"CTS" matching MCP servers:

Enables BM25 lexical search over a user-provided corpus of CTF writeups or technical documents through an MCP tool, returning relevant results with optional category and solved filters. It can run locally over stdio or as a centralized HTTP service shared by multiple MCP clients.

Codebase intelligence and context engine for AI coding agents: search, symbol lookup, impact analysis, and context building via MCP.

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.

A Context-as-a-Service MCP server that maintains structured, graph-based context for Shopify apps by extracting and summarizing data from web sources and help centers. It enables multi-agent systems to retrieve isolated, provenance-backed context slices or starter bundles via push and pull mechanisms.

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.

A Model Context Protocol (MCP) server that enables Claude to use Monte Carlo Tree Search algorithms for deep, explorative analysis of topics, questions, or text inputs.

Enables MCP-capable AI clients to share one local SQLite-backed memory of preferences, decisions, tasks, and handoffs across sessions and models. It supports saving, searching, recalling, exporting, and restoring context through tools like remember, recall, get_context, and save_handoff.

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.

A ready-to-use starter implementation of the Model Context Protocol (MCP) server that enables applications to provide standardized context for LLMs with sample resources, tools, and prompts.

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

An MCP server that converts GitHub repositories and documentation sites into token-counted, searchable context blobs for AI agents, with tools like pack_repo, search_context, and pack_docs.

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

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.

Gives any AI assistant three tools to search IRDAI health-insurance rules, flag non-payable bill items, and check an insurance claim against the policy wording so each deduction is judged with a verified quote and the payable amount is recalculated.

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