MCP Server

  MCP server enabling search and crawl functions via Search1API.

  Search1API MCP Server is an implementation of the Model Context Protocol (MCP) that provides search and crawl services using the Search1API. It allows seamless integration with MCP-compatible clients, including LibreChat and various developer tools, by managing API key configuration through multiple methods. Built with Node.js, it supports both standalone operation and Docker-based deployment for integration in broader AI toolchains.

  157 39 MCP
• 35
  

  Chainlist MCP Server

  Fast, structured EVM chain info for AI agents via the Model Context Protocol

  Chainlist MCP Server enables AI agents and MCP-compatible clients to quickly access and search verified EVM blockchain data. It sources data from Chainlist.org and provides efficient REST-like tools for retrieving details by chain ID or searching by keyword. The server outputs structured Markdown responses, supporting AI context integration with tabulated RPC endpoints and explorers for clarity.

  2 2 MCP
• 36
  

  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
• 37
  

  Sourcerer MCP

  Semantic code search & navigation MCP server for efficient AI agent context retrieval.

  Sourcerer MCP provides a Model Context Protocol (MCP) server that enables AI agents to perform semantic code search and navigation. By indexing codebases at the function, class, and chunk level, it allows agents to retrieve only the necessary code snippets, greatly reducing token consumption. The tool integrates with Tree-sitter for language parsing and OpenAI for generating code embeddings, supporting advanced contextual code understanding without full file ingestion.

  95 11 MCP
• 38
  

  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
• 39
  

  OpenAI WebSearch MCP Server

  Intelligent web search with OpenAI reasoning model support, fully MCP-compatible.

  OpenAI WebSearch MCP Server provides advanced web search functionality integrated with OpenAI's latest reasoning models, such as gpt-5 and o3-series. It features full compatibility with the Model Context Protocol, enabling easy integration into AI assistants that require up-to-date information and contextual awareness. Built with flexible configuration options, smart reasoning effort controls, and support for location-based search customization. Suitable for environments such as Claude Desktop, Cursor, and automated research workflows.

  75 18 MCP
• 40
  

  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
• 41
  

  mcp-memgraph

  Expose Memgraph database features via the Model Context Protocol.

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

  52 5 MCP
• 42
  

  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
• 43
  

  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
• 44
  

  TrackMage MCP Server

  Shipment and logistics tracking MCP server with multi-carrier support.

  TrackMage MCP Server implements the Model Context Protocol (MCP) to provide shipment tracking, logistics management, and API integration for over 1,600 carriers worldwide. It allows integration with major LLMs, supports resources such as workspaces, shipments, orders, carriers, and tracking statuses, and offers tools to create, update, and monitor shipments and orders. The server supports OAuth-based authentication, flexible configuration via environment variables, and can be deployed locally for customized logistics operations.

  1 4 MCP
• 45
  

  MongoDB Lens

  Natural language MongoDB access via a local MCP server.

  MongoDB Lens offers a local Model Context Protocol (MCP) server that enables full-featured interaction with MongoDB databases using natural language queries through large language models. It provides tools for querying, running aggregations, schema analysis, performance optimization, and more. The server supports integration with a variety of MCP clients, making MongoDB data accessible and manageable by natural language commands. Users benefit from features such as connection aliasing, schema inference, and data protection mechanisms for sensitive operations.

  191 24 MCP
• 46
  

  Brave Search MCP Server

  MCP integration for web, image, news, video, and local search via Brave Search API.

  Implements a Model Context Protocol server that connects with the Brave Search API, enabling AI systems to perform comprehensive web, image, news, video, and local points of interest searches. Provides standardized MCP tools for various search types, each supporting advanced filtering parameters. Designed for easy integration in context-aware model interfaces such as Claude Code.

  86 17 MCP
• 47
  

  Ebook-MCP

  A Model Context Protocol server for conversational e-book interaction and AI integration.

  Ebook-MCP acts as a Model Context Protocol (MCP) server enabling seamless interaction between large language model (LLM) applications and electronic books such as EPUB and PDF. It standardizes APIs for AI-powered reading, searching, and managing digital libraries. Through natural language interfaces, it provides smart library management, content navigation, and interactive learning within digital books. Ebook-MCP integrates with modern AI-powered IDEs and supports multi-format digital book processing.

  132 23 MCP
• 48
  

  Kibela MCP Server

  MCP server for seamless LLM integration with Kibela knowledge management.

  Kibela MCP Server enables integration of Large Language Models (LLMs) with the Kibela note-sharing platform via the Model Context Protocol. It provides search, retrieval, and management of Kibela notes, users, groups, and folders, exposing these capabilities in a standardized MCP interface. The implementation utilizes Kibela's GraphQL API and supports configuration through environment variables and Docker. Designed for interoperability with tools like Cursor, it streamlines access and manipulation of organizational knowledge by AI systems.

  7 6 MCP
• 49
  

  Brave Search MCP Server

  MCP-compliant server providing advanced Brave Search API tools via STDIO and HTTP.

  Implements a Model Context Protocol (MCP) server for integrating with the Brave Search API, offering tools for web, local business, image, video, and news searches along with AI-powered summarization. Supports both STDIO and HTTP transports and adheres to established MCP conventions for context management. Provides structured tool schemas and customizable parameters to handle sophisticated search queries and results. Enables advanced filtering, multi-type result aggregation, and seamless integration for AI model workflows.

  337 71 MCP
• 50
  

  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