{"id":"qdrant-llamaindex-mcp-server","name":"qdrant-llamaindex-mcp-server","af_score":60.2,"security_score":48.2,"reliability_score":27.5,"what_it_does":"Provides a Model Context Protocol (MCP) server exposing tools to read (and optionally write) documents stored in a Qdrant vector database that were indexed by LlamaIndex. It supports dynamic collection selection at runtime and attempts to adapt to various LlamaIndex payload/content field formats. For embeddings, it detects the embedding model per collection and embeds queries using a whitelisted set of allowed models, otherwise falling back to a default model.","best_when":"You run an MCP-capable LLM app/agent that needs read-only or controlled write access to LlamaIndex data in Qdrant and you want automatic handling of differing payload schemas and embedding model selection.","avoid_when":"You cannot restrict or secure access to the server/tooling (especially if write tools are enabled), or you require strict guarantees about embedding model provenance and resource usage while the embedding whitelist is permissive or disabled.","last_evaluated":"2026-04-04T21:47:10.384201+00:00","has_mcp":true,"has_api":false,"auth_methods":["Qdrant API key via QDRANT_API_KEY (passed through from environment)","MCP transport security not specified in README; server is configured via FastMCP transport (stdio/sse/streamable-http)"],"has_free_tier":false,"known_gotchas":["Write tools may be enabled when QDRANT_READ_ONLY=false; ensure you keep read-only mode on for safety with autonomous agents.","Embedding model whitelist can block collections; the server falls back to EMBEDDING_MODEL when a collection’s model is not allowed, which may produce retrieval quality changes.","Collection names are supplied dynamically by MCP clients; agents must pass correct collection_name for each call.","If using vector search by raw vector (qdrant-search-by-vector), clients must supply correctly shaped vectors (array of floats) matching the target collection’s vector config."],"error_quality":0.0}