Gemini Embedding 2 MCP Server
Related Servers
Alternatives to Gemini Embedding 2 MCP Server
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityCmaintenanceProvides a self-learning multimodal memory server with cross-modal retrieval across text, images, audio, and code via MCP tools and resources.Apache 2.0
- AlicenseNot gradedqualityDmaintenanceA self-hosted, multi-context memory server that enables AI agents to search and retrieve information from local documents and crawled websites via MCP tools. It runs fully offline using Postgres and Ollama to provide secure, private knowledge management and retrieval-augmented generation.2MIT
- AlicenseNot gradedqualityBmaintenanceA lightweight, local-first MCP memory server for LLM agents that enables storing, searching, and retrieving agent memories with zero external dependencies.1MIT
- AlicenseAqualityBmaintenanceMCP server for persistent, cross-session, local-first memory for AI agents, storing memories as Markdown files with SQLite indexing for hybrid search.24Apache 2.0
- FlicenseNot gradedqualityDmaintenanceAn MCP server for managing persistent AI memory using hybrid search (keyword + semantic vector) with SQLite storage and offline-first local embeddings.-
- AlicenseAqualityCmaintenanceA local, fully-offline MCP memory server that enables persistent storage and retrieval of information using SQLite with both keyword and semantic vector search capabilities.1019 npm13MIT
TDQS
Scored across 7 tools
Each tool targets a distinct operation: indexing, previewing, listing, searching, context retrieval, removal, and syncing. No functional overlap exists.
All tool names follow a consistent verb_noun pattern in snake_case, e.g., index_directory, list_indexed_directories, search_my_documents. The pattern is uniform and predictable.
With 7 tools, the server covers the essential workflows for local embedding and retrieval without excess or deficiency. The count fits well with the domain scope.
Provides a full lifecycle: create (index_directory), read (search, get_result_context, list), update (sync_indexed_directories), delete (remove_directory_from_index), plus a dry-run preview. No obvious gaps.