# Semantic search

A semantic search MCP service based on the Qdrant vector database, supporting multi - collection retrieval and configurable result return

A Machine Control Protocol (MCP) server based on the Qdrant vector database, used for storing and retrieving text information, supporting semantic search and FastEmbed integration.

A TypeScript-based MCP server that integrates with Mem0 to provide memory stream functions

This is a knowledge base management tool based on the MCP server, which provides a list of knowledge base content and retrieval functions, and supports semantic search and automatic index updates.

The MCP Registry Server project provides a semantic search-based MCP server retrieval function, supporting quick installation through the Smithery tool and integration with Claude Desktop for use.

The mem0 MCP Server provides structured memory storage and semantic search services for project management

An MCP server based on Claude for document management and semantic search using Needle

This project is an MCP server for Federal Open Market Committee (FOMC) statement analysis and retrieval, providing semantic search, trend analysis, and metadata access functions, and handling complex data processing processes through a simple tool interface.

Context Lens is a local semantic search tool that can convert any content into a searchable knowledge base, enabling AI assistants to understand the meaning rather than just match keywords. It uses a built - in LanceDB vector database, supports local files, GitHub repositories, and URL content, does not require an API key or cloud service, and processes data completely locally.

Claude Context is an MCP plugin that provides in - depth context of the entire codebase for AI programming assistants through semantic code search. It supports multiple embedding models and vector databases to achieve efficient code retrieval.

A high-performance MCP server that provides persistent multimodal context storage for LLM agents, supports thread isolation, metadata filtering, full-text search, and semantic search, and is compatible with SQLite and PostgreSQL backends.

This is an MCP server for Microsoft Dynamics 365 Finance & Operations development. It accesses over 50,000 F&O standard components through semantic search, enabling AI assistants to find relevant implementation patterns and read local source code during development.

Glider is a Roslyn-based MCP server that provides semantic analysis, intelligent refactoring, and architecture exploration capabilities for C# code in MCP clients (such as Claude Code).

JitAPI is an MCP server that enables LLMs to interact with any API by dynamically discovering relevant endpoints in the OpenAPI specification. It uses semantic search and dependency graphs to find only the endpoints required for each task, supporting multi-API registration, LLM-driven workflow planning, and general execution.

markymark is a language server and AI agent tool for Markdown and structured data files, providing navigation, refactoring, search, and diagnostic functions, and supporting the LSP and MCP protocols.

Kolada MCP Server is an intelligent middleware that connects large language models with the Swedish Kolada statistical database, providing functions such as semantic search, KPI analysis, and multi - year comparison, simplifying the query and interpretation of public - sector data.

This project is a semantic search tool based on Elasticsearch for semantic retrieval of Search Labs blog posts, including crawler configuration, index mapping updates, and MCP server integration functions.

An MCP server that connects AI assistants with HubSpot CRM data, providing access to contact, company, and interaction data. Built - in vector storage and caching mechanisms optimize performance.

This project is a semantic search tool based on Elasticsearch for semantic retrieval of Search Labs blog posts, including crawler configuration, index mapping update, and MCP server integration functions.

The MCP-RAG Server is an implementation based on the Model Context Protocol (MCP), aiming to provide real-time document access to AI assistants through semantic vector search, thereby generating context-aware responses based on the latest information.

A knowledge graph server based on Neo4j, integrating AI models and the MCP protocol, supporting dynamic knowledge management and semantic search.

An MCP server, CLI tool, and TypeScript library for exploring JSR (JavaScript repository), providing semantic search, package detail viewing, download statistics, and document retrieval functions, and supporting the Deno environment.

CodeFlow is an intelligent code analysis tool that generates detailed call graphs by parsing the abstract syntax tree of the code and provides semantic search functionality. It includes two interfaces, a CLI tool and an MCP server, aiming to help developers understand complex codebases with minimal cognitive burden.

A lightning-fast, language-agnostic code analysis MCP server built on Rust, offering instant symbol lookup, reference tracking, and semantic code search. Designed for large codebases with performance as a priority.

BuildAutomata Memory is a persistent memory system based on the MCP protocol, providing semantic search and versioned memory storage across sessions for AI agents, supporting intelligent classification, timeline tracing, and multi-tool synchronization

A privacy - first document search server that runs entirely locally, providing semantic search functions for AI programming tools through the MCP protocol. No API keys or cloud services are required, and all data processing is completed on the user's computer.

DeepContext is an MCP server that provides symbol - aware semantic search capabilities for code assistants. By intelligently parsing code structure and semantic relationships, it can accurately locate relevant code snippets in large codebases and improve development efficiency.

This is an MCP service that provides a free public API directory, supports semantic search and detailed API information queries, and is built on a public API dataset.

DMCP is a semantic tool discovery protocol that solves the problem of too many tools in MCP servers. It realizes on-demand query-driven tool discovery through vector search, significantly reducing token consumption and improving the accuracy of tool selection.

This is an MCP server designed for the Smart Connections plugin, providing read-only semantic search functionality for the Obsidian knowledge base, emphasizing security and lightweight implementation.