"DTS" matching MCP servers:

An MCP server that enables web search and page content retrieval via the Keenable API, supporting search with filters and fetching clean markdown content from indexed URLs.

Enables LLM hosts to perform grounded, cited retrieval and answer generation over your own documents using hybrid BM25 and dense search, with explicit refusal when answers are not supported by the sources.

Enables AI assistants to search the web, conduct deep research, extract web content, and get AI-powered answers in real-time via the KEIRO API.

Enables AI assistants to access and search Expo documentation with semantic search and AI-enhanced code examples and explanations using Gemini AI.

Enables coding agents to query a local, offline memory store of past session traces through hybrid BM25 plus semantic retrieval over extracted memories and chunks. Lets users recall relevant memories, search chunks and sessions, and explore cross-session clusters directly from their agent.

Enables AI assistants to interact with Meilisearch via the Model Context Protocol, allowing comprehensive index, document, and search management through a standardized interface.

Enables AI assistants to interact with Meilisearch through a standardized interface, supporting index and document management, search capabilities, settings configuration, task monitoring, and experimental vector search.

DEVONthink 4 connector with six tools for search, retrieval, and write operations. Dry-run by default, append-only audit log, selective undo via audit_id; macOS-only, MIT, local-only, clean-room implementation.

A Model Context Protocol server that enables interaction with Chop's Setup system, providing an interface to retrieve setup information via a REST API.

Enables MCP clients to browse a local skill library, retrieve individual skill instructions and files, route task queries via Jev, and report completion activity.

A cloud-based vector memory service that provides AI assistants with persistent storage, semantic search, and entity management via the Model Context Protocol. It features multi-tenant isolation and bidirectional synchronization with macOS and Google contacts and calendars.

Provides ranked full-text search over Obsidian vaults using SQLite FTS5, BM25 scoring, and multilingual stemming, adding a vault_fts_search tool to find relevant notes beyond exact line matches.

A TypeScript implementation of the Model Context Protocol server that enables creation, management, and semantic search of memory streams with Mem0 integration.

A Python backend implementing the Model Context Protocol with Azure OpenAI integration, enabling applications to interact with LLMs through a standardized interface with streaming capabilities.

Enables AI agents to perform grounded web research with injection resistance, claim verification, and cost-aware routing through MCP tools like web_search, fetch_url, extract_claims, and check_grounding.

Long-term memory MCP server for Claude Code with SQLite FTS5 full-text search, BM25 ranking, access tracking, and upsert deduplication. Zero config via npx.

Enables intent-based semantic search over external design system documentation, allowing MCP-compatible AI assistants to retrieve relevant design tokens, component architectures, and code patterns via a single tool.

Provides access to LangSearch's Web Search and Semantic Rerank APIs for AI assistants. It enables web searching with advanced filtering and reranking of documents based on semantic relevance.

A Model Context Protocol server for generating text embeddings using OpenAI, Anthropic, or Ollama, with tools for single and batch embedding operations.

Exposes code search and file reading tools over the Model Context Protocol, enabling any MCP-compatible client to query a codebase with natural language.