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workspace-qdrant-mcp

Verified Safe

by ChrisGVE

Overview

A semantic workspace platform that provides project-scoped vector database operations through a Model Context Protocol (MCP) server, backed by a high-performance Rust daemon for file watching, processing, and ingestion. It enables LLM agents to naturally interact with project knowledge through conversational memory and hybrid semantic search.

Installation

Run Command
python -m workspace_qdrant_mcp.main --transport http

Environment Variables

  • QDRANT_URL
  • QDRANT_API_KEY
  • FASTEMBED_MODEL
  • WORKSPACE_QDRANT_LOG_LEVEL
  • WORKSPACE_QDRANT_QDRANT__URL
  • CLAUDE_MODEL
  • HOME
  • PATH

Security Notes

The system demonstrates strong architectural security principles, notably 'Daemon-Only Writes' to Qdrant (First Principle 10), which centralizes data modification through a trusted Rust component and prevents direct writes from potentially less secure LLM agents or the Python MCP server. Sensitive data handling includes log sanitization (e.g., API keys, passwords) and binary validation for CLI-managed executables. TLS for gRPC communication is 'infrastructure ready' but not explicitly marked as deployed, posing a potential risk in untrusted network environments if not otherwise secured. Configuration is managed using environment variables, avoiding hardcoded secrets.

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Stats

Interest Score30
Security Score9
Cost ClassHigh
Avg Tokens250
Stars1
Forks0
Last Update2026-01-19

Tags

semantic searchvector databaseLLM agentsconversational memoryfile watchingRust daemonPython serverQdrantSQLiteCLImulti-tenant