anythingllm-mcp
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- AlicenseAqualityBmaintenanceEnables managing and controlling AnythingLLM instances through MCP, providing tools to list, create, and delete workspaces, retrieve system environment settings, and get vector counts.51MIT
- AlicenseAqualityBmaintenanceEnables MCP-compatible clients to interact with AnythingLLM, providing tools for workspace management, chat and thread operations, document operations, vector search, and system inspection.346MIT
- AlicenseAqualityCmaintenanceEnables AI assistants to search and ask questions about documents stored in AnythingLLM workspaces through MCP tools.4MIT
- AlicenseBqualityDmaintenanceEnables seamless integration with AnythingLLM instances, providing complete workspace management, chat operations, document handling, user administration, and AI agent configuration through natural language.3845 npm16MIT
- FlicenseCqualityDmaintenanceMCP server for AnythingLLM that enables AI document chat platform interaction with tools for workspaces, chat, documents, threads, and system operations.17-
- AlicenseNot gradedqualityCmaintenanceEnables AnythingLLM to be controlled by any MCP-compatible client via HTTP, SSE, or WebSocket, with automatic workspace selection and background operation.MIT
TDQS
Scored across 9 tools
Each tool maps to a distinct resource+action: the ask_workspace/get_answer pair forms a clear async job pattern, and workspace CRUD (list/get/create/update/delete) is unambiguous. The only mild overlap is embedded documents appearing in get_workspace vs list_documents, but descriptions clearly differentiate them.
All names follow a clean verb_noun pattern (list_workspaces, get_workspace, create_workspace, update_workspace, delete_workspace, list_documents, update_embeddings, ask_workspace, get_answer). No convention mixing or vague verbs.
Nine tools is well-scoped for an AnythingLLM management server, with each tool earning its place across workspace management, chat, and embeddings.
Workspace lifecycle is fully covered (list/get/create/update/delete) and the chat flow has a complete async request+poll pair. The one notable gap is document ingestion—there is no tool to create/upload documents, only to list them and attach/remove existing ones, so new content must be added externally.